system

Abstract

We provide the system. [Solution] An information processing system for notifying recipients of deliveries of the delivery time in advance, A means of obtaining location information from a terminal device carried by the delivery person, A means of obtaining traffic information from an external database, A means for calculating the estimated delivery time of a delivery using the aforementioned location information and traffic information, A means of notifying the recipient of the calculated estimated delivery time, A means of receiving a notification from the recipient when they are unable to deliver, 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] In the logistics industry, when the recipient of the delivered item is absent, re-delivery is required, which increases the workload of the delivery person. Also, due to changes in traffic conditions, the delivery time becomes uncertain, making it difficult for the recipient to efficiently receive the delivered item. Such problems lead to an increase in logistics costs and a decrease in customer satisfaction, so a method for efficiently solving them is required.

Means for Solving the Problems

[0005] This invention provides a system that acquires location information from the delivery person's terminal device and traffic information from an external database, and uses this information to calculate the estimated delivery time with high accuracy. Based on the calculated estimated delivery time, the system sends advance notification to the recipient via email or other means. Furthermore, by providing a mechanism that allows recipients to easily contact the delivery person if they are absent, the system efficiently adjusts redeliveries and improves the efficiency of deliveries. In addition, by optimizing delivery routes based on traffic information and minimizing fluctuations in delivery times, the system improves the efficiency of delivery operations.

[0006] An "information processing system" is a computer system designed to manage information, including data acquisition, processing, analysis, and notification.

[0007] A "terminal device" is an electronic device carried by users or delivery personnel for inputting and receiving information, and which has the function of providing location information.

[0008] "Location information" is data that indicates the geographical location of a particular object, and is usually expressed using latitude and longitude.

[0009] "Traffic information" refers to data that shows current conditions related to road use, such as road congestion, traffic jams, and accident information, and is used to improve the operational efficiency of public transportation.

[0010] "Estimated delivery time" refers to information indicating the specific time when a delivery item is expected to arrive at the recipient's address.

[0011] "Advance notification" is a process that allows for planning, preparation, and response by informing recipients in advance of specific information.

[0012] A "delivery attempt notification" is a way for the recipient to inform the delivery company that they will not be able to receive the package at the designated delivery time.

[0013] "Redelivery" refers to the process of attempting to deliver an item to the recipient again after the initial delivery attempt has failed.

[0014] A "delivery route" is an optimized travel path for a delivery person to deliver a package, covering a specific section of the route. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0016] 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.

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

[0018] In the following embodiments, a 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.

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

[0020] In the following embodiments, a 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.

[0021] 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).

[0022] 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."

[0023] [First Embodiment]

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

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0030] 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.

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

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] This invention is an information processing system for improving the efficiency of delivery operations. The program processing of this system is described below in natural language.

[0037] Server Functions

[0038] The server first receives location information transmitted from the delivery person's terminal. This allows it to determine the delivery person's current location. Furthermore, the server obtains information about traffic conditions from an external traffic information database and analyzes it.

[0039] The server uses an AI algorithm to calculate the estimated delivery time for each delivery based on acquired location and traffic information. This also allows for the simultaneous planning of the most efficient delivery route. The calculated estimated delivery time is notified to the user in advance via email or other means.

[0040] Furthermore, if a user reports being unable to receive their delivery, the server collects that information via a link in the email and initiates the redelivery process. It also arranges a redelivery date and time and notifies the delivery person accordingly.

[0041] Device functions

[0042] The delivery person's device sends its current location information to the server at regular intervals. This process allows the server to continuously track the delivery person's location and maintain the optimal route and delivery time.

[0043] The terminal displays the optimal delivery route received from the server and issues real-time instructions to delivery personnel. This information includes route changes due to changes in traffic conditions.

[0044] User functions

[0045] The user receives and confirms an email notification from the server indicating the scheduled delivery time. This notification increases the likelihood of being home at the time of delivery. If the user is unable to be home at the scheduled time, they can notify the server of their absence via the link in the email.

[0046] As a concrete example, the server predicts a delivery to a user between 3 PM and 4 PM on October 5th and sends a delivery notification email. Because the user is unavailable at this time, they use the email link to inform the server of their absence. Based on this information, the server sets a new delivery date and time and notifies both the delivery person and the user. This improves the efficiency of redelivery and contributes to reducing logistics costs.

[0047] The following describes the processing flow.

[0048] Step 1:

[0049] The server operates a system that periodically receives location information from the delivery person's terminal, thereby allowing it to track the delivery person's real-time location.

[0050] Step 2:

[0051] The server retrieves traffic data from an external database and integrates it with received location information before importing it into the system. This process allows for a detailed analysis of the current status of delivery routes.

[0052] Step 3:

[0053] The server uses an AI algorithm based on location information and traffic conditions to calculate the estimated delivery time for each package. Simultaneously, it optimizes the delivery route based on these results.

[0054] Step 4:

[0055] The server sends the user an email notification with the calculated estimated delivery time. This email includes detailed delivery information and a link for missed delivery notifications.

[0056] Step 5:

[0057] Users receive and confirm notification emails from the server, and if they are unable to be home at the scheduled time, they use the provided link to inform the server of their absence.

[0058] Step 6:

[0059] The server receives a missed delivery notification from the user, automatically adjusts the available date and time for redelivery, and notifies the delivery person of the information.

[0060] Step 7:

[0061] The terminal checks the optimized delivery route sent from the server, receives real-time updates, and provides appropriate instructions to the delivery person.

[0062] Step 8:

[0063] The user receives an email notification from the server regarding the rescheduled delivery date and time, and plans the redelivery based on this notification.

[0064] (Example 1)

[0065] 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."

[0066] In delivery operations, delays due to factors such as traffic conditions and recipient absence are frequent, posing a challenge to efficient logistics. Furthermore, the efficiency of redelivery when recipients are absent at the scheduled delivery time is also a problem. These factors lead to increased logistics costs and decreased customer satisfaction, therefore, these issues need to be addressed.

[0067] 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.

[0068] In this invention, the server includes means for acquiring location information from a portable device, means for acquiring traffic information from an external information source, and means for calculating the estimated delivery time using the location information and traffic information. This enables the creation of efficient delivery plans in real time. Furthermore, by adjusting the date and time of redelivery, it is possible to improve delivery efficiency and customer satisfaction.

[0069] An "information processing system" is a set of devices or programs for collecting, analyzing, and processing information, and for generating specific results or instructions based on that information.

[0070] A "portable device" is a terminal device that a user can possess or carry with them, and that has the function of transmitting and receiving location information.

[0071] "Location information" refers to data that indicates the current location of a specific object, and is usually expressed as latitude and longitude.

[0072] "External information sources" refer to data sources that exist outside the system, such as databases and services that provide traffic information and other real-time data.

[0073] "Traffic information" refers to data that shows traffic flow, congestion, accident situations, etc., in a specific area or route.

[0074] "Estimated delivery time" refers to the time when the delivered item is expected to be delivered to the recipient, and is calculated taking into account factors such as traffic conditions and distance.

[0075] "Means of calculation" refers to calculations, or devices and programs, used to derive specific conclusions or results using the obtained data.

[0076] "Means of notification" refers to methods or technologies for informing a user or recipient of specific information, including forms such as email and app notifications.

[0077] "Means for receiving absence notifications" refers to a device or program that receives absence notifications from recipients and uses them to determine the next course of action.

[0078] "Means of adjusting the redelivery date and time" refers to a process or device that determines a new delivery date and time based on a missed delivery notice and informs the relevant parties of that information.

[0079] This invention is a method for streamlining delivery operations using an information processing system. The main components include a server, a portable terminal for delivery personnel, and a user.

[0080] First, the server receives location information transmitted from the delivery person's portable device. This location information is obtained using GPS technology and used to determine the delivery person's current location. The server also obtains traffic information from an external source. This source is a service that provides real-time traffic flow data, and the information can be aggregated via an API.

[0081] The server inputs the received location and traffic information into an AI algorithm to calculate the estimated delivery time for the package. This AI algorithm also plans the optimal delivery route, taking into account past data and current conditions. The AI ​​model used learns traffic patterns using machine learning techniques and can make predictions. These prediction results are stored in a database, and the server uses this to notify the user of the estimated delivery time.

[0082] The delivery driver's portable terminal receives optimal route information from the server and displays it on the terminal's screen. This information includes real-time traffic conditions and instructions for the best route. Because the portable terminal provides instructions to the delivery driver in real time, delivery efficiency can be improved.

[0083] The user receives a notification email from the server and confirms the scheduled delivery time. This notification includes a link that allows the user to easily report their absence if they are not available at the scheduled time. When the user uses this link to notify the server of their absence, the server arranges a new delivery date and time and informs both the delivery person and the user of the result.

[0084] As a concrete example, if a user is unable to receive a delivery, the server sends a notification email stating, "Delivery is scheduled for October 5th between 3 PM and 4 PM. If you will be absent, please use this link to contact us." This prompt allows the user to quickly notify the server of their absence, and the server can automatically arrange for redelivery. This improves delivery efficiency and customer satisfaction.

[0085] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0086] Step 1:

[0087] The server receives location information periodically transmitted from the delivery person's portable device. The location information used as input is coordinate data obtained using GPS technology. By storing this in a database, the server can identify the current location of the delivery person. Specifically, when the data is received, the server adds a timestamp and records the location information as part of the delivery history.

[0088] Step 2:

[0089] The server obtains real-time traffic information from external traffic information services. This data includes traffic flow, congestion, and road closures. The server analyzes this data as input and stores it in a database to identify changes in traffic conditions. Based on this information, it identifies traffic patterns and outputs the data in a formatted form for use in the next stage.

[0090] Step 3:

[0091] The server inputs the collected location and traffic information into an AI algorithm to calculate the estimated delivery time. Specifically, it passes this data to a generating AI model to predict the delivery time. The AI ​​model learns from past patterns and outputs the estimated delivery time along with the shortest route. The outputted estimated time and route information are used in the next notification step.

[0092] Step 4:

[0093] The server notifies the user of the calculated estimated delivery time. Specifically, it informs the user of the estimated delivery time in the form of an email or app notification. For example, it might send a message saying, "Your delivery is scheduled to arrive between 2 PM and 3 PM on October 5th." This output information is used to help the user prepare for receiving their delivery.

[0094] Step 5:

[0095] Users can notify the delivery service of their missed delivery via an email or in-app link that notifies them of the estimated delivery time. When a user clicks the link, the server receives the input and records it in the database as information indicating that redelivery is required. This input is used to schedule the next redelivery.

[0096] Step 6:

[0097] Based on the user's missed delivery notification, the server uses an AI algorithm to calculate and adjust the redelivery date and time. The AI ​​algorithm considers the current schedule and traffic information to output a new, available delivery date and time. The adjusted date and time are notified to the delivery person and the user and reflected in the delivery plan.

[0098] (Application Example 1)

[0099] 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."

[0100] To improve the efficiency of time management and delivery accuracy in delivery operations, accurate notification of scheduled delivery times and flexible handling of situations where recipients are absent are required. Furthermore, it is necessary to optimize delivery routes immediately in response to traffic conditions to increase efficiency.

[0101] 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.

[0102] In this invention, the server includes means for acquiring spatial information from terminal devices carried by delivery personnel, means for acquiring road condition information from external information sources, and means for calculating the estimated delivery time of the delivered items using the spatial information and road condition information. This enables improved delivery accuracy and efficient route management.

[0103] A "delivery person" is a person or organization responsible for transporting goods or items in order to carry out delivery operations.

[0104] A "terminal device" refers to an electronic device that is capable of inputting and displaying information and can communicate with external systems.

[0105] "Spatial information" refers to data that indicates the location of a specific point, and is geographical information obtained through methods such as GPS.

[0106] "External information sources" refer to databases and information systems that are located outside of servers and terminal devices and provide the necessary information.

[0107] "Road condition information" refers to traffic-related information that affects driving, such as road congestion and road passability.

[0108] "Estimated delivery time" refers to the time when the delivered item is expected to arrive at the designated delivery location.

[0109] A "beneficiary" refers to a person who receives benefits or advantages from receiving a delivery service.

[0110] An "absence notice" is information used to inform the recipient that they will be absent at the time of delivery, allowing for rescheduling of the delivery.

[0111] "Route information" refers to data about the optimal route for delivery personnel to reach their destination.

[0112] This invention provides a system that enables delivery personnel to efficiently perform delivery tasks and allows recipients to respond in a timely manner. The following hardware and software are used in the operation of this system.

[0113] The server receives spatial information at regular intervals from the terminal devices carried by delivery personnel to track their location. This spatial information includes GPS data, enabling highly accurate location determination. The server also obtains road condition information from external sources such as the Google® Maps API to understand traffic conditions in real time. Based on this, the server applies AI algorithms to calculate estimated delivery times and optimize delivery routes based on spatial and road condition information.

[0114] The terminal device displays optimal route information received from the server to the delivery person. This display utilizes a smartphone application to provide real-time directions and estimated arrival times. Based on this information, the delivery person can perform deliveries efficiently.

[0115] The recipient receives a notification of the estimated delivery time from the server via email or a mobile app. The notification includes a section for sending a missed delivery notification, allowing the recipient to easily inform the server of their situation when they are away. This facilitates smooth arrangement of redelivery.

[0116] For example, when a recipient orders lunch, the server takes traffic congestion into account and predicts that the food will be delivered in 45 minutes, notifying the recipient accordingly. If the recipient is not home at that time, they can use the provided link to reschedule the delivery.

[0117] An example of a prompt message to input into a generative AI model is as follows:

[0118] "Please use the Google Maps API to tell me the current best route and estimated arrival time. The delivery destination is Shinjuku."

