System

Abstract

A system is provided.SOLUTION: A system comprising: means for a user to obtain location information; means for obtaining real-time availability data; means for predicting locker usage trends based on historical data; means for comprehensively analyzing a plurality of factors; means for recommending an optimal locker; means for presenting information to a user; means for a user to reserve a locker; and means for providing a user with navigation information to a destination.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In urban areas around train stations, coin lockers tend to fill up during busy times and locations, creating a problem of users having to spend a lot of time finding a suitable locker. Conventional systems require users to search a wide area of ​​the station to find an available locker, which causes significant stress for users. Furthermore, it is difficult to suggest the optimal locker, taking into account multiple factors such as weather, congestion, and luggage size. Therefore, there is a need for a system that allows users to quickly and efficiently find the optimal coin locker. [Means for solving the problem]

[0005] The system of the present invention includes a means for users to obtain location information, a means for obtaining real-time availability data, a means for predicting locker usage trends based on past data, a means for comprehensively analyzing multiple factors, a means for recommending the most suitable locker, a means for presenting information to users, a means for users to reserve a locker, and a means for providing users with navigation information to their destination. Weather information and user reviews and reputation information can also be obtained and reflected in the recommendation of the most suitable locker. This system allows users to quickly and stress-free find the most suitable coin locker and temporarily store their luggage.

[0006] A "means for obtaining user location information" is a device or system that uses GPS or other location information obtaining technology to obtain the latitude and longitude of the user's current location.

[0007] "Means of obtaining real-time availability data" refers to API requests and data acquisition methods for obtaining current availability information in real time from each coin locker management system.

[0008] "Methods for predicting locker usage trends based on past data" refers to a method of analyzing past coin locker usage history and patterns, and predicting future usage trends using AI or statistical models.

[0009] "Means for comprehensively analyzing multiple factors" refers to a process in which information such as the user's location, availability data, weather, luggage size, and reviews is used as input data and comprehensively analyzed using an AI model or algorithm.

[0010] A "means for recommending the optimal locker" is an algorithm or method for selecting the coin locker that is most suitable for a user based on the results of analyzing multiple factors.

[0011] "Means of presenting information to users" refers to the screen display method and notification function for displaying information about the selected optimal coin locker on the user's device.

[0012] "Means for users to reserve a locker" refers to the process by which users input the necessary information to reserve a selected coin locker and send the reservation information to the locker management system.

[0013] "Means for providing users with navigation information to their destination" refers to a map application or navigation function that displays and provides route guidance information to the most suitable coin locker on the user's device. [Brief explanation of the drawings]

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

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

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

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

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

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

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0022] [First embodiment]

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

[0024] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

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

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

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0031] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

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

[0033] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

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

[0035] This invention provides a system that allows users to quickly find the best coin locker near an urban station. The system comprehensively analyzes the user's current location, real-time locker availability, past usage data, weather information, and multiple other factors to suggest the best coin locker for the user.

[0036] The program of this system operates in the following steps:

[0037] Program Operation

[0038] 1. Obtaining user location information

[0039] The device activates the GPS sensor and acquires the user's current location information (latitude and longitude). The acquired location information is then sent from the device to the server.

[0040] 2. Get real-time availability data

[0041] The server sends an API request to each station's coin locker management system to obtain real-time availability data for each locker, which is then stored in the server's database.

[0042] 3. AI-based selection of optimal lockers

[0043] The server inputs multiple factors, such as the user's location, real-time availability data, past usage data, weather information, user reviews, and luggage size, into an AI algorithm for comprehensive analysis, and the most suitable coin locker is selected as the result.

[0044] 4. Presentation of recommended results

[0045] The server sends information about the most suitable coin locker to the terminal, which displays the received information on its screen and suggests the most suitable coin locker to the user.

[0046] 5. Locker Reservation and Navigation

[0047] When the user selects a suggested locker, the terminal sends the information to the server. The server reserves the selected locker and receives confirmation of the reservation from the locker management system. The server then sends a reservation completion notification to the terminal, which notifies the user. In addition, the terminal provides the user with navigation information to the locker.

[0048] Specific examples

[0049] Consider a case where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage.

[0050] 1. Obtaining user location information

[0051] The user's device activates the GPS sensor and obtains the current location (e.g., latitude 35.681236, longitude 139.767125). The device then sends this location information to the server.

[0052] 2. Get real-time availability data

[0053] The server sends an API request to the Tokyo Station coin locker management system to obtain availability data. For example, suppose there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[0054] 3. AI-based selection of optimal lockers

[0055] The server inputs the user's current location, real-time availability, past usage data (the West Exit area tends to be crowded at 5 p.m. on weekdays), weather information (rainy weather), luggage size (large suitcase), and user reviews into an AI model for comprehensive analysis. As a result, it is determined that a locker in the East Exit area is the most suitable.

[0056] 4. Presentation of recommended results

[0057] The server sends locker information for the east exit area to the terminal, and the terminal displays to the user, "There are large-size coin lockers that are ideal for the east exit area."

[0058] 5. Locker Reservation and Navigation

[0059] When the user selects a suggested locker, the device sends this selection to the server. The server reserves the locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the device. The device displays a reservation completion notification to the user and also launches a map application to navigate the user to the locker. For example, it displays information such as "Proceed to the East Exit area. It is on your right."

[0060] As described above, this system allows users to quickly and efficiently find the most suitable coin locker, making luggage storage in urban areas extremely convenient.

[0061] The processing flow will be explained below.

[0062] Step 1:

[0063] The device activates the GPS sensor to obtain the current latitude and longitude information, which is then sent to the server.

[0064] Step 2:

[0065] The server sends an API request to the coin locker management system at each station, receives real-time availability data returned from each management system, and stores it in a database.

[0066] Step 3:

[0067] The server obtains the user's current location and real-time availability data. Additionally, it also obtains past coin locker usage history data, weather data, current date and time, and user reviews and reputation information from the database.

[0068] Step 4:

[0069] The server inputs this data into an AI algorithm to calculate the suitability of each locker, which then identifies the coin locker that is best suited for the user.

[0070] Step 5:

[0071] The server sends information about the best coin locker to the terminal, which then visually displays the received information to the user.

[0072] Step 6:

[0073] The user selects a suggested locker on the device screen, and the device sends the user's selection information to the server.

[0074] Step 7:

[0075] The server reserves the selected locker and sends the reservation information to the locker management system. After receiving confirmation of the reservation, the server sends a notification to the terminal.

[0076] Step 8:

[0077] The device will notify the user that the reservation is complete and then launch the navigation function, which will launch the map application and display a route from the user's current location to the desired locker.

[0078] Step 9:

[0079] The device provides users with real-time information about directions and turns, such as "Please proceed to the East Exit area. It's on your right."

[0080] This will allow users to find the most suitable coin locker quickly and stress-free, even in complex city centers.

[0081] Example 1

[0082] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0083] As demand for coin lockers available around urban stations increases, users face the challenge of finding the most suitable locker quickly. In particular, since it is necessary to take into account numerous factors, such as the user's current location, real-time availability, past usage data, weather information, and user reviews, a system is needed that can comprehensively analyze these complex conditions in a short amount of time and suggest the most suitable locker.

[0084] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0085] In this invention, the server includes means for users to obtain location information, means for obtaining real-time availability data, means for predicting locker usage trends based on past data, means for comprehensively analyzing multiple factors, means for recommending the most suitable locker, means for presenting information to the user, means for the user to reserve a locker, means for providing the user with navigation information to the destination, means for comprehensively analyzing factors using an AI algorithm, and means for the server to send an API request to the locker management system and obtain real-time availability data. This allows users to quickly and efficiently find the most suitable coin locker, making it extremely convenient to store luggage in urban areas.

[0086] A "user" refers to someone who uses the system to search for a coin locker.

[0087] "Location information" refers to the latitude and longitude of a user's current location as determined using location measurement means such as GPS.

[0088] "Real-time availability data" refers to data that represents the current availability of coin lockers at each location.

[0089] "Historical data" refers to information showing the usage history and trends of coin lockers in the past.

[0090] "Multiple factors" refers to a variety of data, including user location information, real-time availability data, past usage data, weather information, and reviews.

[0091] "AI algorithm" refers to an algorithm that uses machine learning and artificial intelligence technology to analyze data and derive optimal results.

[0092] "API Request" means a request for data retrieval sent through an Application Program Interface (API).

[0093] A "locker management system" refers to a system that manages coin locker availability and reservation information.

[0094] "Reservation" refers to the process of making a specific coin locker available for use for a certain period of time.

[0095] "Navigation information" refers to information that includes routes and instructions for users to reach their destination (coin locker).

[0096] This invention provides a system that allows users to quickly find the best coin locker near an urban station. The system comprehensively analyzes the user's current location, real-time locker availability, past usage data, weather information, and multiple other factors to suggest the best coin locker for the user.

[0097] The system is implemented using the following hardware and software.

[0098] Hardware

[0099] Device: A mobile device such as a smartphone or tablet that is equipped with a GPS sensor and acquires the user's current location.

[0100] Server: A powerful computer system that runs databases and AI algorithms.

[0101] Locker management system: A system that manages the availability and reservation information of coin lockers installed at each station.

[0102] software

[0103] GPS function: Built into the device's operating system (OS) and obtains the user's location information.

[0104] API: Application Program Interface (API) for data exchange between the server and the locker management system.

[0105] AI algorithm: An algorithm that comprehensively analyzes data and selects the optimal locker. Specifically, it uses a machine learning model (e.g., a deep learning model).

[0106] System Operation

[0107] 1. Obtaining user location information

[0108] The device activates the GPS sensor and acquires the user's current location information (latitude and longitude). The acquired location information is then sent from the device to the server.

[0109] 2. Get real-time availability data

[0110] The server sends an API request to each station's coin locker management system to obtain real-time availability data for each locker, which is then stored in the server's database.

[0111] 3. AI-based selection of optimal lockers

[0112] The server inputs multiple factors, such as the user's location, real-time availability data, past usage data, weather information, user reviews, and luggage size, into an AI algorithm for comprehensive analysis, and the most suitable coin locker is selected as the result.

[0113] 4. Presentation of recommended results

[0114] The server sends information about the most suitable coin locker to the terminal, which displays the received information on its screen and suggests the most suitable coin locker to the user.

[0115] 5. Locker Reservation and Navigation

[0116] When the user selects a suggested locker, the terminal sends the information to the server. The server reserves the selected locker and receives confirmation of the reservation from the locker management system. The server then sends a reservation completion notification to the terminal, which notifies the user. In addition, the terminal provides the user with navigation information to the locker.

[0117] Specific examples

[0118] As a concrete example, let's consider the case where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage.

[0119] Obtaining user location information: The user's device activates the GPS sensor and obtains the current location (latitude 35.681236, longitude 139.767125). The device then sends this location information to the server.

[0120] Obtaining real-time availability data: The server sends an API request to Tokyo Station's coin locker management system to obtain availability data. For example, there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[0121] AI-based selection of the best locker: The server inputs the user's current location, real-time availability, past usage data, weather information, luggage size, and customer reviews into an AI model for comprehensive analysis. As a result, it determines that a locker in the East Exit area is the best option.