[0119] This invention will improve delivery efficiency and enhance convenience for recipients.

[0120] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0121] Step 1:

[0122] The server receives spatial information transmitted from the delivery person's terminal device at regular intervals. This input data includes precise location information using GPS. The server receives this data and determines the delivery person's current location.

[0123] Step 2:

[0124] The server accesses the Google Maps API, an external source of information, to retrieve the latest road conditions. This information includes data on road congestion and passable routes. The retrieved information is used to analyze traffic patterns and find the optimal route.

[0125] Step 3:

[0126] The server uses an AI algorithm to analyze the spatial information obtained in Step 1 and the road condition information obtained in Step 2. This analysis calculates the estimated delivery time to each delivery destination and formulates the optimal route. The AI ​​learns traffic congestion patterns and selects the route that achieves the shortest delivery time.

[0127] Step 4:

[0128] The server sends the calculated estimated delivery time and route information as a notification to the recipient. This notification arrives via the recipient's email address or mobile app. The notification input includes the delivery address information, and the output presents the estimated delivery time to the recipient.

[0129] Step 5:

[0130] The terminal receives route information transmitted from the server and displays it to the delivery person in real time. In this process, the delivery person checks the route from their current location to the destination through an application installed on the terminal. This allows the delivery person to deliver quickly by following the optimal route.

[0131] Step 6:

[0132] When a user receives a notification, they click the link in the notification to report their absence to the server. This input includes their intention to be absent at the scheduled delivery time, and the server then arranges a new redelivery date and time as output.

[0133] Step 7:

[0134] Based on the user's absence notification, the server automatically readjusts the delivery person's schedule and creates a new delivery plan. This process streamlines redelivery and reduces costs. The server notifies the user of the new schedule and suggests the optimal time for both the user and the delivery person.

[0135] 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.

[0136] This invention combines an information processing system that notifies recipients of the delivery time in advance with a function that recognizes the user's emotions and optimizes the delivery experience based on those emotions. The program processing in this system is described below in natural language.

[0137] Server Functions

[0138] First, the server periodically receives location information transmitted from the delivery person's terminal and calculates the delivery route and estimated delivery time. Second, it activates an emotion engine via email and the interface to analyze the user's emotions. The emotion engine analyzes the user's responses and feedback to determine whether they are positive or negative about the delivery. Based on this emotion information, the server adjusts notification methods and message content to provide a more personalized delivery experience.

[0139] The server has a feature that simplifies the process for users to notify the delivery person of their absence, thereby reducing the stress associated with being away from home. This also makes scheduling redelivery smoother.

[0140] Device functions

[0141] The delivery driver's terminal updates and displays the optimal delivery route received from the server in real time. This information is linked to real-time traffic conditions, enabling efficient deliveries.

[0142] User functions

[0143] Users receive delivery notification emails from the server and can easily contact the server using a link if they are not home. Users can also express their emotions through feedback to the server, and the server will use this information to adjust the format of delivery notifications.

[0144] For example, when a user receives a delivery schedule via email in the morning, the sentiment engine analyzes the user's past response data and detects that their mood for the day is positive. Based on this, the server sends a notification in a friendly tone, providing the user with a stress-free experience. If the user is not home, the email concisely presents an option for missed delivery, and the server quickly arranges a redelivery date and time.

[0145] Thus, this system aims to improve the user experience and, in particular, to streamline delivery operations by enabling personalized responses based on emotions.

[0146] The following describes the processing flow.

[0147] Step 1:

[0148] The server periodically obtains location information from the delivery person's terminal device. This allows the server to determine the delivery person's real-time location.

[0149] Step 2:

[0150] The server retrieves traffic information from an external database and analyzes it in combination with location information. Based on this, an AI algorithm is used to calculate the estimated delivery time for the package.

[0151] Step 3:

[0152] The server uses an AI algorithm to calculate the optimal delivery route based on traffic information and transmits this information to the delivery person's terminal. This information enables the delivery person to make deliveries more efficiently.

[0153] Step 4:

[0154] The server creates a notification for the user based on the estimated delivery time and route information. The notification includes the estimated delivery time, as well as a link or button for contacting the user if they are unable to receive the delivery.

[0155] Step 5:

[0156] Using an emotion engine, the server analyzes past user data to estimate the user's emotional state. Based on the obtained emotional information, it adjusts the content and tone of notifications and sends them to the user.

[0157] Step 6:

[0158] The user checks the notification email from the server and, if there is a problem with the scheduled delivery time, uses the absence notification link to send an absence notification.

[0159] Step 7:

[0160] The server receives a missed delivery notification from the user and suggests the most suitable redelivery date and time. This allows the server to coordinate the details of the redelivery with the user.

[0161] Step 8:

[0162] The delivery driver's terminal follows the delivery route provided by the server and immediately receives and responds to any updated information. This is to utilize real-time information and maintain efficient deliveries.

[0163] Step 9:

[0164] The server collects data from the entire delivery operation and updates the database to use for future notifications and route optimization.

[0165] (Example 2)

[0166] 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".

[0167] While existing delivery information systems can notify recipients of delivery times, they struggle to provide personalized service that takes recipients' feelings into account. Furthermore, the process for redelivery in case of absence is cumbersome, highlighting the need for improved customer satisfaction.

[0168] 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.

[0169] In this invention, the server includes means for acquiring location information from a communication device carried by the delivery person, means for acquiring traffic conditions from an external information source, and means for driving an analysis device for analyzing the user's emotions. This enables the customization of delivery notifications based on the recipient's emotions and smooth redelivery procedures in case of absence.

[0170] A "communication device" is a device carried by a delivery person that has the function of transmitting location information to a server.

[0171] "External information source" refers to the platform to which the server connects to obtain information on traffic conditions.

[0172] "Location information" refers to latitude and longitude data indicating the delivery person's current location, and the delivery route is calculated based on this information.

[0173] "Traffic conditions" refers to dynamic information about roads, such as road congestion and traffic restrictions.

[0174] An "analysis device" is a core component of a system that analyzes user emotions and adjusts notification content based on that data.

[0175] "Estimated delivery time" refers to the estimated arrival time of a delivery item, calculated based on location information and traffic conditions.

[0176] "Notification content" refers to a message sent to the recipient that includes information such as the scheduled delivery time and redelivery options.

[0177] "Redelivery procedure" refers to the method of requesting redelivery for receiving a package when the recipient is absent, and is a process designed to simplify the procedure for the recipient.

[0178] This invention is an information system for improving the delivery experience for recipients of delivered goods. The specific implementation method is described below.

[0179] The server uses a GPS-enabled device to receive location information from the communication device carried by the delivery person. This device is equipped with a dedicated application and has the function to automatically transmit location data to the server. Based on the acquired location information, the server obtains traffic information from external sources. This external source utilizes traffic information systems provided via the internet. Specifically, for example, it uses the API of a map service provider to acquire real-time data.

[0180] The server operates an emotion analysis system that utilizes natural language processing technology to analyze user emotions. This system collects user feedback and past history, and identifies emotions using an AI model. For example, if a user sends positive feedback such as "I'm looking forward to the delivery," the server recognizes this as a positive emotion and adjusts the notification accordingly.

[0181] The terminal displays optimized delivery routes sent from the server, assisting delivery drivers with navigation. This allows delivery drivers to efficiently deliver packages to customers. The terminal is equipped with a map display function that reflects real-time location information.

[0182] Users can check the delivery time and status in real time through delivery notification emails received from the server. If they are not home, they can easily request redelivery by clicking a link included in the email. The absence notification process is provided through a user-friendly interface, significantly reducing the effort required.

[0183] Examples of specific prompt messages are as follows:

[0184] "Of all the delivery notifications you've received in the past, which one did you find the most pleasant? What was its tone and content?"

[0185] Thus, the system based on the present invention improves the user experience and supports efficient delivery operations.

[0186] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0187] Step 1:

[0188] The server receives location information from the delivery person's communication device. This location information is GPS data and includes latitude and longitude. The server receives this data and stores it in a database. Specifically, the server continuously updates this location information every minute.

[0189] Step 2:

[0190] The server obtains traffic information from external sources. The input consists of requests to a real-time traffic data API. The output data from this API includes traffic congestion and road closure information. The server analyzes this traffic information and uses it to optimize delivery routes. Specifically, the server analyzes the API response and applies an algorithm to calculate the most efficient route.

[0191] Step 3:

[0192] The server calculates the estimated delivery time based on location information and traffic conditions. Input includes location data and traffic data. The server uses this data to calculate travel time to each delivery point and generates the shortest possible delivery schedule. The output is the estimated delivery time, which is then notified to both the delivery person and the recipient. Specifically, the server uses an appropriate algorithm to estimate travel time and incorporates the estimated time into the notification email.

[0193] Step 4:

[0194] The server collects user feedback and analyzes its sentiment. Input includes user response data. A generative AI model is used to perform sentiment analysis on this text data. The output is data indicating the emotional state, which is used to adjust the tone of notifications. Specifically, the AI ​​model scans the text and categorizes the feedback as either positive or negative.

[0195] Step 5:

[0196] The terminal displays optimized route information sent from the server. Its input is route data received from the server. Based on this data, the terminal uses a map application to provide appropriate navigation instructions. As output, the delivery person receives real-time route instructions and uses them to navigate. Specifically, the terminal utilizes voice guidance and map displays to efficiently guide the delivery person to their destination.

[0197] Step 6:

[0198] The user receives a delivery notification and, if absent, requests redelivery. The input comes from a notification email from the server. This email contains a link to request redelivery; the user clicks this link to request redelivery. The output is the redelivery option selected by the user, which is reflected on the server. Specifically, the user specifies the next delivery time by filling out and submitting a simple form.

[0199] (Application Example 2)

[0200] 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 device 14 will be referred to as the "terminal."

[0201] In today's delivery services, recipients sometimes experience dissatisfaction with their delivery experience, particularly because delivery notifications are often uniform and do not reflect individual needs or feelings. Furthermore, the process of redelivery when recipients are absent can be cumbersome and stressful for them. There is a need to solve these problems and provide a better customer experience.

[0202] 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.

[0203] In this invention, the server includes means for acquiring geographical location information from a terminal device carried by the delivery person, means for acquiring traffic condition information from an external information source, and means for analyzing the recipient's emotional state and personalizing the notification message. This makes it possible to accurately calculate the estimated delivery time and provide a personalized delivery notification that corresponds to the recipient's emotional state.

[0204] An "information processing system" is an integrated system of hardware and software for collecting, processing, and analyzing data and providing results according to specific tasks or purposes.

[0205] "Geographic location information" refers to information used to identify a specific point on Earth, and is usually expressed using latitude and longitude.

[0206] "Traffic condition information" refers to information regarding current congestion levels and traffic speeds on roads and in traffic systems.

[0207] "Estimated delivery time" refers to the specific time when the delivered item is expected to be delivered to the recipient.

[0208] The "recipient" is the individual or organization that actually receives the delivered item.

[0209] An "absence notification" is a procedure or message used to notify the recipient that they will not be present at the designated time.

[0210] "Emotional state" refers to an individual's mental state and can be classified into positive or negative emotions.

[0211] "Personalization" is the process of adjusting or customizing information or services to suit specific individuals or circumstances.

[0212] This invention is an information processing system aimed at analyzing the emotional state of recipients and personalizing the delivery experience based on that analysis. The server first obtains the geographical location information of the delivery person and collects traffic condition information from external sources. Using this information, it accurately calculates the estimated delivery time. It also evaluates the emotional state of recipients by analyzing feedback from recipients and past data.

[0213] Based on this information, the server generates personalized delivery notification messages. For example, if the recipient is in a positive emotional state, the notification message will be sent in a friendly tone. Also, if the recipient is absent, the server provides a redirection option to make it easy for them to report the absence.

[0214] The terminal device displays the optimal delivery route, reflecting the delivery person's real-time geographical location and traffic conditions. This allows delivery people to make deliveries efficiently.

[0215] Recipients receive notifications from the server via email or other electronic means, allowing for flexible responses when they are unavailable. Generative AI models are used for sentiment analysis throughout this process. For example, if a recipient has provided positive feedback on past orders, the next notification message will be a friendly one, such as "Have a great day!" Another example of a prompt for the generative AI model during sentiment analysis is, "Consider the user's past feedback to determine their positive or negative emotional state, and create a food delivery notification message based on that."

[0216] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0217] Step 1:

[0218] The server receives geographical location information from a terminal device carried by the delivery person. The input is real-time location data transmitted from the terminal, and the output is geographical location coordinates stored on the server. Based on this data, the server performs an operation to determine the delivery person's current location.

[0219] Step 2:

[0220] The server obtains traffic condition information from external sources. The input is current traffic data received through the API of a traffic information service, and the output is analyzed data regarding traffic congestion and road conditions. This allows the server to analyze traffic conditions that may affect deliveries.

[0221] Step 3:

[0222] The server retrieves past feedback data to analyze the recipient's emotional state. The input is the recipient's feedback history, and the output is the result of the emotional state analysis using a generative AI model. This allows the server to identify the recipient's past tendencies towards positive or negative emotions.

[0223] Step 4:

[0224] The server uses geographical location and traffic information to calculate the estimated delivery time for the package. The input is the current location and traffic data obtained in the previous step, and the output is the optimal delivery time prediction. This allows the server to plan an efficient delivery route.

[0225] Step 5:

[0226] The server generates a notification message to send to the recipient, reflecting the results of sentiment analysis. The input is the analyzed sentiment data, and the output is a personalized delivery notification message. The server uses this to generate a personalized message for the recipient.

[0227] Step 6:

[0228] Users receive personalized delivery notification messages from the server and take actions such as reporting absences as needed. The input is the message sent from the server, and the output is the user's response and absence report data. This allows users to easily communicate their reactions to the server.

[0229] Step 7:

[0230] The terminal displays real-time updated delivery route information to the delivery person. The input is optimized route information sent from the server, and the output is navigation instructions displayed on the terminal. This enables delivery people to perform deliveries efficiently.

[0231] 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.

[0232] 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.

[0233] 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.

[0234] [Second Embodiment]

[0235] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0236] 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.

[0237] 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).

[0238] 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.

[0239] 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.

[0240] 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).

[0241] 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.

[0242] 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.

[0243] 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.

[0244] 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.

[0245] 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.

[0246] 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".

[0247] This invention is an information processing system for improving the efficiency of delivery operations. The program processing of this system is described below in natural language.

[0248] Server Functions

[0249] The server first receives location information transmitted from the delivery person's terminal. This allows it to determine the delivery person's current location. Furthermore, the server obtains information about traffic conditions from an external traffic information database and analyzes it.

[0250] The server uses an AI algorithm to calculate the estimated delivery time for each delivery based on acquired location and traffic information. This also allows for the simultaneous planning of the most efficient delivery route. The calculated estimated delivery time is notified to the user in advance via email or other means.

[0251] Furthermore, if a user reports being unable to receive their delivery, the server collects that information via a link in the email and initiates the redelivery process. It also arranges a redelivery date and time and notifies the delivery person accordingly.

[0252] Device functions

[0253] The delivery person's device sends its current location information to the server at regular intervals. This process allows the server to continuously track the delivery person's location and maintain the optimal route and delivery time.

[0254] The terminal displays the optimal delivery route received from the server and issues real-time instructions to delivery personnel. This information includes route changes due to changes in traffic conditions.

[0255] User functions

[0256] The user receives and confirms an email notification from the server indicating the scheduled delivery time. This notification increases the likelihood of being home at the time of delivery. If the user is unable to be home at the scheduled time, they can notify the server of their absence via the link in the email.

[0257] As a concrete example, the server predicts a delivery to a user between 3 PM and 4 PM on October 5th and sends a delivery notification email. Because the user is unavailable at this time, they use the email link to inform the server of their absence. Based on this information, the server sets a new delivery date and time and notifies both the delivery person and the user. This improves the efficiency of redelivery and contributes to reducing logistics costs.

[0258] The following describes the processing flow.

[0259] Step 1:

[0260] The server operates a system that periodically receives location information from the delivery person's terminal, thereby allowing it to track the delivery person's real-time location.

[0261] Step 2:

[0262] The server retrieves traffic data from an external database and integrates it with received location information before importing it into the system. This process allows for a detailed analysis of the current status of delivery routes.

[0263] Step 3:

[0264] The server uses an AI algorithm based on location information and traffic conditions to calculate the estimated delivery time for each package. Simultaneously, it optimizes the delivery route based on these results.

[0265] Step 4:

[0266] The server sends the user an email notification with the calculated estimated delivery time. This email includes detailed delivery information and a link for missed delivery notifications.

[0267] Step 5:

[0268] Users receive and confirm notification emails from the server, and if they are unable to be home at the scheduled time, they use the provided link to inform the server of their absence.

[0269] Step 6:

[0270] The server receives a missed delivery notification from the user, automatically adjusts the available date and time for redelivery, and notifies the delivery person of the information.

[0271] Step 7:

[0272] The terminal checks the optimized delivery route sent from the server, receives real-time updates, and provides appropriate instructions to the delivery person.

[0273] Step 8:

[0274] The user receives an email notification from the server regarding the rescheduled delivery date and time, and plans the redelivery based on this notification.

[0275] (Example 1)

[0276] 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."

[0277] In delivery operations, delays due to factors such as traffic conditions and recipient absence are frequent, posing a challenge to efficient logistics. Furthermore, the efficiency of redelivery when recipients are absent at the scheduled delivery time is also a problem. These factors lead to increased logistics costs and decreased customer satisfaction, therefore, these issues need to be addressed.

[0278] 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.

[0279] In this invention, the server includes means for acquiring location information from a portable device, means for acquiring traffic information from an external information source, and means for calculating the estimated delivery time using the location information and traffic information. This enables the creation of efficient delivery plans in real time. Furthermore, by adjusting the date and time of redelivery, it is possible to improve delivery efficiency and customer satisfaction.

[0280] An "information processing system" is a set of devices or programs for collecting, analyzing, and processing information, and for generating specific results or instructions based on that information.

[0281] A "portable device" is a terminal device that a user can possess or carry with them, and that has the function of transmitting and receiving location information.

[0282] "Location information" refers to data indicating the current location of a specific object, usually information represented by latitude and longitude.

[0283] "External information source" refers to a data provider existing outside the system, and refers to databases and services that provide traffic information and other real-time data.

[0284] "Traffic information" refers to data indicating traffic flow, congestion, accident situations, etc. in a specific area or route.

[0285] "Scheduled delivery time" refers to the time when the delivered item is predicted to be delivered to the recipient, and is a time calculated considering factors such as traffic conditions and distance.

[0286] "Calculation means" refers to a calculation for deriving a specific conclusion or result using the obtained data, or a device or program therefor.

[0287] "Notification means" refers to a method or technology for notifying a user or recipient of specific information, including forms such as email sending and app notifications.

[0288] "Absence notification receiving means" refers to a device or program that receives an absence notification from the recipient and determines the next action based on it.

[0289] "Redelivery date / time adjustment means" refers to a process or device that determines a new delivery date / time based on an absence notification and notifies the relevant parties of that information.

[0290] This invention is a method for improving the efficiency of delivery operations using an information processing system. The main components include a server, a delivery person's portable terminal, and a user.

[0291] First, the server receives location information transmitted from the delivery person's portable device. This location information is obtained using GPS technology and used to determine the delivery person's current location. The server also obtains traffic information from an external source. This source is a service that provides real-time traffic flow data, and the information can be aggregated via an API.

[0292] The server inputs the received location and traffic information into an AI algorithm to calculate the estimated delivery time for the package. This AI algorithm also plans the optimal delivery route, taking into account past data and current conditions. The AI ​​model used learns traffic patterns using machine learning techniques and can make predictions. These prediction results are stored in a database, and the server uses this to notify the user of the estimated delivery time.

[0293] The delivery driver's portable terminal receives optimal route information from the server and displays it on the terminal's screen. This information includes real-time traffic conditions and instructions for the best route. Because the portable terminal provides instructions to the delivery driver in real time, delivery efficiency can be improved.

[0294] The user receives a notification email from the server and confirms the scheduled delivery time. This notification includes a link that allows the user to easily report their absence if they are not available at the scheduled time. When the user uses this link to notify the server of their absence, the server arranges a new delivery date and time and informs both the delivery person and the user of the result.

[0295] As a concrete example, if a user is unable to receive a delivery, the server sends a notification email stating, "Delivery is scheduled for October 5th between 3 PM and 4 PM. If you will be absent, please use this link to contact us." This prompt allows the user to quickly notify the server of their absence, and the server can automatically arrange for redelivery. This improves delivery efficiency and customer satisfaction.

[0296] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0297] Step 1:

[0298] The server receives location information periodically transmitted from the delivery person's portable device. The location information used as input is coordinate data obtained using GPS technology. By storing this in a database, the server can identify the current location of the delivery person. Specifically, when the data is received, the server adds a timestamp and records the location information as part of the delivery history.

[0299] Step 2:

[0300] The server obtains real-time traffic information from external traffic information services. This data includes traffic flow, congestion, and road closures. The server analyzes this data as input and stores it in a database to identify changes in traffic conditions. Based on this information, it identifies traffic patterns and outputs the data in a formatted form for use in the next stage.

[0301] Step 3:

[0302] The server inputs the collected location and traffic information into an AI algorithm to calculate the estimated delivery time. Specifically, it passes this data to a generating AI model to predict the delivery time. The AI ​​model learns from past patterns and outputs the estimated delivery time along with the shortest route. The outputted estimated time and route information are used in the next notification step.

[0303] Step 4:

[0304] The server notifies the user of the calculated estimated delivery time. Specifically, it informs the user of the estimated delivery time in the form of an email or app notification. For example, it might send a message saying, "Your delivery is scheduled to arrive between 2 PM and 3 PM on October 5th." This output information is used to help the user prepare for receiving their delivery.

[0305] Step 5:

[0306] The user can send a notice of absence using the email with the delivery scheduled time notified or the link in the app. When the user clicks on the link, the server receives the input and records it in the database as information that requires redelivery. This input is used for the next redelivery adjustment.

[0307] Step 6:

[0308] Based on the notice of absence from the user, the server calculates and adjusts the redelivery date and time using an AI algorithm. The AI algorithm takes into account the current schedule and traffic information and outputs a new deliverable date and time. The adjusted date and time are notified to the delivery person and the user and reflected in the delivery plan.

[0309] (Application Example 1)

[0310] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0311] In order to achieve efficient time management and improved delivery accuracy in the delivery business, accurate notification of the delivery scheduled time and flexible response during absence are required. Also, it is necessary to improve the efficiency of delivery by immediate route optimization according to traffic conditions.

[0312] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0313] In this invention, the server includes means for acquiring spatial information from a terminal device carried by a delivery person, means for acquiring road condition information from an external information source, and means for calculating the delivery scheduled time of the delivery item using the spatial information and the road condition information. This enables improved delivery accuracy and efficient route management.

[0314] A "delivery person" is a person or organization responsible for transporting goods or items in order to perform the delivery business.

[0315] A "terminal device" refers to an electronic device that is capable of inputting and displaying information and can communicate with external systems.

[0316] "Spatial information" refers to data that indicates the location of a specific point, and is geographical information obtained through methods such as GPS.

[0317] "External information sources" refer to databases and information systems that are located outside of servers and terminal devices and provide the necessary information.

[0318] "Road condition information" refers to traffic-related information that affects driving, such as road congestion and road passability.

[0319] "Estimated delivery time" refers to the time when the delivered item is expected to arrive at the designated delivery location.

[0320] A "beneficiary" refers to a person who receives benefits or advantages from receiving a delivery service.

[0321] An "absence notice" is information used to inform the recipient that they will be absent at the time of delivery, allowing for rescheduling of the delivery.

[0322] "Route information" refers to data about the optimal route for delivery personnel to reach their destination.

[0323] This invention provides a system that enables delivery personnel to efficiently perform delivery tasks and allows recipients to respond in a timely manner. The following hardware and software are used in the operation of this system.

[0324] The server receives spatial information at regular intervals from the terminal devices carried by delivery personnel to track their location. This spatial information includes GPS data, enabling highly accurate location determination. The server also obtains road condition information from external sources such as the Google Maps API to understand traffic conditions in real time. Based on this, the server applies AI algorithms to calculate estimated delivery times and optimize delivery routes based on spatial and road condition information.

[0325] The terminal device displays optimal route information received from the server to the delivery person. This display utilizes a smartphone application to provide real-time directions and estimated arrival times. Based on this information, the delivery person can perform deliveries efficiently.

[0326] The recipient receives a notification of the estimated delivery time from the server via email or a mobile app. The notification includes a section for sending a missed delivery notification, allowing the recipient to easily inform the server of their situation when they are away. This facilitates smooth arrangement of redelivery.

[0327] For example, when a recipient orders lunch, the server takes traffic congestion into account and predicts that the food will be delivered in 45 minutes, notifying the recipient accordingly. If the recipient is not home at that time, they can use the provided link to reschedule the delivery.

[0328] An example of a prompt message to input into a generative AI model is as follows:

[0329] "Please use the Google Maps API to tell me the current best route and estimated arrival time. The delivery destination is Shinjuku."

[0330] This invention will improve delivery efficiency and enhance convenience for recipients.

[0331] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0332] Step 1:

[0333] The server receives spatial information transmitted from the delivery person's terminal device at regular intervals. This input data includes precise location information using GPS. The server receives this data and determines the delivery person's current location.

[0334] Step 2:

[0335] The server accesses the Google Maps API, an external source of information, to retrieve the latest road conditions. This information includes data on road congestion and passable routes. The retrieved information is used to analyze traffic patterns and find the optimal route.

[0336] Step 3:

[0337] The server uses an AI algorithm to analyze the spatial information obtained in Step 1 and the road condition information obtained in Step 2. This analysis calculates the estimated delivery time to each delivery destination and formulates the optimal route. The AI ​​learns traffic congestion patterns and selects the route that achieves the shortest delivery time.

[0338] Step 4:

[0339] The server sends the calculated estimated delivery time and route information as a notification to the recipient. This notification arrives via the recipient's email address or mobile app. The notification input includes the delivery address information, and the output presents the estimated delivery time to the recipient.

[0340] Step 5:

[0341] The terminal receives route information transmitted from the server and displays it to the delivery person in real time. In this process, the delivery person checks the route from their current location to the destination through an application installed on the terminal. This allows the delivery person to deliver quickly by following the optimal route.

[0342] Step 6:

[0343] When a user receives a notification, they click the link in the notification to report their absence to the server. This input includes their intention to be absent at the scheduled delivery time, and the server then arranges a new redelivery date and time as output.

[0344] Step 7:

[0345] Based on the user's absence notification, the server automatically readjusts the delivery person's schedule and creates a new delivery plan. This process streamlines redelivery and reduces costs. The server notifies the user of the new schedule and suggests the optimal time for both the user and the delivery person.

[0346] 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.

[0347] This invention combines an information processing system that notifies recipients of the delivery time in advance with a function that recognizes the user's emotions and optimizes the delivery experience based on those emotions. The program processing in this system is described below in natural language.