[0122] Presentation of recommended results: The server sends locker information for the East Exit area to the terminal, and the terminal displays to the user, "There are large-size coin lockers that are ideal for the East Exit area."

[0123] Locker reservation and navigation: When the user selects a suggested locker, the device sends this selection to the server. The server reserves the locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the device. The device displays a reservation completion notification to the user and also launches a map application to navigate the user to the locker. For example, it may display information such as "Proceed to the East Exit area. It is on your right."

[0124] Prompt Sentence Examples

[0125] Prompt: "I've arrived at Tokyo Station. My current location is latitude 35.681236, longitude 139.767125. Can you tell me the best coin locker location?"

[0126] As described above, this system allows users to quickly and efficiently find the most suitable coin locker, making luggage storage in urban areas extremely convenient.

[0127] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0128] Step 1:

[0129] Obtaining user location information

[0130] The device activates the GPS sensor and obtains the user's current location information (latitude and longitude). The obtained location information is sent from the device to the server. Specifically, the device's GPS function reads the current location, generates data in the format of latitude 35.681236, longitude 139.767125, and sends it to the server via an HTTP request. At this time, the input is the location data from the GPS sensor, and the output is the latitude and longitude data sent to the server.

[0131] Step 2:

[0132] Get real-time availability data

[0133] The server sends an API request to each station's coin locker management system to obtain real-time availability data. For example, the server sends a request like "GET / coinlocker / status?station=tokyo". The obtained data shows the real-time availability of each locker. The input is the API request, and the output is availability data that is saved in the server's database. Specifically, the data obtained is "10 available lockers in the east exit area and 5 available lockers in the west exit area" and stored in the server's database.

[0134] Step 3:

[0135] AI-based selection of optimal lockers

[0136] The server inputs multiple factors, such as the user's location, real-time availability data, past usage data, weather information, reviews, and luggage size, into an AI algorithm for comprehensive analysis. Specifically, this data is compiled into a single data frame and then input into a machine learning model. For example, data such as latitude 35.681236, longitude 139.767125, rain, and large suitcase are input. The AI ​​algorithm analyzes this data and selects the most suitable coin locker. The input is the user's location and other related data, and the output is the result that "lockers in the east exit area are optimal."

[0137] Step 4:

[0138] Providing recommended results

[0139] The server sends the selected information about the optimal coin locker to the terminal. The terminal displays the received information on the screen and makes suggestions to the user. The input is the optimal locker information sent from the server, and the output is a message displayed on the terminal screen saying, "There is an L-size coin locker that is optimal in the East Exit area." Specifically, the terminal receives an HTTP request and displays the information on the screen.

[0140] Step 5:

[0141] Locker reservation and navigation

[0142] When the user selects a suggested locker, the device sends this information to the server. The server then sends an API request to the locker management system to reserve the selected locker. For example, a request like "POST / locker / reserve?id=12345" is sent. The server receives confirmation of reservation completion from the locker management system. The server then sends a notification of reservation completion to the device, which then notifies the user. The device then provides the user with navigation information to the locker. The input is the user's selection information and a reservation completion notification, and the output is a notification from the device such as "Reservation completed" and navigation information. Specifically, the device launches a map application and displays a guide message saying, "Proceed to the east exit area. It is on your right."

[0143] (Application example 1)

[0144] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0145] In urban and congested areas, it is difficult for users to efficiently and quickly find the optimal facilities and services. In particular, food delivery services require the selection of the optimal delivery location or store, taking into account the user's location, weather, congestion, and other factors. Furthermore, there is no established system for navigating users to their destination after selection, which hinders convenience.

[0146] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0147] In this invention, the server includes means for users to acquire location information, means for acquiring real-time availability data, means for predicting usage trends based on past data, means for comprehensively analyzing multiple factors, means for recommending optimal facilities, means for presenting information to users, means for users to reserve facilities, means for providing users with navigation information to their destination, and means for acquiring congestion and operation status of various bases in real time and recommending optimal delivery bases. This enables users to efficiently and quickly find optimal delivery bases and stores, improving convenience.

[0148] "User location information" is data that indicates the user's current geographic location and is obtained using sensors such as GPS.

[0149] "Real-time availability data" refers to data that indicates the availability status of each facility or service in real time.

[0150] "Past data" refers to data that indicates past usage history and trends, and is used to predict future usage trends.

[0151] "Multiple factors" refers to the variety of information the system takes into account, such as user location information, availability data, historical data, weather information, and reviews.

[0152] "Comprehensive analysis" refers to a data processing method that combines multiple factors to derive optimal results.

[0153] "Optimal facilities" refers to facilities and services that are most suitable for users under specific conditions.

[0154] "Recommending" means that the system suggests the best option to the user based on the analysis results.

[0155] "Presenting information" means that the system visually displays the analysis results and recommendations to the user.

[0156] "Reserving facilities" refers to the process by which a user reserves selected facilities or services in advance through the system.

[0157] "Navigation information" refers to information that provides directions and instructions for a user to reach a destination.

[0158] "Delivery base" refers to a location for receiving and shipping food in food delivery.

[0159] "Crowding status" is information that indicates how crowded a particular location or facility is currently.

[0160] "Operation status" is information that indicates the current level of operation of a facility or base.

[0161] MODE FOR CARRYING OUT THE INVENTION

[0162] This invention is a system that allows users to efficiently find the optimal facilities and services (hereinafter referred to as "delivery locations") in congested areas such as urban areas. This system is particularly applicable to food delivery, and provides a function to recommend the optimal delivery location by comprehensively analyzing the user's current location, real-time congestion status of locations, past usage trends, weather information, word-of-mouth reviews, etc.

[0163] Program Generation

[0164] In a specific embodiment, the system operates in the following steps.

[0165] Hardware and software used

[0166] The main components of this system are as follows:

[0167] User device: A smartphone or tablet equipped with a GPS sensor. Examples include iPhone and Android devices.

[0168] Server: Processes and optimizes the data sent by the user. Examples: AWS EC2, Google Cloud Platform.

[0169] AI algorithms: Comprehensive analysis of multiple factors. Examples: TensorFlow, PyTorch.

[0170] Navigation API: Showing users directions to their destination. Example: Google Maps API.

[0171] Data processing and calculation

[0172] Obtaining user location information: The user's device obtains the latitude and longitude using the GPS sensor and sends it to the server. For example, if the user is currently in Tokyo, their exact location information will be obtained.

[0173] Obtaining real-time availability data: Data is obtained from an API that manages the congestion status and capacity of each delivery location on the server.

[0174] Comprehensive data analysis: The server inputs the user's location, real-time availability, past data, weather information, reviews, etc. into an AI algorithm to select the optimal delivery location.

[0175] Presentation of recommendation results: The selection results are sent to the user's device and the information is presented visually. For example, "The optimal delivery point is here."

[0176] Providing navigation information: Using the Google Maps API, route information to the user's selected location is provided.

[0177] Specific examples

[0178] When a user attempts to use food delivery at home, the smartphone obtains the user's current location and recommends the most suitable restaurant, taking into account that it is a rainy day. This system allows users to efficiently and quickly find the optimal delivery location. For example, if a user inputs, "I am looking for the best food delivery option at home. It is a rainy day, and there are three restaurants: A, B, and C. Please recommend the best delivery location based on the location and availability of each," the system will analyze all factors and recommend the optimal location.

[0179] Prompt Sentence Examples

[0180] "A user is looking for the best restaurant delivery service in their current location. It's a rainy day, and there are three restaurants: A, B, and C. Please recommend the best delivery location based on their location and availability."

[0181] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0182] Step 1:

[0183] The user device activates the GPS sensor and acquires the user's current location (latitude and longitude). The input data is the location information from the GPS sensor, and the output data is the latitude and longitude information recorded on the device. The acquired location information is sent from the device to the server.

[0184] Step 2:

[0185] The server sends a request to an API that manages the congestion and operation status of each delivery location, and obtains real-time availability data. The input data is the request information to the API, and the output data is the real-time congestion and capacity data obtained by the server. The obtained data is stored in the server's database.

[0186] Step 3:

[0187] The server retrieves past usage data, weather information, and review data from the database. The input data is a database query, and the output data is the retrieved past usage history, current weather information, and review data. These data are used in the next step.

[0188] Step 4:

[0189] The server inputs multiple factors, such as the user's current location, real-time availability data, past usage data, weather information, and reviews, into an AI algorithm for comprehensive analysis. This diverse information constitutes the input data, and the output data is the optimal delivery point calculated by the AI ​​algorithm. Prediction processing is performed using an AI model (TensorFlow or PyTorch) to process the data.

[0190] Step 5:

[0191] The server recommends the optimal delivery point to the user based on the analysis results of the AI ​​algorithm. The input data is the AI ​​analysis results, and the output data is the recommendation information sent to the user's device. The device displays the recommendation results on the screen and tells the user, "Here is the optimal delivery point."

[0192] Step 6:

[0193] When the user selects a suggested delivery location, the user terminal sends the information to the server. The input data is the user's selection information, and the output data is the selection information sent to the server. The server then confirms the order at the selected delivery location.

[0194] Step 7:

[0195] The server sends reservation and order confirmation information to the delivery base for confirmation. The input data is reservation and order information, and the output data is reservation confirmation information from the delivery base. The server obtains the confirmation information and notifies the user's terminal.

[0196] Step 8:

[0197] The user's device uses the Google Maps API to provide the user with navigation information to the optimal delivery location. The input data is the request information to the Google Maps API, and the output data is the navigation information. The device presents this information to the user and begins navigation.

[0198] By following these steps, users can efficiently and quickly find the optimal delivery location and use food delivery services.

[0199] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0200] This invention provides a system that allows users to quickly find the best coin locker near urban stations, and also has the function of recognizing the user's emotions and recommending the best locker based on that.The system recommends the best coin locker to the user by comprehensively analyzing the user's current location, real-time locker availability, past usage data, weather information, word-of-mouth and reputation information, and user emotional data.

[0201] The program of this system operates in the following steps:

[0202] Program Operation

[0203] 1. Obtaining user location information

[0204] The device activates the GPS sensor and acquires the user's current location information (latitude and longitude). The acquired location information is then sent from the device to the server.

[0205] 2. Get real-time availability data

[0206] The server sends an API request to each station's coin locker management system to obtain real-time availability data for each locker, which is then stored in the server's database.

[0207] 3. AI-based selection of optimal lockers

[0208] The server inputs multiple factors, such as the user's location information, real-time availability data, past usage data, weather data, reviews and reputation, and emotional data from an emotion engine, into an AI algorithm for comprehensive analysis, and the most suitable coin locker is selected as the result.

[0209] 4. Presentation of recommended results

[0210] The server sends information about the best coin locker to the terminal, which visually displays the received information to the user and suggests the best locker according to the user's emotional state.