[0348] Server Functions

[0349] First, the server periodically receives location information transmitted from the delivery person's terminal and calculates the delivery route and estimated delivery time. Second, it activates an emotion engine via email and the interface to analyze the user's emotions. The emotion engine analyzes the user's responses and feedback to determine whether they are positive or negative about the delivery. Based on this emotion information, the server adjusts notification methods and message content to provide a more personalized delivery experience.

[0350] The server has a feature that simplifies the process for users to notify the delivery person of their absence, thereby reducing the stress associated with being away from home. This also makes scheduling redelivery smoother.

[0351] Device functions

[0352] The delivery driver's terminal updates and displays the optimal delivery route received from the server in real time. This information is linked to real-time traffic conditions, enabling efficient deliveries.

[0353] User functions

[0354] Users receive delivery notification emails from the server and can easily contact the server using a link if they are not home. Users can also express their emotions through feedback to the server, and the server will use this information to adjust the format of delivery notifications.

[0355] For example, when a user receives a delivery schedule via email in the morning, the sentiment engine analyzes the user's past response data and detects that their mood for the day is positive. Based on this, the server sends a notification in a friendly tone, providing the user with a stress-free experience. If the user is not home, the email concisely presents an option for missed delivery, and the server quickly arranges a redelivery date and time.

[0356] Thus, this system aims to improve the user experience and, in particular, to streamline delivery operations by enabling personalized responses based on emotions.

[0357] The following describes the processing flow.

[0358] Step 1:

[0359] The server periodically obtains location information from the delivery person's terminal device. This allows the server to determine the delivery person's real-time location.

[0360] Step 2:

[0361] The server retrieves traffic information from an external database and analyzes it in combination with location information. Based on this, an AI algorithm is used to calculate the estimated delivery time for the package.

[0362] Step 3:

[0363] The server uses an AI algorithm to calculate the optimal delivery route based on traffic information and transmits this information to the delivery person's terminal. This information enables the delivery person to make deliveries more efficiently.

[0364] Step 4:

[0365] The server creates a notification for the user based on the estimated delivery time and route information. The notification includes the estimated delivery time, as well as a link or button for contacting the user if they are unable to receive the delivery.

[0366] Step 5:

[0367] Using an emotion engine, the server analyzes past user data to estimate the user's emotional state. Based on the obtained emotional information, it adjusts the content and tone of notifications and sends them to the user.

[0368] Step 6:

[0369] The user checks the notification email from the server and, if there is a problem with the scheduled delivery time, uses the absence notification link to send an absence notification.

[0370] Step 7:

[0371] The server receives a missed delivery notification from the user and suggests the most suitable redelivery date and time. This allows the server to coordinate the details of the redelivery with the user.

[0372] Step 8:

[0373] The delivery driver's terminal follows the delivery route provided by the server and immediately receives and responds to any updated information. This is to utilize real-time information and maintain efficient deliveries.

[0374] Step 9:

[0375] The server collects data from the entire delivery operation and updates the database to use for future notifications and route optimization.

[0376] (Example 2)

[0377] 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".

[0378] While existing delivery information systems can notify recipients of delivery times, they struggle to provide personalized service that takes recipients' feelings into account. Furthermore, the process for redelivery in case of absence is cumbersome, highlighting the need for improved customer satisfaction.

[0379] 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.

[0380] In this invention, the server includes means for acquiring location information from a communication device carried by the delivery person, means for acquiring traffic conditions from an external information source, and means for driving an analysis device for analyzing the user's emotions. This enables the customization of delivery notifications based on the recipient's emotions and smooth redelivery procedures in case of absence.

[0381] A "communication device" is a device carried by a delivery person that has the function of transmitting location information to a server.

[0382] "External information source" refers to the platform to which the server connects to obtain information on traffic conditions.

[0383] "Location information" refers to latitude and longitude data indicating the delivery person's current location, and the delivery route is calculated based on this information.

[0384] "Traffic conditions" refers to dynamic information about roads, such as road congestion and traffic restrictions.

[0385] An "analysis device" is a core component of a system that analyzes user emotions and adjusts notification content based on that data.

[0386] "Estimated delivery time" refers to the estimated arrival time of a delivery item, calculated based on location information and traffic conditions.

[0387] "Notification content" refers to a message sent to the recipient that includes information such as the scheduled delivery time and redelivery options.

[0388] "Redelivery procedure" refers to the method of requesting redelivery for receiving a package when the recipient is absent, and is a process designed to simplify the procedure for the recipient.

[0389] This invention is an information system for improving the delivery experience for recipients of delivered goods. The specific implementation method is described below.

[0390] The server uses a GPS-enabled device to receive location information from the communication device carried by the delivery person. This device is equipped with a dedicated application and has the function to automatically transmit location data to the server. Based on the acquired location information, the server obtains traffic information from external sources. This external source utilizes traffic information systems provided via the internet. Specifically, for example, it uses the API of a map service provider to acquire real-time data.

[0391] The server operates an emotion analysis system that utilizes natural language processing technology to analyze user emotions. This system collects user feedback and past history, and identifies emotions using an AI model. For example, if a user sends positive feedback such as "I'm looking forward to the delivery," the server recognizes this as a positive emotion and adjusts the notification accordingly.

[0392] The terminal displays optimized delivery routes sent from the server, assisting delivery drivers with navigation. This allows delivery drivers to efficiently deliver packages to customers. The terminal is equipped with a map display function that reflects real-time location information.

[0393] Users can check the delivery time and status in real time through delivery notification emails received from the server. If they are not home, they can easily request redelivery by clicking a link included in the email. The absence notification process is provided through a user-friendly interface, significantly reducing the effort required.

[0394] Examples of specific prompt messages are as follows:

[0395] "Of all the delivery notifications you've received in the past, which one did you find the most pleasant? What was its tone and content?"

[0396] Thus, the system based on the present invention improves the user experience and supports efficient delivery operations.

[0397] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0398] Step 1:

[0399] The server receives location information from the delivery person's communication device. This location information is GPS data and includes latitude and longitude. The server receives this data and stores it in a database. Specifically, the server continuously updates this location information every minute.

[0400] Step 2:

[0401] The server obtains traffic information from external sources. The input consists of requests to a real-time traffic data API. The output data from this API includes traffic congestion and road closure information. The server analyzes this traffic information and uses it to optimize delivery routes. Specifically, the server analyzes the API response and applies an algorithm to calculate the most efficient route.

[0402] Step 3:

[0403] The server calculates the estimated delivery time based on location information and traffic conditions. Input includes location data and traffic data. The server uses this data to calculate travel time to each delivery point and generates the shortest possible delivery schedule. The output is the estimated delivery time, which is then notified to both the delivery person and the recipient. Specifically, the server uses an appropriate algorithm to estimate travel time and incorporates the estimated time into the notification email.

[0404] Step 4:

[0405] The server collects user feedback and analyzes its sentiment. Input includes user response data. A generative AI model is used to perform sentiment analysis on this text data. The output is data indicating the emotional state, which is used to adjust the tone of notifications. Specifically, the AI ​​model scans the text and categorizes the feedback as either positive or negative.

[0406] Step 5:

[0407] The terminal displays optimized route information sent from the server. Its input is route data received from the server. Based on this data, the terminal uses a map application to provide appropriate navigation instructions. As output, the delivery person receives real-time route instructions and uses them to navigate. Specifically, the terminal utilizes voice guidance and map displays to efficiently guide the delivery person to their destination.

[0408] Step 6:

[0409] The user receives a delivery notification and, if absent, requests redelivery. The input comes from a notification email from the server. This email contains a link to request redelivery; the user clicks this link to request redelivery. The output is the redelivery option selected by the user, which is reflected on the server. Specifically, the user specifies the next delivery time by filling out and submitting a simple form.

[0410] (Application Example 2)

[0411] 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."

[0412] In today's delivery services, recipients sometimes experience dissatisfaction with their delivery experience, particularly because delivery notifications are often uniform and do not reflect individual needs or feelings. Furthermore, the process of redelivery when recipients are absent can be cumbersome and stressful for them. There is a need to solve these problems and provide a better customer experience.

[0413] 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.

[0414] In this invention, the server includes means for acquiring geographical location information from a terminal device carried by the delivery person, means for acquiring traffic condition information from an external information source, and means for analyzing the recipient's emotional state and personalizing the notification message. This makes it possible to accurately calculate the estimated delivery time and provide a personalized delivery notification that corresponds to the recipient's emotional state.

[0415] An "information processing system" is an integrated system of hardware and software for collecting, processing, and analyzing data and providing results according to specific tasks or purposes.

[0416] "Geographic location information" refers to information used to identify a specific point on Earth, and is usually expressed using latitude and longitude.

[0417] "Traffic condition information" refers to information regarding current congestion levels and traffic speeds on roads and in traffic systems.

[0418] "Estimated delivery time" refers to the specific time when the delivered item is expected to be delivered to the recipient.

[0419] The "recipient" is the individual or organization that actually receives the delivered item.

[0420] An "absence notification" is a procedure or message used to notify the recipient that they will not be present at the designated time.

[0421] "Emotional state" refers to an individual's mental state and can be classified into positive or negative emotions.

[0422] "Personalization" is the process of adjusting or customizing information or services to suit specific individuals or circumstances.

[0423] This invention is an information processing system aimed at analyzing the emotional state of recipients and personalizing the delivery experience based on that analysis. The server first obtains the geographical location information of the delivery person and collects traffic condition information from external sources. Using this information, it accurately calculates the estimated delivery time. It also evaluates the emotional state of recipients by analyzing feedback from recipients and past data.

[0424] Based on this information, the server generates personalized delivery notification messages. For example, if the recipient is in a positive emotional state, the notification message will be sent in a friendly tone. Also, if the recipient is absent, the server provides a redirection option to make it easy for them to report the absence.

[0425] The terminal device displays the optimal delivery route, reflecting the delivery person's real-time geographical location and traffic conditions. This allows delivery people to make deliveries efficiently.

[0426] Recipients receive notifications from the server via email or other electronic means, allowing for flexible responses when they are unavailable. Generative AI models are used for sentiment analysis throughout this process. For example, if a recipient has provided positive feedback on past orders, the next notification message will be a friendly one, such as "Have a great day!" Another example of a prompt for the generative AI model during sentiment analysis is, "Consider the user's past feedback to determine their positive or negative emotional state, and create a food delivery notification message based on that."

[0427] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0428] Step 1:

[0429] The server receives geographical location information from a terminal device carried by the delivery person. The input is real-time location data transmitted from the terminal, and the output is geographical location coordinates stored on the server. Based on this data, the server performs an operation to determine the delivery person's current location.

[0430] Step 2:

[0431] The server obtains traffic condition information from external sources. The input is current traffic data received through the API of a traffic information service, and the output is analyzed data regarding traffic congestion and road conditions. This allows the server to analyze traffic conditions that may affect deliveries.

[0432] Step 3:

[0433] The server retrieves past feedback data to analyze the recipient's emotional state. The input is the recipient's feedback history, and the output is the result of the emotional state analysis using a generative AI model. This allows the server to identify the recipient's past tendencies towards positive or negative emotions.

[0434] Step 4:

[0435] The server uses geographical location and traffic information to calculate the estimated delivery time for the package. The input is the current location and traffic data obtained in the previous step, and the output is the optimal delivery time prediction. This allows the server to plan an efficient delivery route.

[0436] Step 5:

[0437] The server generates a notification message to send to the recipient, reflecting the results of sentiment analysis. The input is the analyzed sentiment data, and the output is a personalized delivery notification message. The server uses this to generate a personalized message for the recipient.

[0438] Step 6:

[0439] Users receive personalized delivery notification messages from the server and take actions such as reporting absences as needed. The input is the message sent from the server, and the output is the user's response and absence report data. This allows users to easily communicate their reactions to the server.

[0440] Step 7:

[0441] The terminal displays real-time updated delivery route information to the delivery person. The input is optimized route information sent from the server, and the output is navigation instructions displayed on the terminal. This enables delivery people to perform deliveries efficiently.

[0442] 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.

[0443] 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.

[0444] 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.

[0445] [Third Embodiment]

[0446] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0447] 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.

[0448] 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).

[0449] 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.

[0450] 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.

[0451] 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).

[0452] 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.

[0453] 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.

[0454] 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.

[0455] 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.

[0456] 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.

[0457] 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".

[0458] This invention is an information processing system for improving the efficiency of delivery operations. The program processing of this system is described below in natural language.

[0459] Server Functions

[0460] The server first receives location information transmitted from the delivery person's terminal. This allows it to determine the delivery person's current location. Furthermore, the server obtains information about traffic conditions from an external traffic information database and analyzes it.

[0461] The server uses an AI algorithm to calculate the estimated delivery time for each delivery based on acquired location and traffic information. This also allows for the simultaneous planning of the most efficient delivery route. The calculated estimated delivery time is notified to the user in advance via email or other means.

[0462] Furthermore, if a user reports being unable to receive their delivery, the server collects that information via a link in the email and initiates the redelivery process. It also arranges a redelivery date and time and notifies the delivery person accordingly.

[0463] Device functions

[0464] The delivery person's device sends its current location information to the server at regular intervals. This process allows the server to continuously track the delivery person's location and maintain the optimal route and delivery time.

[0465] The terminal displays the optimal delivery route received from the server and issues real-time instructions to delivery personnel. This information includes route changes due to changes in traffic conditions.

[0466] User functions

[0467] The user receives and confirms an email notification from the server indicating the scheduled delivery time. This notification increases the likelihood of being home at the time of delivery. If the user is unable to be home at the scheduled time, they can notify the server of their absence via the link in the email.

[0468] As a concrete example, the server predicts a delivery to a user between 3 PM and 4 PM on October 5th and sends a delivery notification email. Because the user is unavailable at this time, they use the email link to inform the server of their absence. Based on this information, the server sets a new delivery date and time and notifies both the delivery person and the user. This improves the efficiency of redelivery and contributes to reducing logistics costs.

[0469] The following describes the processing flow.

[0470] Step 1:

[0471] The server operates a system that periodically receives location information from the delivery person's terminal, thereby allowing it to track the delivery person's real-time location.

[0472] Step 2:

[0473] The server retrieves traffic data from an external database and integrates it with received location information before importing it into the system. This process allows for a detailed analysis of the current status of delivery routes.

[0474] Step 3:

[0475] The server uses an AI algorithm based on location information and traffic conditions to calculate the estimated delivery time for each package. Simultaneously, it optimizes the delivery route based on these results.

[0476] Step 4:

[0477] The server sends the user an email notification with the calculated estimated delivery time. This email includes detailed delivery information and a link for missed delivery notifications.

[0478] Step 5:

[0479] Users receive and confirm notification emails from the server, and if they are unable to be home at the scheduled time, they use the provided link to inform the server of their absence.

[0480] Step 6:

[0481] The server receives a missed delivery notification from the user, automatically adjusts the available date and time for redelivery, and notifies the delivery person of the information.

[0482] Step 7:

[0483] The terminal checks the optimized delivery route sent from the server, receives real-time updates, and provides appropriate instructions to the delivery person.

[0484] Step 8:

[0485] The user receives an email notification from the server regarding the rescheduled delivery date and time, and plans the redelivery based on this notification.

[0486] (Example 1)

[0487] 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."

[0488] In delivery operations, delays due to factors such as traffic conditions and recipient absence are frequent, posing a challenge to efficient logistics. Furthermore, the efficiency of redelivery when recipients are absent at the scheduled delivery time is also a problem. These factors lead to increased logistics costs and decreased customer satisfaction, therefore, these issues need to be addressed.

[0489] 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.

[0490] In this invention, the server includes means for acquiring location information from a portable device, means for acquiring traffic information from an external information source, and means for calculating the estimated delivery time using the location information and traffic information. This enables the creation of efficient delivery plans in real time. Furthermore, by adjusting the date and time of redelivery, it is possible to improve delivery efficiency and customer satisfaction.

[0491] An "information processing system" is a set of devices or programs for collecting, analyzing, and processing information, and for generating specific results or instructions based on that information.

[0492] A "portable device" is a terminal device that a user can possess or carry with them, and that has the function of transmitting and receiving location information.

[0493] "Location information" refers to data that indicates the current location of a specific object, and is usually expressed as latitude and longitude.

[0494] "External information sources" refer to data sources that exist outside the system, such as databases and services that provide traffic information and other real-time data.

[0495] "Traffic information" refers to data that shows traffic flow, congestion, accident situations, etc., in a specific area or route.

[0496] "Estimated delivery time" refers to the time when the delivered item is expected to be delivered to the recipient, and is calculated taking into account factors such as traffic conditions and distance.

[0497] "Means of calculation" refers to calculations, or devices and programs, used to derive specific conclusions or results using the obtained data.

[0498] "Means of notification" refers to methods or technologies for informing a user or recipient of specific information, including forms such as email and app notifications.

[0499] "Means for receiving absence notifications" refers to a device or program that receives absence notifications from recipients and uses them to determine the next course of action.

[0500] "Means of adjusting the redelivery date and time" refers to a process or device that determines a new delivery date and time based on a missed delivery notice and informs the relevant parties of that information.

[0501] This invention is a method for streamlining delivery operations using an information processing system. The main components include a server, a portable terminal for delivery personnel, and a user.

[0502] First, the server receives location information transmitted from the delivery person's portable device. This location information is obtained using GPS technology and used to determine the delivery person's current location. The server also obtains traffic information from an external source. This source is a service that provides real-time traffic flow data, and the information can be aggregated via an API.

[0503] The server inputs the received location and traffic information into an AI algorithm to calculate the estimated delivery time for the package. This AI algorithm also plans the optimal delivery route, taking into account past data and current conditions. The AI ​​model used learns traffic patterns using machine learning techniques and can make predictions. These prediction results are stored in a database, and the server uses this to notify the user of the estimated delivery time.

[0504] The delivery driver's portable terminal receives optimal route information from the server and displays it on the terminal's screen. This information includes real-time traffic conditions and instructions for the best route. Because the portable terminal provides instructions to the delivery driver in real time, delivery efficiency can be improved.

[0505] The user receives a notification email from the server and confirms the scheduled delivery time. This notification includes a link that allows the user to easily report their absence if they are not available at the scheduled time. When the user uses this link to notify the server of their absence, the server arranges a new delivery date and time and informs both the delivery person and the user of the result.

[0506] As a concrete example, if a user is unable to receive a delivery, the server sends a notification email stating, "Delivery is scheduled for October 5th between 3 PM and 4 PM. If you will be absent, please use this link to contact us." This prompt allows the user to quickly notify the server of their absence, and the server can automatically arrange for redelivery. This improves delivery efficiency and customer satisfaction.

[0507] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0508] Step 1:

[0509] The server receives location information periodically transmitted from the delivery person's portable device. The location information used as input is coordinate data obtained using GPS technology. By storing this in a database, the server can identify the current location of the delivery person. Specifically, when the data is received, the server adds a timestamp and records the location information as part of the delivery history.

[0510] Step 2:

[0511] The server obtains real-time traffic information from external traffic information services. This data includes traffic flow, congestion, and road closures. The server analyzes this data as input and stores it in a database to identify changes in traffic conditions. Based on this information, it identifies traffic patterns and outputs the data in a formatted form for use in the next stage.

[0512] Step 3:

[0513] The server inputs the collected location and traffic information into an AI algorithm to calculate the estimated delivery time. Specifically, it passes this data to a generating AI model to predict the delivery time. The AI ​​model learns from past patterns and outputs the estimated delivery time along with the shortest route. The outputted estimated time and route information are used in the next notification step.

[0514] Step 4:

[0515] The server notifies the user of the calculated estimated delivery time. Specifically, it informs the user of the estimated delivery time in the form of an email or app notification. For example, it might send a message saying, "Your delivery is scheduled to arrive between 2 PM and 3 PM on October 5th." This output information is used to help the user prepare for receiving their delivery.

[0516] Step 5:

[0517] Users can notify the delivery service of their missed delivery via an email or in-app link that notifies them of the estimated delivery time. When a user clicks the link, the server receives the input and records it in the database as information indicating that redelivery is required. This input is used to schedule the next redelivery.

[0518] Step 6:

[0519] Based on the user's missed delivery notification, the server uses an AI algorithm to calculate and adjust the redelivery date and time. The AI ​​algorithm considers the current schedule and traffic information to output a new, available delivery date and time. The adjusted date and time are notified to the delivery person and the user and reflected in the delivery plan.

[0520] (Application Example 1)

[0521] 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."

[0522] To improve the efficiency of time management and delivery accuracy in delivery operations, accurate notification of scheduled delivery times and flexible handling of situations where recipients are absent are required. Furthermore, it is necessary to optimize delivery routes immediately in response to traffic conditions to increase efficiency.

[0523] 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.

[0524] In this invention, the server includes means for acquiring spatial information from terminal devices carried by delivery personnel, means for acquiring road condition information from external information sources, and means for calculating the estimated delivery time of the delivered items using the spatial information and road condition information. This enables improved delivery accuracy and efficient route management.

[0525] A "delivery person" is a person or organization responsible for transporting goods or items in order to carry out delivery operations.

[0526] A "terminal device" refers to an electronic device that is capable of inputting and displaying information and can communicate with external systems.

[0527] "Spatial information" refers to data that indicates the location of a specific point, and is geographical information obtained through methods such as GPS.

[0528] "External information sources" refer to databases and information systems that are located outside of servers and terminal devices and provide the necessary information.

[0529] "Road condition information" refers to traffic-related information that affects driving, such as road congestion and road passability.

[0530] "Estimated delivery time" refers to the time when the delivered item is expected to arrive at the designated delivery location.

[0531] A "beneficiary" refers to a person who receives benefits or advantages from receiving a delivery service.

[0532] An "absence notice" is information used to inform the recipient that they will be absent at the time of delivery, allowing for rescheduling of the delivery.

[0533] "Route information" refers to data about the optimal route for delivery personnel to reach their destination.

[0534] This invention provides a system that enables delivery personnel to efficiently perform delivery tasks and allows recipients to respond in a timely manner. The following hardware and software are used in the operation of this system.

[0535] The server receives spatial information at regular intervals from the terminal devices carried by delivery personnel to track their location. This spatial information includes GPS data, enabling highly accurate location determination. The server also obtains road condition information from external sources such as the Google Maps API to understand traffic conditions in real time. Based on this, the server applies AI algorithms to calculate estimated delivery times and optimize delivery routes based on spatial and road condition information.

[0536] The terminal device displays optimal route information received from the server to the delivery person. This display utilizes a smartphone application to provide real-time directions and estimated arrival times. Based on this information, the delivery person can perform deliveries efficiently.

[0537] The recipient receives a notification of the estimated delivery time from the server via email or a mobile app. The notification includes a section for sending a missed delivery notification, allowing the recipient to easily inform the server of their situation when they are away. This facilitates smooth arrangement of redelivery.

[0538] For example, when a recipient orders lunch, the server takes traffic congestion into account and predicts that the food will be delivered in 45 minutes, notifying the recipient accordingly. If the recipient is not home at that time, they can use the provided link to reschedule the delivery.

[0539] An example of a prompt message to input into a generative AI model is as follows:

[0540] "Please use the Google Maps API to tell me the current best route and estimated arrival time. The delivery destination is Shinjuku."

[0541] This invention will improve delivery efficiency and enhance convenience for recipients.

[0542] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0543] Step 1:

[0544] The server receives spatial information transmitted from the delivery person's terminal device at regular intervals. This input data includes precise location information using GPS. The server receives this data and determines the delivery person's current location.

[0545] Step 2:

[0546] The server accesses the Google Maps API, an external source of information, to retrieve the latest road conditions. This information includes data on road congestion and passable routes. The retrieved information is used to analyze traffic patterns and find the optimal route.

[0547] Step 3:

[0548] The server uses an AI algorithm to analyze the spatial information obtained in Step 1 and the road condition information obtained in Step 2. This analysis calculates the estimated delivery time to each delivery destination and formulates the optimal route. The AI ​​learns traffic congestion patterns and selects the route that achieves the shortest delivery time.

[0549] Step 4:

[0550] The server sends the calculated estimated delivery time and route information as a notification to the recipient. This notification arrives via the recipient's email address or mobile app. The notification input includes the delivery address information, and the output presents the estimated delivery time to the recipient.

[0551] Step 5:

[0552] The terminal receives route information transmitted from the server and displays it to the delivery person in real time. In this process, the delivery person checks the route from their current location to the destination through an application installed on the terminal. This allows the delivery person to deliver quickly by following the optimal route.

[0553] Step 6:

[0554] When a user receives a notification, they click the link in the notification to report their absence to the server. This input includes their intention to be absent at the scheduled delivery time, and the server then arranges a new redelivery date and time as output.

[0555] Step 7:

[0556] Based on the user's absence notification, the server automatically readjusts the delivery person's schedule and creates a new delivery plan. This process streamlines redelivery and reduces costs. The server notifies the user of the new schedule and suggests the optimal time for both the user and the delivery person.

[0557] 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.

[0558] This invention combines an information processing system that notifies recipients of the delivery time in advance with a function that recognizes the user's emotions and optimizes the delivery experience based on those emotions. The program processing in this system is described below in natural language.

[0559] Server Functions

[0560] First, the server periodically receives location information transmitted from the delivery person's terminal and calculates the delivery route and estimated delivery time. Second, it activates an emotion engine via email and the interface to analyze the user's emotions. The emotion engine analyzes the user's responses and feedback to determine whether they are positive or negative about the delivery. Based on this emotion information, the server adjusts notification methods and message content to provide a more personalized delivery experience.

[0561] The server has a feature that simplifies the process for users to notify the delivery person of their absence, thereby reducing the stress associated with being away from home. This also makes scheduling redelivery smoother.

[0562] Device functions

[0563] The delivery driver's terminal updates and displays the optimal delivery route received from the server in real time. This information is linked to real-time traffic conditions, enabling efficient deliveries.

[0564] User functions

[0565] Users receive delivery notification emails from the server and can easily contact the server using a link if they are not home. Users can also express their emotions through feedback to the server, and the server will use this information to adjust the format of delivery notifications.

[0566] For example, when a user receives a delivery schedule via email in the morning, the sentiment engine analyzes the user's past response data and detects that their mood for the day is positive. Based on this, the server sends a notification in a friendly tone, providing the user with a stress-free experience. If the user is not home, the email concisely presents an option for missed delivery, and the server quickly arranges a redelivery date and time.

[0567] Thus, this system aims to improve the user experience and, in particular, to streamline delivery operations by enabling personalized responses based on emotions.

[0568] The following describes the processing flow.

[0569] Step 1:

[0570] The server periodically obtains location information from the delivery person's terminal device. This allows the server to determine the delivery person's real-time location.

[0571] Step 2:

[0572] The server retrieves traffic information from an external database and analyzes it in combination with location information. Based on this, an AI algorithm is used to calculate the estimated delivery time for the package.

[0573] Step 3:

[0574] The server uses an AI algorithm to calculate the optimal delivery route based on traffic information and transmits this information to the delivery person's terminal. This information enables the delivery person to make deliveries more efficiently.