[0211] 5. Locker Reservation and Navigation

[0212] When the user selects a suggested locker, the terminal sends the information to the server. The server reserves the selected locker and receives confirmation of the reservation from the locker management system. The server then sends a reservation completion notification to the terminal, which notifies the user. In addition, the terminal provides the user with navigation information to the locker.

[0213] Specific examples

[0214] Consider a case where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage.

[0215] 1. Obtaining user location information

[0216] The user's device activates the GPS sensor and obtains the current location (e.g., latitude 35.681236, longitude 139.767125). The device then sends this location information to the server.

[0217] 2. Get real-time availability data

[0218] The server sends an API request to the Tokyo Station coin locker management system to obtain availability data. For example, suppose there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[0219] 3. AI-based selection of optimal lockers

[0220] The server inputs the user's current location, real-time availability, past usage data (the West Exit area tends to be crowded at 5 p.m. on weekdays), weather information (rainy weather), luggage size (large suitcase), user reviews, and user sentiment data obtained from an emotion engine into an AI model for comprehensive analysis. As a result, it is determined that a locker in the East Exit area is the most suitable.

[0221] 4. Presentation of recommended results

[0222] The server sends locker information for the East Exit area to the device, which then displays to the user, "There are large coin lockers ideal for the East Exit area." If the user is nervous, the device will also display a message that reflects their emotions, such as, "Don't worry, you'll easily find a locker in the East Exit area."

[0223] 5. Locker Reservation and Navigation

[0224] When the user selects a suggested locker, the device sends this selection to the server. The server reserves the locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the device. The device displays a reservation completion notification to the user and also launches a map application to navigate the user to the locker. For example, the device may display information such as "Proceed to the East Exit area. It is on your right," and guidance is given in a tone that reflects the user's emotional state.

[0225] In this way, the system can recommend the most suitable coin locker based on the user's emotions, and further improve the user experience by adjusting the way information is presented and the navigation method.

[0226] The processing flow will be explained below.

[0227] Step 1:

[0228] The device activates the GPS sensor and obtains the user's current location information. For example, the location information obtained is 35.681236 latitude and 139.767125 longitude. The obtained location information is sent from the device to the server.

[0229] Step 2:

[0230] The server sends an API request to each station's coin locker management system. The server receives real-time availability data returned from each management system and stores it in the server's database. For example, suppose there are 10 available lockers in the east exit area and 5 available lockers in the west exit area.

[0231] Step 3:

[0232] The device uses the user's facial expressions and voice data to collect data to input into the emotion engine, which analyzes the user's current emotional state (e.g., tense, relaxed), and sends that data from the device to the server.

[0233] Step 4:

[0234] The server inputs the user's current location, real-time availability data, past usage data, weather data, user reviews and reputation information, and sentiment data into an AI algorithm, which then comprehensively analyzes this information and calculates the suitability of each locker.

[0235] Step 5:

[0236] The server identifies the most suitable coin locker and sends that information to the terminal. For example, it may determine that the most suitable large coin locker is located in the East Exit area.

[0237] Step 6:

[0238] The device displays the received locker information to the user. For example, it may notify the user that "there is a large-size coin locker that is perfect for you in the East Exit area." In addition, messages based on the user's emotional state may also be displayed. For example, if the user is nervous, the device may display a message saying, "Relax, you'll easily find a locker in the East Exit area."

[0239] Step 7:

[0240] The user selects a suggested locker on the device screen, and the device sends the selection information to the server.

[0241] Step 8:

[0242] The server reserves the selected locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the terminal.

[0243] Step 9:

[0244] The device will notify the user that the reservation is complete and then launch the navigation function, which will launch the map application and display a route from the user's current location to the desired locker.

[0245] Step 10:

[0246] The device provides users with real-time information about directions and turns. For example, it displays specific instructions such as, "Go to the East Exit area. It's on your right." The device also adjusts the tone of the instructions based on the user's emotions.

[0247] This series of processes enables users to quickly and stresslessly find the best coin locker even in complex urban stations. In addition, the emotion engine is used to provide appropriate responses and guidance to users.

[0248] Example 2

[0249] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0250] Conventional coin locker management systems have problems in that it takes a lot of time for users to find the best locker, and they lack support that responds to the user's individual needs and emotional state. In particular, around urban stations, where there are many users, it is difficult to grasp availability in real time, and accurate recommendations are often not possible. Furthermore, there is a risk that the user experience will be poor because the service does not sufficiently take into account external factors such as the user's emotions and weather.

[0251] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for acquiring location information from the user, a means for acquiring real-time availability data, a means for predicting locker usage trends based on past usage data, a means for comprehensively analyzing multiple elements (location information, availability data, past usage data, weather information, emotional data, and word-of-mouth / reputation information), a means for recommending the most suitable locker, a means for presenting visual and emotional information to the user, a means for the user to reserve a locker, and a means for providing navigation information to the user to their destination. This allows the user to quickly find the most suitable coin locker and enjoy services tailored to the user's individual needs and emotional state.

[0252] "User" refers to the entity that uses this system to find the most suitable coin locker.

[0253] "Location Information" refers to latitude and longitude data that indicates a user's current location.

[0254] "Real-time availability data" refers to data regarding the current usage status of coin lockers.

[0255] "Past usage data" refers to data showing the past usage history and trends of coin lockers.

[0256] "Weather Information" refers to data regarding current and future weather.

[0257] "Emotional Data" refers to data that indicates a user's current emotional state.

[0258] "Word of mouth and reputation information" refers to data including ratings and impressions from past users of the coin locker.

[0259] "AI algorithm" refers to artificial intelligence technology that comprehensively analyzes multiple factors such as user location information, real-time availability data, past usage data, weather information, emotional data, and word-of-mouth and reputation information.

[0260] "Means for recommending the most suitable locker" refers to a function that uses an AI algorithm to guide users to the coin locker that is most suitable for them.

[0261] "Means for presenting visually and emotionally relevant information" refers to the ability to display information to users in a visually accessible format and provide messages tailored to the user's emotional state.

[0262] "Means of reservation" refers to the function that allows a user to reserve a coin locker of their choice via the system.

[0263] "Means for providing navigation information" refers to a function that provides route guidance to help users reach their desired coin locker without any hassle.

[0264] This invention provides a system that allows users to quickly find the best coin locker near urban stations, and also has the function of recognizing the user's emotions and recommending the best locker based on that.The system recommends the best coin locker to the user by comprehensively analyzing the user's current location, real-time locker availability, past usage data, weather information, word-of-mouth and reputation information, and user emotional data.

[0265] To implement this system, the following hardware and software are required:

[0266] Hardware:

[0267] 1. Device: A smartphone or tablet held by a user. It has a built-in GPS sensor and can obtain current location information.

[0268] 2. Server: A server computer for data processing and analysis, including a database for sending API requests and receiving and storing various data.

[0269] software:

[0270] 1. GPS module: Software that controls the GPS sensor in the device and obtains current location information.

[0271] 2. API Handler: A server-side program, software for obtaining real-time availability data from the coin locker management system.

[0272] 3. Database system: A system for storing and managing various data within a server. Examples include MySQL and PostgreSQL.

[0273] 4. AI algorithm: Software that comprehensively analyzes multiple data to select the optimal coin locker. The generated model is often implemented in a language such as Python.

[0274] 5. Emotion engine: Software for analyzing user emotion data and sending the results to the server. For example, it uses an emotion analysis library.

[0275] 6. User Interface: An application that visually presents information to the user on a device. Frameworks such as React Native may be used.

[0276] Examples:

[0277] Consider a case where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage in. In this case, the system operates as follows:

[0278] 1. Obtaining location information: The user's device activates the GPS sensor and obtains the current location (latitude 35.681236, longitude 139.767125). The device then sends this location information to the server.

[0279] 2. Obtaining real-time availability data: The server sends an API request to Tokyo Station's coin locker management system to obtain availability data. For example, suppose there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[0280] 3. AI-based selection of the best locker: The server inputs the user's current location, real-time availability, past usage data, weather information, user reviews and reputation data, and user sentiment data obtained from an emotion engine into an AI model for comprehensive analysis. As a result, a locker in the East Exit area may be determined to be the best choice.

[0281] 4. Presentation of recommended results: The server sends locker information for the East Exit area to the terminal, which then displays to the user, "There are large-size coin lockers ideal for the East Exit area." If the user is nervous, the terminal also displays a message appropriate to their emotions, such as, "Don't worry, you'll easily find a locker in the East Exit area."

[0282] 5. Locker reservation and navigation: Once the user selects a suggested locker, the device sends this selection to the server. The server reserves the locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the device. The device displays a reservation completion notification to the user and also launches a map application to navigate the user to the locker. For example, it displays information such as "Proceed to the East Exit area. It is on your right."

[0283] Example prompt sentence:

[0284] "Write a natural language description of a system for quickly finding the best coin locker near an urban station. Include examples of each step: obtaining user location information, obtaining real-time availability data, using AI to select the best locker, providing recommendations, reserving the locker, and navigating. Finally, include how to respond if the user is nervous."

[0285] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0286] Step 1:

[0287] Obtaining user location information

[0288] Subject: Terminal

[0289] The device activates the GPS sensor and obtains the user's current location information (latitude and longitude). The input here is the GPS sensor data, and the output is the current location information. The device periodically obtains location information and sends the latest current location to the server. This location information is used in the next processing step.

[0290] Step 2:

[0291] Get real-time availability data

[0292] Subject: Server

[0293] The server sends an API request to the coin locker management system at each station to obtain real-time availability data for each locker. The input here is the API response from the locker management system, and the output is the availability data. The obtained data is stored in the server's database, and the data is used in the next processing step.

[0294] Step 3:

[0295] AI-based selection of optimal lockers

[0296] Subject: Server

[0297] The server inputs the following factors into an AI algorithm, which then performs a comprehensive analysis to select the most suitable coin locker:

[0298] Your location

[0299] Real-time availability data

[0300] Historical usage data

[0301] Weather information

[0302] Reviews and reputation information

[0303] Emotional Data

[0304] The input here is data on the multiple factors mentioned above, and the output is information on the most suitable coin locker. The AI ​​algorithm comprehensively analyzes the data and selects the locker that best suits the user's current needs.

[0305] Step 4:

[0306] Presentation of recommendation results

[0307] Subject: Server and Terminal

[0308] The server sends information about the best coin locker to the terminal. The input here is the locker data from the server, and the output is the information display on the user's terminal. The terminal presents this information visually to the user, and if necessary, displays further encouraging or guiding messages based on the emotion data.

[0309] Step 5:

[0310] Locker reservation and navigation

[0311] Subject: Server and Terminal

[0312] When the user selects a suggested locker, the device sends that information to the server. The input here is the user's selection information, and the output is reservation data for the locker management system. The server reserves the locker and notifies the device that the reservation is complete. The device displays a reservation completion notification to the user and also launches a map application to provide navigation information to the destination.

[0313] (Application example 2)

[0314] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0315] Conventional coin locker recommendation systems can take into account the user's current location, real-time availability data, past usage data, weather information, word-of-mouth reviews, and reputation information, but they lack the functionality to recommend the optimal locker by taking the user's emotional state into account.As a result, they are unable to provide detailed services based on the user's emotions and psychological state, and are unable to sufficiently improve the user experience, which is an issue.

[0316] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0317] In this invention, the server includes a means for obtaining location information from the user, a means for obtaining real-time availability data, a means for predicting locker usage trends based on past data, a means for comprehensively analyzing multiple factors, a means for recommending the most suitable locker, a means for presenting information to the user, a means for recognizing the user's emotional state and presenting information accordingly, a means for the user to reserve a locker, and a means for providing the user with navigation information to their destination. This makes it possible to recommend the most suitable locker and present effective information taking into account the user's emotional state.

[0318] "Means by which users obtain location information" refers to methods of identifying the user's current location using a GPS sensor or communication network, etc., and sending that information to a server.

[0319] "Means of obtaining real-time availability data" refers to methods such as API requests for obtaining availability data in real time from the coin locker management system.

[0320] "Means for predicting locker usage trends based on past data" refers to algorithms and databases that analyze past coin locker usage data and predict future usage trends.

[0321] The "means for comprehensively analyzing multiple factors" refers to an AI algorithm that comprehensively analyzes data obtained from multiple sources, such as the user's location information, real-time availability, past usage data, weather information, word-of-mouth and reputation information, and emotional data.

[0322] The "means for recommending the optimal locker" is an algorithm that recommends the coin locker location that is optimal for the user based on the results of comprehensive data analysis.

[0323] The "means of presenting information to the user" refers to a user interface that provides information on the most suitable coin locker on the user's device through screen display, voice, etc.

[0324] "Means for recognizing the user's emotional state and presenting information accordingly" refers to a system that recognizes the user's emotions using sensors or image analysis, and provides messages and recommended information according to that emotional state.

[0325] "Means for users to reserve a locker" refers to the procedures and system that allow users to remotely reserve a selected locker using a device such as a smartphone.

[0326] "Means for providing users with navigation information to their destination" refers to a map application or navigation system that provides directions from the user's current location to the selected coin locker.

[0327] The system of this invention is designed to help users quickly find the best coin locker near urban train stations. The system comprehensively analyzes the user's current location, real-time locker availability, past usage data, weather information, word-of-mouth and reputation information, and emotional data, and then recommends the best coin locker for the user.

[0328] First, the user's smartphone acquires location information (latitude and longitude) using the built-in GPS sensor and sends this information to the server. The server then makes an API request to the coin locker management system at each station to obtain real-time availability data and store it in a database.

[0329] The server then inputs the acquired user location information, real-time availability data, past usage data, weather information, user reviews and reputation, and emotion data acquired from an emotion recognition engine into an AI algorithm for comprehensive analysis. This AI algorithm is implemented using TensorFlow and PyTorch, for example. As a result of the analysis, the optimal coin locker is selected.

[0330] Information about the selected coin locker is sent from the server to the user's smartphone and displayed visually. Furthermore, messages are displayed according to the user's emotional state. For example, if the user is feeling nervous, a reassuring message such as "Remain calm, you'll find it in the designated location soon" will be displayed.

[0331] Once the user selects a suggested locker, the information is sent to the server, which then reserves the selected locker. Once the reservation is complete, a confirmation is sent to the user's smartphone. The user is also given navigation information via a map application, which guides them to the locker.

[0332] This system allows users to receive recommendations for the best coin lockers that take their emotional state into account, and allows for consistent reservation and navigation. A specific scenario is shown below.

[0333] Specific examples

[0334] Consider a situation where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage.

[0335] Step 1: Get the user's location

[0336] The user's smartphone activates the GPS sensor and acquires the current location (e.g., latitude 35.681236, longitude 139.767125). The location information is sent to the server.

[0337] Step 2: Get real-time availability data

[0338] The server sends an API request to the Tokyo Station coin locker management system to obtain availability data. For example, suppose there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[0339] Step 3: AI-based selection of optimal lockers

[0340] The server inputs and analyzes the current location, real-time availability, past usage data (the West Exit area tends to be crowded at 5 PM on weekdays), weather information (rainy weather), luggage size (large suitcase), user reviews, and sentiment data into an AI model. As a result, it determines that a locker in the East Exit area is the best option.

[0341] Step 4: Providing recommendations

[0342] The server sends locker information for the East Exit area to the smartphone, and the message "There are large coin lockers perfect for the East Exit area" is displayed. If the user is nervous, the message "Don't worry, you'll find it in the designated location soon" is also displayed.

[0343] Step 5: Locker reservation and navigation

[0344] Once the user selects a suggested locker, the smartphone sends this selection to the server, which reserves the locker and retrieves the reservation information. The smartphone then displays a reservation completion notification and launches a map application to provide navigation information, such as "Proceed to the East Exit area. It's on your right."

[0345] Prompt Sentence Examples

[0346] "The user is located in Chuo Ward, Tokyo, and is looking for the best coin locker to store his luggage. It's currently 5 PM, it's raining, and the user is feeling a bit nervous. Based on past data, the West Exit area tends to be crowded around this time of day. Please suggest the best location for the coin locker and how to reserve it."

[0347] In this way, the system can recommend the most suitable coin locker based on the user's emotions, and further improve the user experience by adjusting the way information is presented and the navigation method.

[0348] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0349] Step 1:

[0350] The user's device activates the GPS sensor and acquires current location information (latitude and longitude). The acquired location information is sent to the server. The input is location information from the GPS sensor, and the output is the current location data sent to the server. Specifically, the user's smartphone acquires the current location and generates data such as latitude 35.681236 and longitude 139.767125.

[0351] Step 2:

[0352] The server sends an API request to the coin locker management system at each station to obtain real-time availability data. The input is the API request to the coin locker management system at each station, and the output is availability data. The data obtained by the server is saved in the server's database. Specifically, the server returns the availability of 10 lockers in the east exit area and 5 lockers in the west exit area.

[0353] Step 3:

[0354] The server collects and centralizes past usage data, weather information, reviews, and user sentiment data. The input is data from the server's database and external APIs, and the output is integrated analytical data. Specifically, it collects past weekday usage trends, current weather (rainy weather), review ratings, and sentiment data from an emotion recognition engine.

[0355] Step 4:

[0356] The server inputs location information, availability, past data, weather, reviews, and sentiment data into the AI ​​model, and performs an analysis to select the most suitable locker. The input is all collected data, and the output is the selection result of the most suitable locker. Specifically, the AI ​​model performs a comprehensive analysis and recommends the most suitable locker in the East Exit area for the user.

[0357] Step 5:

[0358] The server sends information about the optimal locker it has selected to the terminal. The terminal then visually displays the received information to the user. The input is the locker information selection result by the AI ​​model, and the output is the information displayed to the user. Specifically, the terminal displays, "There is an L-size coin locker that is ideal for the East Exit area." It also displays messages according to the user's emotional state. For example, if the user is nervous, a reassuring message will be displayed saying, "Remain calm, you will soon find it in the designated location."

[0359] Step 6:

[0360] When the user selects a suggested locker, the information is sent from the terminal to the server, which then reserves the selected locker. The input is the user's selection information, and the output is confirmation of the locker reservation. Specifically, the server sends the reservation information to the locker management system, and the reservation is completed.

[0361] Step 7:

[0362] Once the reservation is complete, the server notifies the user's device of the confirmation. The device then uses a map application to provide navigation information to the user. The input is reservation confirmation information, and the output is navigation information. Specifically, the device displays route guidance such as "Proceed to the East Exit area. It's on your right."

[0363] This series of processes allows users to use coin lockers quickly and optimally while taking into consideration their emotional state.

[0364] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0365] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0366] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0367] [Second embodiment]

[0368] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0369] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0370] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0371] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0372] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0373] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0374] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0375] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0376] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0377] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0378] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0379] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0380] This invention provides a system that allows users to quickly find the best coin locker near an urban station. The system comprehensively analyzes the user's current location, real-time locker availability, past usage data, weather information, and multiple other factors to suggest the best coin locker for the user.

[0381] The program of this system operates in the following steps:

[0382] Program Operation

[0383] 1. Obtaining user location information

[0384] The device activates the GPS sensor and acquires the user's current location information (latitude and longitude). The acquired location information is then sent from the device to the server.

[0385] 2. Get real-time availability data

[0386] The server sends an API request to each station's coin locker management system to obtain real-time availability data for each locker, which is then stored in the server's database.

[0387] 3. AI-based selection of optimal lockers

[0388] The server inputs multiple factors, such as the user's location, real-time availability data, past usage data, weather information, user reviews, and luggage size, into an AI algorithm for comprehensive analysis, and the most suitable coin locker is selected as the result.

[0389] 4. Presentation of recommended results

[0390] The server sends information about the most suitable coin locker to the terminal, which displays the received information on its screen and suggests the most suitable coin locker to the user.

[0391] 5. Locker Reservation and Navigation

[0392] When the user selects a suggested locker, the terminal sends the information to the server. The server reserves the selected locker and receives confirmation of the reservation from the locker management system. The server then sends a reservation completion notification to the terminal, which notifies the user. In addition, the terminal provides the user with navigation information to the locker.

[0393] Specific examples

[0394] Consider a case where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage.

[0395] 1. Obtaining user location information

[0396] The user's device activates the GPS sensor and obtains the current location (e.g., latitude 35.681236, longitude 139.767125). The device then sends this location information to the server.

[0397] 2. Get real-time availability data

[0398] The server sends an API request to the Tokyo Station coin locker management system to obtain availability data. For example, suppose there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[0399] 3. AI-based selection of optimal lockers

[0400] The server inputs the user's current location, real-time availability, past usage data (the West Exit area tends to be crowded at 5 p.m. on weekdays), weather information (rainy weather), luggage size (large suitcase), and user reviews into an AI model for comprehensive analysis. As a result, it is determined that a locker in the East Exit area is the most suitable.

[0401] 4. Presentation of recommended results

[0402] The server sends locker information for the east exit area to the terminal, and the terminal displays to the user, "There are large-size coin lockers that are ideal for the east exit area."

[0403] 5. Locker Reservation and Navigation

[0404] When the user selects a suggested locker, the device sends this selection to the server. The server reserves the locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the device. The device displays a reservation completion notification to the user and also launches a map application to navigate the user to the locker. For example, it displays information such as "Proceed to the East Exit area. It is on your right."

[0405] As described above, this system allows users to quickly and efficiently find the most suitable coin locker, making luggage storage in urban areas extremely convenient.

[0406] The processing flow will be explained below.

[0407] Step 1:

[0408] The device activates the GPS sensor to obtain the current latitude and longitude information, which is then sent to the server.

[0409] Step 2:

[0410] The server sends an API request to the coin locker management system at each station, receives real-time availability data returned from each management system, and stores it in a database.

[0411] Step 3:

[0412] The server obtains the user's current location and real-time availability data. Additionally, it also obtains past coin locker usage history data, weather data, current date and time, and user reviews and reputation information from the database.

[0413] Step 4:

[0414] The server inputs this data into an AI algorithm to calculate the suitability of each locker, which then identifies the coin locker that is best suited for the user.