[0575] Step 4:

[0576] The server creates a notification for the user based on the estimated delivery time and route information. The notification includes the estimated delivery time, as well as a link or button for contacting the user if they are unable to receive the delivery.

[0577] Step 5:

[0578] Using an emotion engine, the server analyzes past user data to estimate the user's emotional state. Based on the obtained emotional information, it adjusts the content and tone of notifications and sends them to the user.

[0579] Step 6:

[0580] The user checks the notification email from the server and, if there is a problem with the scheduled delivery time, uses the absence notification link to send an absence notification.

[0581] Step 7:

[0582] The server receives a missed delivery notification from the user and suggests the most suitable redelivery date and time. This allows the server to coordinate the details of the redelivery with the user.

[0583] Step 8:

[0584] The delivery driver's terminal follows the delivery route provided by the server and immediately receives and responds to any updated information. This is to utilize real-time information and maintain efficient deliveries.

[0585] Step 9:

[0586] The server collects data from the entire delivery operation and updates the database to use for future notifications and route optimization.

[0587] (Example 2)

[0588] 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."

[0589] While existing delivery information systems can notify recipients of delivery times, they struggle to provide personalized service that takes recipients' feelings into account. Furthermore, the process for redelivery in case of absence is cumbersome, highlighting the need for improved customer satisfaction.

[0590] 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.

[0591] In this invention, the server includes means for acquiring location information from a communication device carried by the delivery person, means for acquiring traffic conditions from an external information source, and means for driving an analysis device for analyzing the user's emotions. This enables the customization of delivery notifications based on the recipient's emotions and smooth redelivery procedures in case of absence.

[0592] A "communication device" is a device carried by a delivery person that has the function of transmitting location information to a server.

[0593] "External information source" refers to the platform to which the server connects to obtain information on traffic conditions.

[0594] "Location information" refers to latitude and longitude data indicating the delivery person's current location, and the delivery route is calculated based on this information.

[0595] "Traffic conditions" refers to dynamic information about roads, such as road congestion and traffic restrictions.

[0596] An "analysis device" is a core component of a system that analyzes user emotions and adjusts notification content based on that data.

[0597] "Estimated delivery time" refers to the estimated arrival time of a delivery item, calculated based on location information and traffic conditions.

[0598] "Notification content" refers to a message sent to the recipient that includes information such as the scheduled delivery time and redelivery options.

[0599] "Redelivery procedure" refers to the method of requesting redelivery for receiving a package when the recipient is absent, and is a process designed to simplify the procedure for the recipient.

[0600] This invention is an information system for improving the delivery experience for recipients of delivered goods. The specific implementation method is described below.

[0601] The server uses a GPS-enabled device to receive location information from the communication device carried by the delivery person. This device is equipped with a dedicated application and has the function to automatically transmit location data to the server. Based on the acquired location information, the server obtains traffic information from external sources. This external source utilizes traffic information systems provided via the internet. Specifically, for example, it uses the API of a map service provider to acquire real-time data.

[0602] The server operates an emotion analysis system that utilizes natural language processing technology to analyze user emotions. This system collects user feedback and past history, and identifies emotions using an AI model. For example, if a user sends positive feedback such as "I'm looking forward to the delivery," the server recognizes this as a positive emotion and adjusts the notification accordingly.

[0603] The terminal displays optimized delivery routes sent from the server, assisting delivery drivers with navigation. This allows delivery drivers to efficiently deliver packages to customers. The terminal is equipped with a map display function that reflects real-time location information.

[0604] Users can check the delivery time and status in real time through delivery notification emails received from the server. If they are not home, they can easily request redelivery by clicking a link included in the email. The absence notification process is provided through a user-friendly interface, significantly reducing the effort required.

[0605] Examples of specific prompt messages are as follows:

[0606] "Of all the delivery notifications you've received in the past, which one did you find the most pleasant? What was its tone and content?"

[0607] Thus, the system based on the present invention improves the user experience and supports efficient delivery operations.

[0608] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0609] Step 1:

[0610] The server receives location information from the delivery person's communication device. This location information is GPS data and includes latitude and longitude. The server receives this data and stores it in a database. Specifically, the server continuously updates this location information every minute.

[0611] Step 2:

[0612] The server obtains traffic information from external sources. The input consists of requests to a real-time traffic data API. The output data from this API includes traffic congestion and road closure information. The server analyzes this traffic information and uses it to optimize delivery routes. Specifically, the server analyzes the API response and applies an algorithm to calculate the most efficient route.

[0613] Step 3:

[0614] The server calculates the estimated delivery time based on location information and traffic conditions. Input includes location data and traffic data. The server uses this data to calculate travel time to each delivery point and generates the shortest possible delivery schedule. The output is the estimated delivery time, which is then notified to both the delivery person and the recipient. Specifically, the server uses an appropriate algorithm to estimate travel time and incorporates the estimated time into the notification email.

[0615] Step 4:

[0616] The server collects user feedback and analyzes its sentiment. Input includes user response data. A generative AI model is used to perform sentiment analysis on this text data. The output is data indicating the emotional state, which is used to adjust the tone of notifications. Specifically, the AI ​​model scans the text and categorizes the feedback as either positive or negative.

[0617] Step 5:

[0618] The terminal displays optimized route information sent from the server. Its input is route data received from the server. Based on this data, the terminal uses a map application to provide appropriate navigation instructions. As output, the delivery person receives real-time route instructions and uses them to navigate. Specifically, the terminal utilizes voice guidance and map displays to efficiently guide the delivery person to their destination.

[0619] Step 6:

[0620] The user receives a delivery notification and, if absent, requests redelivery. The input comes from a notification email from the server. This email contains a link to request redelivery; the user clicks this link to request redelivery. The output is the redelivery option selected by the user, which is reflected on the server. Specifically, the user specifies the next delivery time by filling out and submitting a simple form.

[0621] (Application Example 2)

[0622] 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."

[0623] In today's delivery services, recipients sometimes experience dissatisfaction with their delivery experience, particularly because delivery notifications are often uniform and do not reflect individual needs or feelings. Furthermore, the process of redelivery when recipients are absent can be cumbersome and stressful for them. There is a need to solve these problems and provide a better customer experience.

[0624] 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.

[0625] In this invention, the server includes means for acquiring geographical location information from a terminal device carried by the delivery person, means for acquiring traffic condition information from an external information source, and means for analyzing the recipient's emotional state and personalizing the notification message. This makes it possible to accurately calculate the estimated delivery time and provide a personalized delivery notification that corresponds to the recipient's emotional state.

[0626] An "information processing system" is an integrated system of hardware and software for collecting, processing, and analyzing data and providing results according to specific tasks or purposes.

[0627] "Geographic location information" refers to information used to identify a specific point on Earth, and is usually expressed using latitude and longitude.

[0628] "Traffic condition information" refers to information regarding current congestion levels and traffic speeds on roads and in traffic systems.

[0629] "Estimated delivery time" refers to the specific time when the delivered item is expected to be delivered to the recipient.

[0630] The "recipient" is the individual or organization that actually receives the delivered item.

[0631] An "absence notification" is a procedure or message used to notify the recipient that they will not be present at the designated time.

[0632] "Emotional state" refers to an individual's mental state and can be classified into positive or negative emotions.

[0633] "Personalization" is the process of adjusting or customizing information or services to suit specific individuals or circumstances.

[0634] This invention is an information processing system aimed at analyzing the emotional state of recipients and personalizing the delivery experience based on that analysis. The server first obtains the geographical location information of the delivery person and collects traffic condition information from external sources. Using this information, it accurately calculates the estimated delivery time. It also evaluates the emotional state of recipients by analyzing feedback from recipients and past data.

[0635] Based on this information, the server generates personalized delivery notification messages. For example, if the recipient is in a positive emotional state, the notification message will be sent in a friendly tone. Also, if the recipient is absent, the server provides a redirection option to make it easy for them to report the absence.

[0636] The terminal device displays the optimal delivery route, reflecting the delivery person's real-time geographical location and traffic conditions. This allows delivery people to make deliveries efficiently.

[0637] Recipients receive notifications from the server via email or other electronic means, allowing for flexible responses when they are unavailable. Generative AI models are used for sentiment analysis throughout this process. For example, if a recipient has provided positive feedback on past orders, the next notification message will be a friendly one, such as "Have a great day!" Another example of a prompt for the generative AI model during sentiment analysis is, "Consider the user's past feedback to determine their positive or negative emotional state, and create a food delivery notification message based on that."

[0638] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0639] Step 1:

[0640] The server receives geographical location information from a terminal device carried by the delivery person. The input is real-time location data transmitted from the terminal, and the output is geographical location coordinates stored on the server. Based on this data, the server performs an operation to determine the delivery person's current location.

[0641] Step 2:

[0642] The server obtains traffic condition information from external sources. The input is current traffic data received through the API of a traffic information service, and the output is analyzed data regarding traffic congestion and road conditions. This allows the server to analyze traffic conditions that may affect deliveries.

[0643] Step 3:

[0644] The server retrieves past feedback data to analyze the recipient's emotional state. The input is the recipient's feedback history, and the output is the result of the emotional state analysis using a generative AI model. This allows the server to identify the recipient's past tendencies towards positive or negative emotions.

[0645] Step 4:

[0646] The server uses geographical location and traffic information to calculate the estimated delivery time for the package. The input is the current location and traffic data obtained in the previous step, and the output is the optimal delivery time prediction. This allows the server to plan an efficient delivery route.

[0647] Step 5:

[0648] The server generates a notification message to send to the recipient, reflecting the results of sentiment analysis. The input is the analyzed sentiment data, and the output is a personalized delivery notification message. The server uses this to generate a personalized message for the recipient.

[0649] Step 6:

[0650] Users receive personalized delivery notification messages from the server and take actions such as reporting absences as needed. The input is the message sent from the server, and the output is the user's response and absence report data. This allows users to easily communicate their reactions to the server.

[0651] Step 7:

[0652] The terminal displays real-time updated delivery route information to the delivery person. The input is optimized route information sent from the server, and the output is navigation instructions displayed on the terminal. This enables delivery people to perform deliveries efficiently.

[0653] 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.

[0654] 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.

[0655] 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.

[0656] [Fourth Embodiment]

[0657] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0658] 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.

[0659] 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).

[0660] 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.

[0661] 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.

[0662] 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).

[0663] 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.

[0664] 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.

[0665] 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.

[0666] 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.

[0667] 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.

[0668] 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.

[0669] 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".

[0670] This invention is an information processing system for improving the efficiency of delivery operations. The program processing of this system is described below in natural language.

[0671] Server Functions

[0672] The server first receives location information transmitted from the delivery person's terminal. This allows it to determine the delivery person's current location. Furthermore, the server obtains information about traffic conditions from an external traffic information database and analyzes it.

[0673] The server uses an AI algorithm to calculate the estimated delivery time for each delivery based on acquired location and traffic information. This also allows for the simultaneous planning of the most efficient delivery route. The calculated estimated delivery time is notified to the user in advance via email or other means.

[0674] Furthermore, if a user reports being unable to receive their delivery, the server collects that information via a link in the email and initiates the redelivery process. It also arranges a redelivery date and time and notifies the delivery person accordingly.

[0675] Device functions

[0676] The delivery person's device sends its current location information to the server at regular intervals. This process allows the server to continuously track the delivery person's location and maintain the optimal route and delivery time.

[0677] The terminal displays the optimal delivery route received from the server and issues real-time instructions to delivery personnel. This information includes route changes due to changes in traffic conditions.

[0678] User functions

[0679] The user receives and confirms an email notification from the server indicating the scheduled delivery time. This notification increases the likelihood of being home at the time of delivery. If the user is unable to be home at the scheduled time, they can notify the server of their absence via the link in the email.

[0680] As a concrete example, the server predicts a delivery to a user between 3 PM and 4 PM on October 5th and sends a delivery notification email. Because the user is unavailable at this time, they use the email link to inform the server of their absence. Based on this information, the server sets a new delivery date and time and notifies both the delivery person and the user. This improves the efficiency of redelivery and contributes to reducing logistics costs.

[0681] The following describes the processing flow.

[0682] Step 1:

[0683] The server operates a system that periodically receives location information from the delivery person's terminal, thereby allowing it to track the delivery person's real-time location.

[0684] Step 2:

[0685] The server retrieves traffic data from an external database and integrates it with received location information before importing it into the system. This process allows for a detailed analysis of the current status of delivery routes.

[0686] Step 3:

[0687] The server uses an AI algorithm based on location information and traffic conditions to calculate the estimated delivery time for each package. Simultaneously, it optimizes the delivery route based on these results.

[0688] Step 4:

[0689] The server sends the user an email notification with the calculated estimated delivery time. This email includes detailed delivery information and a link for missed delivery notifications.

[0690] Step 5:

[0691] Users receive and confirm notification emails from the server, and if they are unable to be home at the scheduled time, they use the provided link to inform the server of their absence.

[0692] Step 6:

[0693] The server receives a missed delivery notification from the user, automatically adjusts the available date and time for redelivery, and notifies the delivery person of the information.

[0694] Step 7:

[0695] The terminal checks the optimized delivery route sent from the server, receives real-time updates, and provides appropriate instructions to the delivery person.

[0696] Step 8:

[0697] The user receives an email notification from the server regarding the rescheduled delivery date and time, and plans the redelivery based on this notification.

[0698] (Example 1)

[0699] 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".

[0700] In delivery operations, delays due to factors such as traffic conditions and recipient absence are frequent, posing a challenge to efficient logistics. Furthermore, the efficiency of redelivery when recipients are absent at the scheduled delivery time is also a problem. These factors lead to increased logistics costs and decreased customer satisfaction, therefore, these issues need to be addressed.