[0415] Step 5:

[0416] The server sends information about the best coin locker to the terminal, which then visually displays the received information to the user.

[0417] Step 6:

[0418] The user selects a suggested locker on the device screen, and the device sends the user's selection information to the server.

[0419] Step 7:

[0420] The server reserves the selected locker and sends the reservation information to the locker management system. After receiving confirmation of the reservation, the server sends a notification to the terminal.

[0421] Step 8:

[0422] The device will notify the user that the reservation is complete and then launch the navigation function, which will launch the map application and display a route from the user's current location to the desired locker.

[0423] Step 9:

[0424] The device provides users with real-time information about directions and turns, such as "Please proceed to the East Exit area. It's on your right."

[0425] This will allow users to find the most suitable coin locker quickly and stress-free, even in complex city centers.

[0426] Example 1

[0427] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0428] As demand for coin lockers available around urban stations increases, users face the challenge of finding the most suitable locker quickly. In particular, since it is necessary to take into account numerous factors, such as the user's current location, real-time availability, past usage data, weather information, and user reviews, a system is needed that can comprehensively analyze these complex conditions in a short amount of time and suggest the most suitable locker.

[0429] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0430] In this invention, the server includes means for users to obtain location information, means for obtaining real-time availability data, means for predicting locker usage trends based on past data, means for comprehensively analyzing multiple factors, means for recommending the most suitable locker, means for presenting information to the user, means for the user to reserve a locker, means for providing the user with navigation information to the destination, means for comprehensively analyzing factors using an AI algorithm, and means for the server to send an API request to the locker management system and obtain real-time availability data. This allows users to quickly and efficiently find the most suitable coin locker, making it extremely convenient to store luggage in urban areas.

[0431] A "user" refers to someone who uses the system to search for a coin locker.

[0432] "Location information" refers to the latitude and longitude of a user's current location as determined using location measurement means such as GPS.

[0433] "Real-time availability data" refers to data that represents the current availability of coin lockers at each location.

[0434] "Historical data" refers to information showing the usage history and trends of coin lockers in the past.

[0435] "Multiple factors" refers to a variety of data, including user location information, real-time availability data, past usage data, weather information, and reviews.

[0436] "AI algorithm" refers to an algorithm that uses machine learning and artificial intelligence technology to analyze data and derive optimal results.

[0437] "API Request" means a request for data retrieval sent through an Application Program Interface (API).

[0438] A "locker management system" refers to a system that manages coin locker availability and reservation information.

[0439] "Reservation" refers to the process of making a specific coin locker available for use for a certain period of time.

[0440] "Navigation information" refers to information that includes routes and instructions for users to reach their destination (coin locker).

[0441] This invention provides a system that allows users to quickly find the best coin locker near an urban station. The system comprehensively analyzes the user's current location, real-time locker availability, past usage data, weather information, and multiple other factors to suggest the best coin locker for the user.

[0442] The system is implemented using the following hardware and software.

[0443] Hardware

[0444] Device: A mobile device such as a smartphone or tablet that is equipped with a GPS sensor and acquires the user's current location.

[0445] Server: A powerful computer system that runs databases and AI algorithms.

[0446] Locker management system: A system that manages the availability and reservation information of coin lockers installed at each station.

[0447] software

[0448] GPS function: Built into the device's operating system (OS) and obtains the user's location information.

[0449] API: Application Program Interface (API) for data exchange between the server and the locker management system.

[0450] AI algorithm: An algorithm that comprehensively analyzes data and selects the optimal locker. Specifically, it uses a machine learning model (e.g., a deep learning model).

[0451] System Operation

[0452] 1. Obtaining user location information

[0453] The device activates the GPS sensor and acquires the user's current location information (latitude and longitude). The acquired location information is then sent from the device to the server.

[0454] 2. Get real-time availability data

[0455] The server sends an API request to each station's coin locker management system to obtain real-time availability data for each locker, which is then stored in the server's database.

[0456] 3. AI-based selection of optimal lockers

[0457] The server inputs multiple factors, such as the user's location, real-time availability data, past usage data, weather information, user reviews, and luggage size, into an AI algorithm for comprehensive analysis, and the most suitable coin locker is selected as the result.

[0458] 4. Presentation of recommended results

[0459] The server sends information about the most suitable coin locker to the terminal, which displays the received information on its screen and suggests the most suitable coin locker to the user.

[0460] 5. Locker Reservation and Navigation

[0461] When the user selects a suggested locker, the terminal sends the information to the server. The server reserves the selected locker and receives confirmation of the reservation from the locker management system. The server then sends a reservation completion notification to the terminal, which notifies the user. In addition, the terminal provides the user with navigation information to the locker.

[0462] Specific examples

[0463] As a concrete example, let's consider the case where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage.

[0464] Obtaining user location information: The user's device activates the GPS sensor and obtains the current location (latitude 35.681236, longitude 139.767125). The device then sends this location information to the server.

[0465] Obtaining real-time availability data: The server sends an API request to Tokyo Station's coin locker management system to obtain availability data. For example, there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[0466] AI-based selection of the best locker: The server inputs the user's current location, real-time availability, past usage data, weather information, luggage size, and customer reviews into an AI model for comprehensive analysis. As a result, it determines that a locker in the East Exit area is the best option.

[0467] Presentation of recommended results: The server sends locker information for the East Exit area to the terminal, and the terminal displays to the user, "There are large-size coin lockers that are ideal for the East Exit area."

[0468] Locker reservation and navigation: When the user selects a suggested locker, the device sends this selection to the server. The server reserves the locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the device. The device displays a reservation completion notification to the user and also launches a map application to navigate the user to the locker. For example, it may display information such as "Proceed to the East Exit area. It is on your right."

[0469] Prompt Sentence Examples

[0470] Prompt: "I've arrived at Tokyo Station. My current location is latitude 35.681236, longitude 139.767125. Can you tell me the best coin locker location?"

[0471] As described above, this system allows users to quickly and efficiently find the most suitable coin locker, making luggage storage in urban areas extremely convenient.

[0472] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0473] Step 1:

[0474] Obtaining user location information

[0475] The device activates the GPS sensor and obtains the user's current location information (latitude and longitude). The obtained location information is sent from the device to the server. Specifically, the device's GPS function reads the current location, generates data in the format of latitude 35.681236, longitude 139.767125, and sends it to the server via an HTTP request. At this time, the input is the location data from the GPS sensor, and the output is the latitude and longitude data sent to the server.

[0476] Step 2:

[0477] Get real-time availability data

[0478] The server sends an API request to each station's coin locker management system to obtain real-time availability data. For example, the server sends a request like "GET / coinlocker / status?station=tokyo". The obtained data shows the real-time availability of each locker. The input is the API request, and the output is availability data that is saved in the server's database. Specifically, the data obtained is "10 available lockers in the east exit area and 5 available lockers in the west exit area" and stored in the server's database.

[0479] Step 3:

[0480] AI-based selection of optimal lockers

[0481] The server inputs multiple factors, such as the user's location, real-time availability data, past usage data, weather information, reviews, and luggage size, into an AI algorithm for comprehensive analysis. Specifically, this data is compiled into a single data frame and then input into a machine learning model. For example, data such as latitude 35.681236, longitude 139.767125, rain, and large suitcase are input. The AI ​​algorithm analyzes this data and selects the most suitable coin locker. The input is the user's location and other related data, and the output is the result that "lockers in the east exit area are optimal."

[0482] Step 4:

[0483] Providing recommended results

[0484] The server sends the selected information about the optimal coin locker to the terminal. The terminal displays the received information on the screen and makes suggestions to the user. The input is the optimal locker information sent from the server, and the output is a message displayed on the terminal screen saying, "There is an L-size coin locker that is optimal in the East Exit area." Specifically, the terminal receives an HTTP request and displays the information on the screen.

[0485] Step 5:

[0486] Locker reservation and navigation

[0487] When the user selects a suggested locker, the device sends this information to the server. The server then sends an API request to the locker management system to reserve the selected locker. For example, a request like "POST / locker / reserve?id=12345" is sent. The server receives confirmation of reservation completion from the locker management system. The server then sends a notification of reservation completion to the device, which then notifies the user. The device then provides the user with navigation information to the locker. The input is the user's selection information and a reservation completion notification, and the output is a notification from the device such as "Reservation completed" and navigation information. Specifically, the device launches a map application and displays a guide message saying, "Proceed to the east exit area. It is on your right."

[0488] (Application example 1)

[0489] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0490] In urban and congested areas, it is difficult for users to efficiently and quickly find the optimal facilities and services. In particular, food delivery services require the selection of the optimal delivery location or store, taking into account the user's location, weather, congestion, and other factors. Furthermore, there is no established system for navigating users to their destination after selection, which hinders convenience.

[0491] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0492] In this invention, the server includes means for users to acquire location information, means for acquiring real-time availability data, means for predicting usage trends based on past data, means for comprehensively analyzing multiple factors, means for recommending optimal facilities, means for presenting information to users, means for users to reserve facilities, means for providing users with navigation information to their destination, and means for acquiring congestion and operation status of various bases in real time and recommending optimal delivery bases. This enables users to efficiently and quickly find optimal delivery bases and stores, improving convenience.

[0493] "User location information" is data that indicates the user's current geographic location and is obtained using sensors such as GPS.

[0494] "Real-time availability data" refers to data that indicates the availability status of each facility or service in real time.

[0495] "Past data" refers to data that indicates past usage history and trends, and is used to predict future usage trends.

[0496] "Multiple factors" refers to the variety of information the system takes into account, such as user location information, availability data, historical data, weather information, and reviews.

[0497] "Comprehensive analysis" refers to a data processing method that combines multiple factors to derive optimal results.

[0498] "Optimal facilities" refers to facilities and services that are most suitable for users under specific conditions.

[0499] "Recommending" means that the system suggests the best option to the user based on the analysis results.

[0500] "Presenting information" means that the system visually displays the analysis results and recommendations to the user.

[0501] "Reserving facilities" refers to the process by which a user reserves selected facilities or services in advance through the system.

[0502] "Navigation information" refers to information that provides directions and instructions for a user to reach a destination.

[0503] "Delivery base" refers to a location for receiving and shipping food in food delivery.

[0504] "Crowding status" is information that indicates how crowded a particular location or facility is currently.

[0505] "Operation status" is information that indicates the current level of operation of a facility or base.

[0506] MODE FOR CARRYING OUT THE INVENTION

[0507] This invention is a system that allows users to efficiently find the optimal facilities and services (hereinafter referred to as "delivery locations") in congested areas such as urban areas. This system is particularly applicable to food delivery, and provides a function to recommend the optimal delivery location by comprehensively analyzing the user's current location, real-time congestion status of locations, past usage trends, weather information, word-of-mouth reviews, etc.

[0508] Program Generation

[0509] In a specific embodiment, the system operates in the following steps.

[0510] Hardware and software used

[0511] The main components of this system are as follows:

[0512] User device: A smartphone or tablet equipped with a GPS sensor. Examples include iPhone and Android devices.

[0513] Server: Processes and optimizes the data sent by the user. Examples: AWS EC2, Google Cloud Platform.

[0514] AI algorithms: Comprehensive analysis of multiple factors. Examples: TensorFlow, PyTorch.

[0515] Navigation API: Showing users directions to their destination. Example: Google Maps API.

[0516] Data processing and calculation

[0517] Obtaining user location information: The user's device obtains the latitude and longitude using the GPS sensor and sends it to the server. For example, if the user is currently in Tokyo, their exact location information will be obtained.

[0518] Obtaining real-time availability data: Data is obtained from an API that manages the congestion status and capacity of each delivery location on the server.

[0519] Comprehensive data analysis: The server inputs the user's location, real-time availability, past data, weather information, reviews, etc. into an AI algorithm to select the optimal delivery location.

[0520] Presentation of recommendation results: The selection results are sent to the user's device and the information is presented visually. For example, "The optimal delivery point is here."

[0521] Providing navigation information: Using the Google Maps API, route information to the user's selected location is provided.

[0522] Specific examples

[0523] When a user attempts to use food delivery at home, the smartphone obtains the user's current location and recommends the most suitable restaurant, taking into account that it is a rainy day. This system allows users to efficiently and quickly find the optimal delivery location. For example, if a user inputs, "I am looking for the best food delivery option at home. It is a rainy day, and there are three restaurants: A, B, and C. Please recommend the best delivery location based on the location and availability of each," the system will analyze all factors and recommend the optimal location.

[0524] Prompt Sentence Examples

[0525] "A user is looking for the best restaurant delivery service in their current location. It's a rainy day, and there are three restaurants: A, B, and C. Please recommend the best delivery location based on their location and availability."

[0526] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0527] Step 1:

[0528] The user device activates the GPS sensor and acquires the user's current location (latitude and longitude). The input data is the location information from the GPS sensor, and the output data is the latitude and longitude information recorded on the device. The acquired location information is sent from the device to the server.

[0529] Step 2:

[0530] The server sends a request to an API that manages the congestion and operation status of each delivery location, and obtains real-time availability data. The input data is the request information to the API, and the output data is the real-time congestion and capacity data obtained by the server. The obtained data is stored in the server's database.

[0531] Step 3:

[0532] The server retrieves past usage data, weather information, and review data from the database. The input data is a database query, and the output data is the retrieved past usage history, current weather information, and review data. These data are used in the next step.

[0533] Step 4:

[0534] The server inputs multiple factors, such as the user's current location, real-time availability data, past usage data, weather information, and reviews, into an AI algorithm for comprehensive analysis. This diverse information constitutes the input data, and the output data is the optimal delivery point calculated by the AI ​​algorithm. Prediction processing is performed using an AI model (TensorFlow or PyTorch) to process the data.

[0535] Step 5:

[0536] The server recommends the optimal delivery point to the user based on the analysis results of the AI ​​algorithm. The input data is the AI ​​analysis results, and the output data is the recommendation information sent to the user's device. The device displays the recommendation results on the screen and tells the user, "Here is the optimal delivery point."

[0537] Step 6:

[0538] When the user selects a suggested delivery location, the user terminal sends the information to the server. The input data is the user's selection information, and the output data is the selection information sent to the server. The server then confirms the order at the selected delivery location.

[0539] Step 7:

[0540] The server sends reservation and order confirmation information to the delivery base for confirmation. The input data is reservation and order information, and the output data is reservation confirmation information from the delivery base. The server obtains the confirmation information and notifies the user's terminal.

[0541] Step 8:

[0542] The user's device uses the Google Maps API to provide the user with navigation information to the optimal delivery location. The input data is the request information to the Google Maps API, and the output data is the navigation information. The device presents this information to the user and begins navigation.

[0543] By following these steps, users can efficiently and quickly find the optimal delivery location and use food delivery services.

[0544] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0545] This invention provides a system that allows users to quickly find the best coin locker near urban stations, and also has the function of recognizing the user's emotions and recommending the best locker based on that.The system recommends the best coin locker to the user by comprehensively analyzing the user's current location, real-time locker availability, past usage data, weather information, word-of-mouth and reputation information, and user emotional data.

[0546] The program of this system operates in the following steps:

[0547] Program Operation

[0548] 1. Obtaining user location information

[0549] The device activates the GPS sensor and acquires the user's current location information (latitude and longitude). The acquired location information is then sent from the device to the server.

[0550] 2. Get real-time availability data

[0551] The server sends an API request to each station's coin locker management system to obtain real-time availability data for each locker, which is then stored in the server's database.

[0552] 3. AI-based selection of optimal lockers

[0553] The server inputs multiple factors, such as the user's location information, real-time availability data, past usage data, weather data, reviews and reputation, and emotional data from an emotion engine, into an AI algorithm for comprehensive analysis, and the most suitable coin locker is selected as the result.

[0554] 4. Presentation of recommended results

[0555] The server sends information about the best coin locker to the terminal, which visually displays the received information to the user and suggests the best locker according to the user's emotional state.

[0556] 5. Locker Reservation and Navigation

[0557] When the user selects a suggested locker, the terminal sends the information to the server. The server reserves the selected locker and receives confirmation of the reservation from the locker management system. The server then sends a reservation completion notification to the terminal, which notifies the user. In addition, the terminal provides the user with navigation information to the locker.

[0558] Specific examples

[0559] Consider a case where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage.

[0560] 1. Obtaining user location information

[0561] The user's device activates the GPS sensor and obtains the current location (e.g., latitude 35.681236, longitude 139.767125). The device then sends this location information to the server.

[0562] 2. Get real-time availability data

[0563] The server sends an API request to the Tokyo Station coin locker management system to obtain availability data. For example, suppose there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[0564] 3. AI-based selection of optimal lockers

[0565] The server inputs the user's current location, real-time availability, past usage data (the West Exit area tends to be crowded at 5 p.m. on weekdays), weather information (rainy weather), luggage size (large suitcase), user reviews, and user sentiment data obtained from an emotion engine into an AI model for comprehensive analysis. As a result, it is determined that a locker in the East Exit area is the most suitable.

[0566] 4. Presentation of recommended results

[0567] The server sends locker information for the East Exit area to the device, which then displays to the user, "There are large coin lockers ideal for the East Exit area." If the user is nervous, the device will also display a message that reflects their emotions, such as, "Don't worry, you'll easily find a locker in the East Exit area."

[0568] 5. Locker Reservation and Navigation

[0569] When the user selects a suggested locker, the device sends this selection to the server. The server reserves the locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the device. The device displays a reservation completion notification to the user and also launches a map application to navigate the user to the locker. For example, the device may display information such as "Proceed to the East Exit area. It is on your right," and guidance is given in a tone that reflects the user's emotional state.

[0570] In this way, the system can recommend the most suitable coin locker based on the user's emotions, and further improve the user experience by adjusting the way information is presented and the navigation method.

[0571] The processing flow will be explained below.

[0572] Step 1:

[0573] The device activates the GPS sensor and obtains the user's current location information. For example, the location information obtained is 35.681236 latitude and 139.767125 longitude. The obtained location information is sent from the device to the server.

[0574] Step 2:

[0575] The server sends an API request to each station's coin locker management system. The server receives real-time availability data returned from each management system and stores it in the server's database. For example, suppose there are 10 available lockers in the east exit area and 5 available lockers in the west exit area.

[0576] Step 3:

[0577] The device uses the user's facial expressions and voice data to collect data to input into the emotion engine, which analyzes the user's current emotional state (e.g., tense, relaxed), and sends that data from the device to the server.

[0578] Step 4:

[0579] The server inputs the user's current location, real-time availability data, past usage data, weather data, user reviews and reputation information, and sentiment data into an AI algorithm, which then comprehensively analyzes this information and calculates the suitability of each locker.

[0580] Step 5:

[0581] The server identifies the most suitable coin locker and sends that information to the terminal. For example, it may determine that the most suitable large coin locker is located in the East Exit area.

[0582] Step 6:

[0583] The device displays the received locker information to the user. For example, it may notify the user that "there is a large-size coin locker that is perfect for you in the East Exit area." In addition, messages based on the user's emotional state may also be displayed. For example, if the user is nervous, the device may display a message saying, "Relax, you'll easily find a locker in the East Exit area."

[0584] Step 7:

[0585] The user selects a suggested locker on the device screen, and the device sends the selection information to the server.

[0586] Step 8:

[0587] The server reserves the selected locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the terminal.

[0588] Step 9:

[0589] The device will notify the user that the reservation is complete and then launch the navigation function, which will launch the map application and display a route from the user's current location to the desired locker.

[0590] Step 10:

[0591] The device provides users with real-time information about directions and turns. For example, it displays specific instructions such as, "Go to the East Exit area. It's on your right." The device also adjusts the tone of the instructions based on the user's emotions.

[0592] This series of processes enables users to quickly and stresslessly find the best coin locker even in complex urban stations. In addition, the emotion engine is used to provide appropriate responses and guidance to users.

[0593] Example 2

[0594] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0595] Conventional coin locker management systems have problems in that it takes a lot of time for users to find the best locker, and they lack support that responds to the user's individual needs and emotional state. In particular, around urban stations, where there are many users, it is difficult to grasp availability in real time, and accurate recommendations are often not possible. Furthermore, there is a risk that the user experience will be poor because the service does not sufficiently take into account external factors such as the user's emotions and weather.

[0596] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for acquiring location information from the user, a means for acquiring real-time availability data, a means for predicting locker usage trends based on past usage data, a means for comprehensively analyzing multiple elements (location information, availability data, past usage data, weather information, emotional data, and word-of-mouth / reputation information), a means for recommending the most suitable locker, a means for presenting visual and emotional information to the user, a means for the user to reserve a locker, and a means for providing navigation information to the user to their destination. This allows the user to quickly find the most suitable coin locker and enjoy services tailored to the user's individual needs and emotional state.

[0597] "User" refers to the entity that uses this system to find the most suitable coin locker.

[0598] "Location Information" refers to latitude and longitude data that indicates a user's current location.

[0599] "Real-time availability data" refers to data regarding the current usage status of coin lockers.

[0600] "Past usage data" refers to data showing the past usage history and trends of coin lockers.

[0601] "Weather Information" refers to data regarding current and future weather.

[0602] "Emotional Data" refers to data that indicates a user's current emotional state.

[0603] "Word of mouth and reputation information" refers to data including ratings and impressions from past users of the coin locker.

[0604] "AI algorithm" refers to artificial intelligence technology that comprehensively analyzes multiple factors such as user location information, real-time availability data, past usage data, weather information, emotional data, and word-of-mouth and reputation information.

[0605] "Means for recommending the most suitable locker" refers to a function that uses an AI algorithm to guide users to the coin locker that is most suitable for them.

[0606] "Means for presenting visually and emotionally relevant information" refers to the ability to display information to users in a visually accessible format and provide messages tailored to the user's emotional state.

[0607] "Means of reservation" refers to the function that allows a user to reserve a coin locker of their choice via the system.

[0608] "Means for providing navigation information" refers to a function that provides route guidance to help users reach their desired coin locker without any hassle.