[0701] 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.

[0702] In this invention, the server includes means for acquiring location information from a portable device, means for acquiring traffic information from an external information source, and means for calculating the estimated delivery time using the location information and traffic information. This enables the creation of efficient delivery plans in real time. Furthermore, by adjusting the date and time of redelivery, it is possible to improve delivery efficiency and customer satisfaction.

[0703] An "information processing system" is a set of devices or programs for collecting, analyzing, and processing information, and for generating specific results or instructions based on that information.

[0704] A "portable device" is a terminal device that a user can possess or carry with them, and that has the function of transmitting and receiving location information.

[0705] "Location information" refers to data that indicates the current location of a specific object, and is usually expressed as latitude and longitude.

[0706] "External information sources" refer to data sources that exist outside the system, such as databases and services that provide traffic information and other real-time data.

[0707] "Traffic information" refers to data that shows traffic flow, congestion, accident situations, etc., in a specific area or route.

[0708] "Estimated delivery time" refers to the time when the delivered item is expected to be delivered to the recipient, and is calculated taking into account factors such as traffic conditions and distance.

[0709] "Means of calculation" refers to calculations, or devices and programs, used to derive specific conclusions or results using the obtained data.

[0710] "Means of notification" refers to methods or technologies for informing a user or recipient of specific information, including forms such as email and app notifications.

[0711] "Means for receiving absence notifications" refers to a device or program that receives absence notifications from recipients and uses them to determine the next course of action.

[0712] "Means of adjusting the redelivery date and time" refers to a process or device that determines a new delivery date and time based on a missed delivery notice and informs the relevant parties of that information.

[0713] This invention is a method for streamlining delivery operations using an information processing system. The main components include a server, a portable terminal for delivery personnel, and a user.

[0714] First, the server receives location information transmitted from the delivery person's portable device. This location information is obtained using GPS technology and used to determine the delivery person's current location. The server also obtains traffic information from an external source. This source is a service that provides real-time traffic flow data, and the information can be aggregated via an API.

[0715] The server inputs the received location and traffic information into an AI algorithm to calculate the estimated delivery time for the package. This AI algorithm also plans the optimal delivery route, taking into account past data and current conditions. The AI ​​model used learns traffic patterns using machine learning techniques and can make predictions. These prediction results are stored in a database, and the server uses this to notify the user of the estimated delivery time.

[0716] The delivery driver's portable terminal receives optimal route information from the server and displays it on the terminal's screen. This information includes real-time traffic conditions and instructions for the best route. Because the portable terminal provides instructions to the delivery driver in real time, delivery efficiency can be improved.

[0717] The user receives a notification email from the server and confirms the scheduled delivery time. This notification includes a link that allows the user to easily report their absence if they are not available at the scheduled time. When the user uses this link to notify the server of their absence, the server arranges a new delivery date and time and informs both the delivery person and the user of the result.

[0718] As a concrete example, if a user is unable to receive a delivery, the server sends a notification email stating, "Delivery is scheduled for October 5th between 3 PM and 4 PM. If you will be absent, please use this link to contact us." This prompt allows the user to quickly notify the server of their absence, and the server can automatically arrange for redelivery. This improves delivery efficiency and customer satisfaction.

[0719] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0720] Step 1:

[0721] The server receives location information periodically transmitted from the delivery person's portable device. The location information used as input is coordinate data obtained using GPS technology. By storing this in a database, the server can identify the current location of the delivery person. Specifically, when the data is received, the server adds a timestamp and records the location information as part of the delivery history.

[0722] Step 2:

[0723] The server obtains real-time traffic information from external traffic information services. This data includes traffic flow, congestion, and road closures. The server analyzes this data as input and stores it in a database to identify changes in traffic conditions. Based on this information, it identifies traffic patterns and outputs the data in a formatted form for use in the next stage.

[0724] Step 3:

[0725] The server inputs the collected location and traffic information into an AI algorithm to calculate the estimated delivery time. Specifically, it passes this data to a generating AI model to predict the delivery time. The AI ​​model learns from past patterns and outputs the estimated delivery time along with the shortest route. The outputted estimated time and route information are used in the next notification step.

[0726] Step 4:

[0727] The server notifies the user of the calculated estimated delivery time. Specifically, it informs the user of the estimated delivery time in the form of an email or app notification. For example, it might send a message saying, "Your delivery is scheduled to arrive between 2 PM and 3 PM on October 5th." This output information is used to help the user prepare for receiving their delivery.

[0728] Step 5:

[0729] Users can notify the delivery service of their missed delivery via an email or in-app link that notifies them of the estimated delivery time. When a user clicks the link, the server receives the input and records it in the database as information indicating that redelivery is required. This input is used to schedule the next redelivery.

[0730] Step 6:

[0731] Based on the user's missed delivery notification, the server uses an AI algorithm to calculate and adjust the redelivery date and time. The AI ​​algorithm considers the current schedule and traffic information to output a new, available delivery date and time. The adjusted date and time are notified to the delivery person and the user and reflected in the delivery plan.

[0732] (Application Example 1)

[0733] 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".

[0734] To improve the efficiency of time management and delivery accuracy in delivery operations, accurate notification of scheduled delivery times and flexible handling of situations where recipients are absent are required. Furthermore, it is necessary to optimize delivery routes immediately in response to traffic conditions to increase efficiency.

[0735] 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.

[0736] In this invention, the server includes means for acquiring spatial information from terminal devices carried by delivery personnel, means for acquiring road condition information from external information sources, and means for calculating the estimated delivery time of the delivered items using the spatial information and road condition information. This enables improved delivery accuracy and efficient route management.

[0737] A "delivery person" is a person or organization responsible for transporting goods or items in order to carry out delivery operations.

[0738] A "terminal device" refers to an electronic device that is capable of inputting and displaying information and can communicate with external systems.

[0739] "Spatial information" refers to data that indicates the location of a specific point, and is geographical information obtained through methods such as GPS.

[0740] "External information sources" refer to databases and information systems that are located outside of servers and terminal devices and provide the necessary information.

[0741] "Road condition information" refers to traffic-related information that affects driving, such as road congestion and road passability.

[0742] "Estimated delivery time" refers to the time when the delivered item is expected to arrive at the designated delivery location.

[0743] A "beneficiary" refers to a person who receives benefits or advantages from receiving a delivery service.

[0744] An "absence notice" is information used to inform the recipient that they will be absent at the time of delivery, allowing for rescheduling of the delivery.

[0745] "Route information" refers to data about the optimal route for delivery personnel to reach their destination.

[0746] This invention provides a system that enables delivery personnel to efficiently perform delivery tasks and allows recipients to respond in a timely manner. The following hardware and software are used in the operation of this system.

[0747] The server receives spatial information at regular intervals from the terminal devices carried by delivery personnel to track their location. This spatial information includes GPS data, enabling highly accurate location determination. The server also obtains road condition information from external sources such as the Google Maps API to understand traffic conditions in real time. Based on this, the server applies AI algorithms to calculate estimated delivery times and optimize delivery routes based on spatial and road condition information.

[0748] The terminal device displays optimal route information received from the server to the delivery person. This display utilizes a smartphone application to provide real-time directions and estimated arrival times. Based on this information, the delivery person can perform deliveries efficiently.

[0749] The recipient receives a notification of the estimated delivery time from the server via email or a mobile app. The notification includes a section for sending a missed delivery notification, allowing the recipient to easily inform the server of their situation when they are away. This facilitates smooth arrangement of redelivery.

[0750] For example, when a recipient orders lunch, the server takes traffic congestion into account and predicts that the food will be delivered in 45 minutes, notifying the recipient accordingly. If the recipient is not home at that time, they can use the provided link to reschedule the delivery.

[0751] An example of a prompt message to input into a generative AI model is as follows:

[0752] "Please use the Google Maps API to tell me the current best route and estimated arrival time. The delivery destination is Shinjuku."

[0753] This invention will improve delivery efficiency and enhance convenience for recipients.

[0754] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0755] Step 1:

[0756] The server receives spatial information transmitted from the delivery person's terminal device at regular intervals. This input data includes precise location information using GPS. The server receives this data and determines the delivery person's current location.

[0757] Step 2:

[0758] The server accesses the Google Maps API, an external source of information, to retrieve the latest road conditions. This information includes data on road congestion and passable routes. The retrieved information is used to analyze traffic patterns and find the optimal route.

[0759] Step 3:

[0760] The server uses an AI algorithm to analyze the spatial information obtained in Step 1 and the road condition information obtained in Step 2. This analysis calculates the estimated delivery time to each delivery destination and formulates the optimal route. The AI ​​learns traffic congestion patterns and selects the route that achieves the shortest delivery time.

[0761] Step 4:

[0762] The server sends the calculated estimated delivery time and route information as a notification to the recipient. This notification arrives via the recipient's email address or mobile app. The notification input includes the delivery address information, and the output presents the estimated delivery time to the recipient.

[0763] Step 5:

[0764] The terminal receives route information transmitted from the server and displays it to the delivery person in real time. In this process, the delivery person checks the route from their current location to the destination through an application installed on the terminal. This allows the delivery person to deliver quickly by following the optimal route.

[0765] Step 6:

[0766] When a user receives a notification, they click the link in the notification to report their absence to the server. This input includes their intention to be absent at the scheduled delivery time, and the server then arranges a new redelivery date and time as output.

[0767] Step 7:

[0768] Based on the user's absence notification, the server automatically readjusts the delivery person's schedule and creates a new delivery plan. This process streamlines redelivery and reduces costs. The server notifies the user of the new schedule and suggests the optimal time for both the user and the delivery person.

[0769] 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.

[0770] This invention combines an information processing system that notifies recipients of the delivery time in advance with a function that recognizes the user's emotions and optimizes the delivery experience based on those emotions. The program processing in this system is described below in natural language.

[0771] Server Functions

[0772] First, the server periodically receives location information transmitted from the delivery person's terminal and calculates the delivery route and estimated delivery time. Second, it activates an emotion engine via email and the interface to analyze the user's emotions. The emotion engine analyzes the user's responses and feedback to determine whether they are positive or negative about the delivery. Based on this emotion information, the server adjusts notification methods and message content to provide a more personalized delivery experience.

[0773] The server has a feature that simplifies the process for users to notify the delivery person of their absence, thereby reducing the stress associated with being away from home. This also makes scheduling redelivery smoother.

[0774] Device functions

[0775] The delivery driver's terminal updates and displays the optimal delivery route received from the server in real time. This information is linked to real-time traffic conditions, enabling efficient deliveries.

[0776] User functions

[0777] Users receive delivery notification emails from the server and can easily contact the server using a link if they are not home. Users can also express their emotions through feedback to the server, and the server will use this information to adjust the format of delivery notifications.

[0778] For example, when a user receives a delivery schedule via email in the morning, the sentiment engine analyzes the user's past response data and detects that their mood for the day is positive. Based on this, the server sends a notification in a friendly tone, providing the user with a stress-free experience. If the user is not home, the email concisely presents an option for missed delivery, and the server quickly arranges a redelivery date and time.

[0779] Thus, this system aims to improve the user experience and, in particular, to streamline delivery operations by enabling personalized responses based on emotions.

[0780] The following describes the processing flow.

[0781] Step 1:

[0782] The server periodically obtains location information from the delivery person's terminal device. This allows the server to determine the delivery person's real-time location.

[0783] Step 2:

[0784] The server retrieves traffic information from an external database and analyzes it in combination with location information. Based on this, an AI algorithm is used to calculate the estimated delivery time for the package.

[0785] Step 3:

[0786] The server uses an AI algorithm to calculate the optimal delivery route based on traffic information and transmits this information to the delivery person's terminal. This information enables the delivery person to make deliveries more efficiently.

[0787] Step 4:

[0788] The server creates a notification for the user based on the estimated delivery time and route information. The notification includes the estimated delivery time, as well as a link or button for contacting the user if they are unable to receive the delivery.

[0789] Step 5:

[0790] Using an emotion engine, the server analyzes past user data to estimate the user's emotional state. Based on the obtained emotional information, it adjusts the content and tone of notifications and sends them to the user.

[0791] Step 6:

[0792] The user checks the notification email from the server and, if there is a problem with the scheduled delivery time, uses the absence notification link to send an absence notification.

[0793] Step 7:

[0794] The server receives a missed delivery notification from the user and suggests the most suitable redelivery date and time. This allows the server to coordinate the details of the redelivery with the user.

[0795] Step 8:

[0796] The delivery driver's terminal follows the delivery route provided by the server and immediately receives and responds to any updated information. This is to utilize real-time information and maintain efficient deliveries.

[0797] Step 9:

[0798] The server collects data from the entire delivery operation and updates the database to use for future notifications and route optimization.

[0799] (Example 2)

[0800] 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".

[0801] While existing delivery information systems can notify recipients of delivery times, they struggle to provide personalized service that takes recipients' feelings into account. Furthermore, the process for redelivery in case of absence is cumbersome, highlighting the need for improved customer satisfaction.

[0802] 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.

[0803] In this invention, the server includes means for acquiring location information from a communication device carried by the delivery person, means for acquiring traffic conditions from an external information source, and means for driving an analysis device for analyzing the user's emotions. This enables the customization of delivery notifications based on the recipient's emotions and smooth redelivery procedures in case of absence.

[0804] A "communication device" is a device carried by a delivery person that has the function of transmitting location information to a server.

[0805] "External information source" refers to the platform to which the server connects to obtain information on traffic conditions.

[0806] "Location information" refers to latitude and longitude data indicating the delivery person's current location, and the delivery route is calculated based on this information.