[0609] This invention provides a system that allows users to quickly find the best coin locker near urban stations, and also has the function of recognizing the user's emotions and recommending the best locker based on that.The system recommends the best coin locker to the user by comprehensively analyzing the user's current location, real-time locker availability, past usage data, weather information, word-of-mouth and reputation information, and user emotional data.

[0610] To implement this system, the following hardware and software are required:

[0611] Hardware:

[0612] 1. Device: A smartphone or tablet held by a user. It has a built-in GPS sensor and can obtain current location information.

[0613] 2. Server: A server computer for data processing and analysis, including a database for sending API requests and receiving and storing various data.

[0614] software:

[0615] 1. GPS module: Software that controls the GPS sensor in the device and obtains current location information.

[0616] 2. API Handler: A server-side program, software for obtaining real-time availability data from the coin locker management system.

[0617] 3. Database system: A system for storing and managing various data within a server. Examples include MySQL and PostgreSQL.

[0618] 4. AI algorithm: Software that comprehensively analyzes multiple data to select the optimal coin locker. The generated model is often implemented in a language such as Python.

[0619] 5. Emotion engine: Software for analyzing user emotion data and sending the results to the server. For example, it uses an emotion analysis library.

[0620] 6. User Interface: An application that visually presents information to the user on a device. Frameworks such as React Native may be used.

[0621] Examples:

[0622] Consider a case where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage in. In this case, the system operates as follows:

[0623] 1. Obtaining location information: The user's device activates the GPS sensor and obtains the current location (latitude 35.681236, longitude 139.767125). The device then sends this location information to the server.

[0624] 2. Obtaining real-time availability data: The server sends an API request to Tokyo Station's coin locker management system to obtain availability data. For example, suppose there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[0625] 3. AI-based selection of the best locker: The server inputs the user's current location, real-time availability, past usage data, weather information, user reviews and reputation data, and user sentiment data obtained from an emotion engine into an AI model for comprehensive analysis. As a result, a locker in the East Exit area may be determined to be the best choice.

[0626] 4. Presentation of recommended results: The server sends locker information for the East Exit area to the terminal, which then displays to the user, "There are large-size coin lockers ideal for the East Exit area." If the user is nervous, the terminal also displays a message appropriate to their emotions, such as, "Don't worry, you'll easily find a locker in the East Exit area."

[0627] 5. Locker reservation and navigation: Once the user selects a suggested locker, the device sends this selection to the server. The server reserves the locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the device. The device displays a reservation completion notification to the user and also launches a map application to navigate the user to the locker. For example, it displays information such as "Proceed to the East Exit area. It is on your right."

[0628] Example prompt sentence:

[0629] "Write a natural language description of a system for quickly finding the best coin locker near an urban station. Include examples of each step: obtaining user location information, obtaining real-time availability data, using AI to select the best locker, providing recommendations, reserving the locker, and navigating. Finally, include how to respond if the user is nervous."

[0630] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0631] Step 1:

[0632] Obtaining user location information

[0633] Subject: Terminal

[0634] The device activates the GPS sensor and obtains the user's current location information (latitude and longitude). The input here is the GPS sensor data, and the output is the current location information. The device periodically obtains location information and sends the latest current location to the server. This location information is used in the next processing step.

[0635] Step 2:

[0636] Get real-time availability data

[0637] Subject: Server

[0638] The server sends an API request to the coin locker management system at each station to obtain real-time availability data for each locker. The input here is the API response from the locker management system, and the output is the availability data. The obtained data is stored in the server's database, and the data is used in the next processing step.

[0639] Step 3:

[0640] AI-based selection of optimal lockers

[0641] Subject: Server

[0642] The server inputs the following factors into an AI algorithm, which then performs a comprehensive analysis to select the most suitable coin locker:

[0643] Your location

[0644] Real-time availability data

[0645] Historical usage data

[0646] Weather information

[0647] Reviews and reputation information

[0648] Emotional Data

[0649] The input here is data on the multiple factors mentioned above, and the output is information on the most suitable coin locker. The AI ​​algorithm comprehensively analyzes the data and selects the locker that best suits the user's current needs.

[0650] Step 4:

[0651] Presentation of recommendation results

[0652] Subject: Server and Terminal

[0653] The server sends information about the best coin locker to the terminal. The input here is the locker data from the server, and the output is the information display on the user's terminal. The terminal presents this information visually to the user, and if necessary, displays further encouraging or guiding messages based on the emotion data.

[0654] Step 5:

[0655] Locker reservation and navigation

[0656] Subject: Server and Terminal

[0657] When the user selects a suggested locker, the device sends that information to the server. The input here is the user's selection information, and the output is reservation data for the locker management system. The server reserves the locker and notifies the device that the reservation is complete. The device displays a reservation completion notification to the user and also launches a map application to provide navigation information to the destination.

[0658] (Application example 2)

[0659] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0660] Conventional coin locker recommendation systems can take into account the user's current location, real-time availability data, past usage data, weather information, word-of-mouth reviews, and reputation information, but they lack the functionality to recommend the optimal locker by taking the user's emotional state into account.As a result, they are unable to provide detailed services based on the user's emotions and psychological state, and are unable to sufficiently improve the user experience, which is an issue.

[0661] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0662] In this invention, the server includes a means for obtaining location information from the user, a means for obtaining real-time availability data, a means for predicting locker usage trends based on past data, a means for comprehensively analyzing multiple factors, a means for recommending the most suitable locker, a means for presenting information to the user, a means for recognizing the user's emotional state and presenting information accordingly, a means for the user to reserve a locker, and a means for providing the user with navigation information to their destination. This makes it possible to recommend the most suitable locker and present effective information taking into account the user's emotional state.

[0663] "Means by which users obtain location information" refers to methods of identifying the user's current location using a GPS sensor or communication network, etc., and sending that information to a server.

[0664] "Means of obtaining real-time availability data" refers to methods such as API requests for obtaining availability data in real time from the coin locker management system.

[0665] "Means for predicting locker usage trends based on past data" refers to algorithms and databases that analyze past coin locker usage data and predict future usage trends.

[0666] The "means for comprehensively analyzing multiple factors" refers to an AI algorithm that comprehensively analyzes data obtained from multiple sources, such as the user's location information, real-time availability, past usage data, weather information, word-of-mouth and reputation information, and emotional data.

[0667] The "means for recommending the optimal locker" is an algorithm that recommends the coin locker location that is optimal for the user based on the results of comprehensive data analysis.

[0668] The "means of presenting information to the user" refers to a user interface that provides information on the most suitable coin locker on the user's device through screen display, voice, etc.

[0669] "Means for recognizing the user's emotional state and presenting information accordingly" refers to a system that recognizes the user's emotions using sensors or image analysis, and provides messages and recommended information according to that emotional state.

[0670] "Means for users to reserve a locker" refers to the procedures and system that allow users to remotely reserve a selected locker using a device such as a smartphone.

[0671] "Means for providing users with navigation information to their destination" refers to a map application or navigation system that provides directions from the user's current location to the selected coin locker.

[0672] The system of this invention is designed to help users quickly find the best coin locker near urban train stations. The system comprehensively analyzes the user's current location, real-time locker availability, past usage data, weather information, word-of-mouth and reputation information, and emotional data, and then recommends the best coin locker for the user.

[0673] First, the user's smartphone acquires location information (latitude and longitude) using the built-in GPS sensor and sends this information to the server. The server then makes an API request to the coin locker management system at each station to obtain real-time availability data and store it in a database.

[0674] The server then inputs the acquired user location information, real-time availability data, past usage data, weather information, user reviews and reputation, and emotion data acquired from an emotion recognition engine into an AI algorithm for comprehensive analysis. This AI algorithm is implemented using TensorFlow and PyTorch, for example. As a result of the analysis, the optimal coin locker is selected.

[0675] Information about the selected coin locker is sent from the server to the user's smartphone and displayed visually. Furthermore, messages are displayed according to the user's emotional state. For example, if the user is feeling nervous, a reassuring message such as "Remain calm, you'll find it in the designated location soon" will be displayed.

[0676] Once the user selects a suggested locker, the information is sent to the server, which then reserves the selected locker. Once the reservation is complete, a confirmation is sent to the user's smartphone. The user is also given navigation information via a map application, which guides them to the locker.

[0677] This system allows users to receive recommendations for the best coin lockers that take their emotional state into account, and allows for consistent reservation and navigation. A specific scenario is shown below.

[0678] Specific examples

[0679] Consider a situation where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage.

[0680] Step 1: Get the user's location

[0681] The user's smartphone activates the GPS sensor and acquires the current location (e.g., latitude 35.681236, longitude 139.767125). The location information is sent to the server.

[0682] Step 2: Get real-time availability data

[0683] The server sends an API request to the Tokyo Station coin locker management system to obtain availability data. For example, suppose there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[0684] Step 3: AI-based selection of optimal lockers

[0685] The server inputs and analyzes the current location, real-time availability, past usage data (the West Exit area tends to be crowded at 5 PM on weekdays), weather information (rainy weather), luggage size (large suitcase), user reviews, and sentiment data into an AI model. As a result, it determines that a locker in the East Exit area is the best option.

[0686] Step 4: Providing recommendations

[0687] The server sends locker information for the East Exit area to the smartphone, and the message "There are large coin lockers perfect for the East Exit area" is displayed. If the user is nervous, the message "Don't worry, you'll find it in the designated location soon" is also displayed.

[0688] Step 5: Locker reservation and navigation

[0689] Once the user selects a suggested locker, the smartphone sends this selection to the server, which reserves the locker and retrieves the reservation information. The smartphone then displays a reservation completion notification and launches a map application to provide navigation information, such as "Proceed to the East Exit area. It's on your right."

[0690] Prompt Sentence Examples

[0691] "The user is located in Chuo Ward, Tokyo, and is looking for the best coin locker to store his luggage. It's currently 5 PM, it's raining, and the user is feeling a bit nervous. Based on past data, the West Exit area tends to be crowded around this time of day. Please suggest the best location for the coin locker and how to reserve it."

[0692] In this way, the system can recommend the most suitable coin locker based on the user's emotions, and further improve the user experience by adjusting the way information is presented and the navigation method.

[0693] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0694] Step 1:

[0695] The user's device activates the GPS sensor and acquires current location information (latitude and longitude). The acquired location information is sent to the server. The input is location information from the GPS sensor, and the output is the current location data sent to the server. Specifically, the user's smartphone acquires the current location and generates data such as latitude 35.681236 and longitude 139.767125.

[0696] Step 2:

[0697] The server sends an API request to the coin locker management system at each station to obtain real-time availability data. The input is the API request to the coin locker management system at each station, and the output is availability data. The data obtained by the server is saved in the server's database. Specifically, the server returns the availability of 10 lockers in the east exit area and 5 lockers in the west exit area.

[0698] Step 3:

[0699] The server collects and centralizes past usage data, weather information, reviews, and user sentiment data. The input is data from the server's database and external APIs, and the output is integrated analytical data. Specifically, it collects past weekday usage trends, current weather (rainy weather), review ratings, and sentiment data from an emotion recognition engine.