[0807] "Traffic conditions" refers to dynamic information about roads, such as road congestion and traffic restrictions.

[0808] An "analysis device" is a core component of a system that analyzes user emotions and adjusts notification content based on that data.

[0809] "Estimated delivery time" refers to the estimated arrival time of a delivery item, calculated based on location information and traffic conditions.

[0810] "Notification content" refers to a message sent to the recipient that includes information such as the scheduled delivery time and redelivery options.

[0811] "Redelivery procedure" refers to the method of requesting redelivery for receiving a package when the recipient is absent, and is a process designed to simplify the procedure for the recipient.

[0812] This invention is an information system for improving the delivery experience for recipients of delivered goods. The specific implementation method is described below.

[0813] The server uses a GPS-enabled device to receive location information from the communication device carried by the delivery person. This device is equipped with a dedicated application and has the function to automatically transmit location data to the server. Based on the acquired location information, the server obtains traffic information from external sources. This external source utilizes traffic information systems provided via the internet. Specifically, for example, it uses the API of a map service provider to acquire real-time data.

[0814] The server operates an emotion analysis system that utilizes natural language processing technology to analyze user emotions. This system collects user feedback and past history, and identifies emotions using an AI model. For example, if a user sends positive feedback such as "I'm looking forward to the delivery," the server recognizes this as a positive emotion and adjusts the notification accordingly.

[0815] The terminal displays optimized delivery routes sent from the server, assisting delivery drivers with navigation. This allows delivery drivers to efficiently deliver packages to customers. The terminal is equipped with a map display function that reflects real-time location information.

[0816] Users can check the delivery time and status in real time through delivery notification emails received from the server. If they are not home, they can easily request redelivery by clicking a link included in the email. The absence notification process is provided through a user-friendly interface, significantly reducing the effort required.

[0817] Examples of specific prompt messages are as follows:

[0818] "Of all the delivery notifications you've received in the past, which one did you find the most pleasant? What was its tone and content?"

[0819] Thus, the system based on the present invention improves the user experience and supports efficient delivery operations.

[0820] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0821] Step 1:

[0822] The server receives location information from the delivery person's communication device. This location information is GPS data and includes latitude and longitude. The server receives this data and stores it in a database. Specifically, the server continuously updates this location information every minute.

[0823] Step 2:

[0824] The server obtains traffic information from external sources. The input consists of requests to a real-time traffic data API. The output data from this API includes traffic congestion and road closure information. The server analyzes this traffic information and uses it to optimize delivery routes. Specifically, the server analyzes the API response and applies an algorithm to calculate the most efficient route.

[0825] Step 3:

[0826] The server calculates the estimated delivery time based on location information and traffic conditions. Input includes location data and traffic data. The server uses this data to calculate travel time to each delivery point and generates the shortest possible delivery schedule. The output is the estimated delivery time, which is then notified to both the delivery person and the recipient. Specifically, the server uses an appropriate algorithm to estimate travel time and incorporates the estimated time into the notification email.

[0827] Step 4:

[0828] The server collects user feedback and analyzes its sentiment. Input includes user response data. A generative AI model is used to perform sentiment analysis on this text data. The output is data indicating the emotional state, which is used to adjust the tone of notifications. Specifically, the AI ​​model scans the text and categorizes the feedback as either positive or negative.

[0829] Step 5:

[0830] The terminal displays optimized route information sent from the server. Its input is route data received from the server. Based on this data, the terminal uses a map application to provide appropriate navigation instructions. As output, the delivery person receives real-time route instructions and uses them to navigate. Specifically, the terminal utilizes voice guidance and map displays to efficiently guide the delivery person to their destination.

[0831] Step 6:

[0832] The user receives a delivery notification and, if absent, requests redelivery. The input comes from a notification email from the server. This email contains a link to request redelivery; the user clicks this link to request redelivery. The output is the redelivery option selected by the user, which is reflected on the server. Specifically, the user specifies the next delivery time by filling out and submitting a simple form.

[0833] (Application Example 2)

[0834] 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".

[0835] In today's delivery services, recipients sometimes experience dissatisfaction with their delivery experience, particularly because delivery notifications are often uniform and do not reflect individual needs or feelings. Furthermore, the process of redelivery when recipients are absent can be cumbersome and stressful for them. There is a need to solve these problems and provide a better customer experience.

[0836] 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.

[0837] In this invention, the server includes means for acquiring geographical location information from a terminal device carried by the delivery person, means for acquiring traffic condition information from an external information source, and means for analyzing the recipient's emotional state and personalizing the notification message. This makes it possible to accurately calculate the estimated delivery time and provide a personalized delivery notification that corresponds to the recipient's emotional state.

[0838] An "information processing system" is an integrated system of hardware and software for collecting, processing, and analyzing data and providing results according to specific tasks or purposes.

[0839] "Geographic location information" refers to information used to identify a specific point on Earth, and is usually expressed using latitude and longitude.

[0840] "Traffic condition information" refers to information regarding current congestion levels and traffic speeds on roads and in traffic systems.

[0841] "Estimated delivery time" refers to the specific time when the delivered item is expected to be delivered to the recipient.

[0842] The "recipient" is the individual or organization that actually receives the delivered item.

[0843] An "absence notification" is a procedure or message used to notify the recipient that they will not be present at the designated time.

[0844] "Emotional state" refers to an individual's mental state and can be classified into positive or negative emotions.

[0845] "Personalization" is the process of adjusting or customizing information or services to suit specific individuals or circumstances.

[0846] This invention is an information processing system aimed at analyzing the emotional state of recipients and personalizing the delivery experience based on that analysis. The server first obtains the geographical location information of the delivery person and collects traffic condition information from external sources. Using this information, it accurately calculates the estimated delivery time. It also evaluates the emotional state of recipients by analyzing feedback from recipients and past data.

[0847] Based on this information, the server generates personalized delivery notification messages. For example, if the recipient is in a positive emotional state, the notification message will be sent in a friendly tone. Also, if the recipient is absent, the server provides a redirection option to make it easy for them to report the absence.

[0848] The terminal device displays the optimal delivery route, reflecting the delivery person's real-time geographical location and traffic conditions. This allows delivery people to make deliveries efficiently.

[0849] Recipients receive notifications from the server via email or other electronic means, allowing for flexible responses when they are unavailable. Generative AI models are used for sentiment analysis throughout this process. For example, if a recipient has provided positive feedback on past orders, the next notification message will be a friendly one, such as "Have a great day!" Another example of a prompt for the generative AI model during sentiment analysis is, "Consider the user's past feedback to determine their positive or negative emotional state, and create a food delivery notification message based on that."

[0850] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0851] Step 1:

[0852] The server receives geographical location information from a terminal device carried by the delivery person. The input is real-time location data transmitted from the terminal, and the output is geographical location coordinates stored on the server. Based on this data, the server performs an operation to determine the delivery person's current location.

[0853] Step 2:

[0854] The server obtains traffic condition information from external sources. The input is current traffic data received through the API of a traffic information service, and the output is analyzed data regarding traffic congestion and road conditions. This allows the server to analyze traffic conditions that may affect deliveries.

[0855] Step 3:

[0856] The server retrieves past feedback data to analyze the recipient's emotional state. The input is the recipient's feedback history, and the output is the result of the emotional state analysis using a generative AI model. This allows the server to identify the recipient's past tendencies towards positive or negative emotions.

[0857] Step 4:

[0858] The server uses geographical location and traffic information to calculate the estimated delivery time for the package. The input is the current location and traffic data obtained in the previous step, and the output is the optimal delivery time prediction. This allows the server to plan an efficient delivery route.

[0859] Step 5:

[0860] The server generates a notification message to send to the recipient, reflecting the results of sentiment analysis. The input is the analyzed sentiment data, and the output is a personalized delivery notification message. The server uses this to generate a personalized message for the recipient.

[0861] Step 6:

[0862] Users receive personalized delivery notification messages from the server and take actions such as reporting absences as needed. The input is the message sent from the server, and the output is the user's response and absence report data. This allows users to easily communicate their reactions to the server.

[0863] Step 7:

[0864] The terminal displays real-time updated delivery route information to the delivery person. The input is optimized route information sent from the server, and the output is navigation instructions displayed on the terminal. This enables delivery people to perform deliveries efficiently.

[0865] 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.

[0866] 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.

[0867] 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 robot 414.

[0868] 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.

[0869] 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. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, 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.

[0870] 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.

[0871] 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.

[0872] 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.

[0873] 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."

[0874] 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.

[0875] 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.

[0876] 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.

[0877] 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.

[0878] 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.

[0879] 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.

[0880] 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.

[0881] 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.

[0882] 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.

[0883] 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.

[0884] 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.

[0885] 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 as being incorporated by reference.

[0886] The following is further disclosed regarding the embodiments described above.

[0887] (Claim 1)

[0888] An information processing system for notifying recipients of deliveries of the delivery time in advance,

[0889] A means of obtaining location information from a terminal device carried by the delivery person,

[0890] A means of obtaining traffic information from an external database,

[0891] A means for calculating the estimated delivery time of a delivery using the aforementioned location information and traffic information,

[0892] A means of notifying the recipient of the calculated estimated delivery time,

[0893] A means of receiving a notification from the recipient when they are unable to deliver,

[0894] A system that includes this.

[0895] (Claim 2)

[0896] The system according to claim 1, further comprising means for optimizing delivery routes based on traffic information.

[0897] (Claim 3)

[0898] The system according to claim 1, wherein the notification sent to the recipient includes a link or button for making an absence notification.

[0899] "Example 1"

[0900] (Claim 1)

[0901] An information processing system for notifying recipients of deliveries of the delivery time in advance,

[0902] A means of acquiring location information from a portable device,

[0903] Means of obtaining traffic information from external sources,

[0904] A means for calculating the estimated delivery time of a delivery using the aforementioned location information and traffic information,

[0905] A means of notifying the recipient of the calculated estimated delivery time,

[0906] A means of receiving a notification from the recipient when they are unable to deliver,

[0907] A means of adjusting the redelivery date and time based on the aforementioned absence notification,

[0908] A system that includes this.

[0909] (Claim 2)

[0910] The system according to claim 1, further comprising means for optimizing delivery routes based on traffic information.

[0911] (Claim 3)

[0912] The system according to claim 1, wherein the notification sent to the recipient includes means for making an absence notification.

[0913] "Application Example 1"

[0914] (Claim 1)

[0915] An information processing device for notifying the beneficiary of a delivery of the scheduled delivery time in advance,

[0916] A means of acquiring spatial information from terminal devices carried by delivery personnel,

[0917] Means of obtaining road condition information from external sources,

[0918] A means for calculating the estimated delivery time of a delivery using the aforementioned spatial information and road condition information,

[0919] A means of notifying the beneficiary of the calculated estimated delivery time,

[0920] A means of receiving absence notices from beneficiaries,

[0921] A means of optimizing and presenting delivery routes based on the estimated delivery time,

[0922] A system that includes this.

[0923] (Claim 2)

[0924] The system according to claim 1, further comprising means for optimizing delivery routes based on traffic conditions and providing route information to delivery personnel in real time.

[0925] (Claim 3)

[0926] The system according to claim 1, wherein the notification sent to the beneficiary includes a link or control for making a delivery notice, and includes means for scheduling a date and time for redelivery.

[0927] "Example 2 of combining an emotion engine"

[0928] (Claim 1)

[0929] An information processing system for notifying recipients of deliveries of the delivery time in advance,

[0930] A means of obtaining location information from a communication device carried by the delivery person,

[0931] Means of obtaining traffic information from external sources,

[0932] A means for calculating the estimated delivery time of a delivery using the aforementioned location information and traffic conditions,

[0933] A means of notifying the recipient of the calculated estimated delivery time,

[0934] A means of receiving a notification from the recipient when they are unable to deliver,

[0935] A means for driving an analysis device for analyzing user emotions,

[0936] A means of adjusting notification content based on the user's emotions,

[0937] A system that includes this.

[0938] (Claim 2)

[0939] The system according to claim 1, further comprising means for optimizing delivery routes based on traffic conditions.

[0940] (Claim 3)

[0941] The system according to claim 1, wherein the notification sent to the recipient includes information for making a absence notification.

[0942] "Application example 2 of combining emotional engines"

[0943] (Claim 1)

[0944] An information processing system for notifying recipients of deliveries of the delivery time in advance,

[0945] A means of obtaining geographical location information from a terminal device carried by a delivery person,

[0946] Means for obtaining traffic condition information from external sources,

[0947] A means for calculating the estimated delivery time of a delivery using the aforementioned geographic location information and traffic condition information,

[0948] A means of notifying the recipient of the calculated estimated delivery time,

[0949] A means of receiving absence reports from recipients,

[0950] A means of analyzing the recipient's emotional state and personalizing notification messages,

[0951] A system that includes this.

[0952] (Claim 2)

[0953] The system according to claim 1, further comprising means for optimizing delivery routes based on traffic condition information.

[0954] (Claim 3)

[0955] The system according to claim 1, wherein the notification sent to the recipient includes a link or operation for reporting absence. [Explanation of Symbols]

[0956] 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 information processing system for notifying recipients of deliveries of the delivery time in advance, A means of obtaining location information from a terminal device carried by the delivery person, A means of obtaining traffic information from an external database, A means for calculating the estimated delivery time of a delivery using the aforementioned location information and traffic information, A means of notifying the recipient of the calculated estimated delivery time, A means of receiving a notification from the recipient when they are unable to deliver, A system that includes this.

2. The system according to claim 1, further comprising means for optimizing delivery routes based on traffic information.

3. The system according to claim 1, wherein the notification sent to the recipient includes a link or button for making an absence notification.

Images