[0700] Step 4:

[0701] The server inputs location information, availability, past data, weather, reviews, and sentiment data into the AI ​​model, and performs an analysis to select the most suitable locker. The input is all collected data, and the output is the selection result of the most suitable locker. Specifically, the AI ​​model performs a comprehensive analysis and recommends the most suitable locker in the East Exit area for the user.

[0702] Step 5:

[0703] The server sends information about the optimal locker it has selected to the terminal. The terminal then visually displays the received information to the user. The input is the locker information selection result by the AI ​​model, and the output is the information displayed to the user. Specifically, the terminal displays, "There is an L-size coin locker that is ideal for the East Exit area." It also displays messages according to the user's emotional state. For example, if the user is nervous, a reassuring message will be displayed saying, "Remain calm, you will soon find it in the designated location."

[0704] Step 6:

[0705] When the user selects a suggested locker, the information is sent from the terminal to the server, which then reserves the selected locker. The input is the user's selection information, and the output is confirmation of the locker reservation. Specifically, the server sends the reservation information to the locker management system, and the reservation is completed.

[0706] Step 7:

[0707] Once the reservation is complete, the server notifies the user's device of the confirmation. The device then uses a map application to provide navigation information to the user. The input is reservation confirmation information, and the output is navigation information. Specifically, the device displays route guidance such as "Proceed to the East Exit area. It's on your right."

[0708] This series of processes allows users to use coin lockers quickly and optimally while taking into consideration their emotional state.

[0709] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0710] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0711] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0712] [Third embodiment]

[0713] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0714] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0715] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0716] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0717] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0718] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0719] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0720] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0721] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0722] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0723] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0724] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0725] This invention provides a system that allows users to quickly find the best coin locker near an urban station. The system comprehensively analyzes the user's current location, real-time locker availability, past usage data, weather information, and multiple other factors to suggest the best coin locker for the user.

[0726] The program of this system operates in the following steps:

[0727] Program Operation

[0728] 1. Obtaining user location information

[0729] The device activates the GPS sensor and acquires the user's current location information (latitude and longitude). The acquired location information is then sent from the device to the server.

[0730] 2. Get real-time availability data

[0731] The server sends an API request to each station's coin locker management system to obtain real-time availability data for each locker, which is then stored in the server's database.

[0732] 3. AI-based selection of optimal lockers

[0733] The server inputs multiple factors, such as the user's location, real-time availability data, past usage data, weather information, user reviews, and luggage size, into an AI algorithm for comprehensive analysis, and the most suitable coin locker is selected as the result.

[0734] 4. Presentation of recommended results

[0735] The server sends information about the most suitable coin locker to the terminal, which displays the received information on its screen and suggests the most suitable coin locker to the user.

[0736] 5. Locker Reservation and Navigation

[0737] When the user selects a suggested locker, the terminal sends the information to the server. The server reserves the selected locker and receives confirmation of the reservation from the locker management system. The server then sends a reservation completion notification to the terminal, which notifies the user. In addition, the terminal provides the user with navigation information to the locker.

[0738] Specific examples

[0739] Consider a case where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage.

[0740] 1. Obtaining user location information

[0741] The user's device activates the GPS sensor and obtains the current location (e.g., latitude 35.681236, longitude 139.767125). The device then sends this location information to the server.

[0742] 2. Get real-time availability data

[0743] The server sends an API request to the Tokyo Station coin locker management system to obtain availability data. For example, suppose there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[0744] 3. AI-based selection of optimal lockers

[0745] The server inputs the user's current location, real-time availability, past usage data (the West Exit area tends to be crowded at 5 p.m. on weekdays), weather information (rainy weather), luggage size (large suitcase), and user reviews into an AI model for comprehensive analysis. As a result, it is determined that a locker in the East Exit area is the most suitable.

[0746] 4. Presentation of recommended results

[0747] The server sends locker information for the east exit area to the terminal, and the terminal displays to the user, "There are large-size coin lockers that are ideal for the east exit area."

[0748] 5. Locker Reservation and Navigation

[0749] When the user selects a suggested locker, the device sends this selection to the server. The server reserves the locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the device. The device displays a reservation completion notification to the user and also launches a map application to navigate the user to the locker. For example, it displays information such as "Proceed to the East Exit area. It is on your right."

[0750] As described above, this system allows users to quickly and efficiently find the most suitable coin locker, making luggage storage in urban areas extremely convenient.

[0751] The processing flow will be explained below.

[0752] Step 1:

[0753] The device activates the GPS sensor to obtain the current latitude and longitude information, which is then sent to the server.

[0754] Step 2:

[0755] The server sends an API request to the coin locker management system at each station, receives real-time availability data returned from each management system, and stores it in a database.

[0756] Step 3:

[0757] The server obtains the user's current location and real-time availability data. Additionally, it also obtains past coin locker usage history data, weather data, current date and time, and user reviews and reputation information from the database.

[0758] Step 4:

[0759] The server inputs this data into an AI algorithm to calculate the suitability of each locker, which then identifies the coin locker that is best suited for the user.

[0760] Step 5:

[0761] The server sends information about the best coin locker to the terminal, which then visually displays the received information to the user.

[0762] Step 6:

[0763] The user selects a suggested locker on the device screen, and the device sends the user's selection information to the server.

[0764] Step 7:

[0765] The server reserves the selected locker and sends the reservation information to the locker management system. After receiving confirmation of the reservation, the server sends a notification to the terminal.

[0766] Step 8:

[0767] The device will notify the user that the reservation is complete and then launch the navigation function, which will launch the map application and display a route from the user's current location to the desired locker.

[0768] Step 9:

[0769] The device provides users with real-time information about directions and turns, such as "Please proceed to the East Exit area. It's on your right."

[0770] This will allow users to find the most suitable coin locker quickly and stress-free, even in complex city centers.

[0771] Example 1

[0772] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0773] As demand for coin lockers available around urban stations increases, users face the challenge of finding the most suitable locker quickly. In particular, since it is necessary to take into account numerous factors, such as the user's current location, real-time availability, past usage data, weather information, and user reviews, a system is needed that can comprehensively analyze these complex conditions in a short amount of time and suggest the most suitable locker.

[0774] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0775] In this invention, the server includes means for users to obtain location information, means for obtaining real-time availability data, means for predicting locker usage trends based on past data, means for comprehensively analyzing multiple factors, means for recommending the most suitable locker, means for presenting information to the user, means for the user to reserve a locker, means for providing the user with navigation information to the destination, means for comprehensively analyzing factors using an AI algorithm, and means for the server to send an API request to the locker management system and obtain real-time availability data. This allows users to quickly and efficiently find the most suitable coin locker, making it extremely convenient to store luggage in urban areas.

[0776] A "user" refers to someone who uses the system to search for a coin locker.

[0777] "Location information" refers to the latitude and longitude of a user's current location as determined using location measurement means such as GPS.

[0778] "Real-time availability data" refers to data that represents the current availability of coin lockers at each location.

[0779] "Historical data" refers to information showing the usage history and trends of coin lockers in the past.

[0780] "Multiple factors" refers to a variety of data, including user location information, real-time availability data, past usage data, weather information, and reviews.

[0781] "AI algorithm" refers to an algorithm that uses machine learning and artificial intelligence technology to analyze data and derive optimal results.

[0782] "API Request" means a request for data retrieval sent through an Application Program Interface (API).

[0783] A "locker management system" refers to a system that manages coin locker availability and reservation information.

[0784] "Reservation" refers to the process of making a specific coin locker available for use for a certain period of time.

[0785] "Navigation information" refers to information that includes routes and instructions for users to reach their destination (coin locker).

[0786] This invention provides a system that allows users to quickly find the best coin locker near an urban station. The system comprehensively analyzes the user's current location, real-time locker availability, past usage data, weather information, and multiple other factors to suggest the best coin locker for the user.

[0787] The system is implemented using the following hardware and software.

[0788] Hardware

[0789] Device: A mobile device such as a smartphone or tablet that is equipped with a GPS sensor and acquires the user's current location.

[0790] Server: A powerful computer system that runs databases and AI algorithms.

[0791] Locker management system: A system that manages the availability and reservation information of coin lockers installed at each station.

[0792] software

[0793] GPS function: Built into the device's operating system (OS) and obtains the user's location information.

[0794] API: Application Program Interface (API) for data exchange between the server and the locker management system.

[0795] AI algorithm: An algorithm that comprehensively analyzes data and selects the optimal locker. Specifically, it uses a machine learning model (e.g., a deep learning model).

[0796] System Operation

[0797] 1. Obtaining user location information

[0798] The device activates the GPS sensor and acquires the user's current location information (latitude and longitude). The acquired location information is then sent from the device to the server.

[0799] 2. Get real-time availability data

[0800] The server sends an API request to each station's coin locker management system to obtain real-time availability data for each locker, which is then stored in the server's database.

[0801] 3. AI-based selection of optimal lockers

[0802] The server inputs multiple factors, such as the user's location, real-time availability data, past usage data, weather information, user reviews, and luggage size, into an AI algorithm for comprehensive analysis, and the most suitable coin locker is selected as the result.

[0803] 4. Presentation of recommended results

[0804] The server sends information about the most suitable coin locker to the terminal, which displays the received information on its screen and suggests the most suitable coin locker to the user.

[0805] 5. Locker Reservation and Navigation

[0806] When the user selects a suggested locker, the terminal sends the information to the server. The server reserves the selected locker and receives confirmation of the reservation from the locker management system. The server then sends a reservation completion notification to the terminal, which notifies the user. In addition, the terminal provides the user with navigation information to the locker.

[0807] Specific examples

[0808] As a concrete example, let's consider the case where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage.

[0809] Obtaining user location information: The user's device activates the GPS sensor and obtains the current location (latitude 35.681236, longitude 139.767125). The device then sends this location information to the server.

[0810] Obtaining real-time availability data: The server sends an API request to Tokyo Station's coin locker management system to obtain availability data. For example, there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[0811] AI-based selection of the best locker: The server inputs the user's current location, real-time availability, past usage data, weather information, luggage size, and customer reviews into an AI model for comprehensive analysis. As a result, it determines that a locker in the East Exit area is the best option.

[0812] Presentation of recommended results: The server sends locker information for the East Exit area to the terminal, and the terminal displays to the user, "There are large-size coin lockers that are ideal for the East Exit area."

[0813] Locker reservation and navigation: When the user selects a suggested locker, the device sends this selection to the server. The server reserves the locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the device. The device displays a reservation completion notification to the user and also launches a map application to navigate the user to the locker. For example, it may display information such as "Proceed to the East Exit area. It is on your right."

[0814] Prompt Sentence Examples

[0815] Prompt: "I've arrived at Tokyo Station. My current location is latitude 35.681236, longitude 139.767125. Can you tell me the best coin locker location?"

[0816] As described above, this system allows users to quickly and efficiently find the most suitable coin locker, making luggage storage in urban areas extremely convenient.

[0817] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0818] Step 1:

[0819] Obtaining user location information

[0820] The device activates the GPS sensor and obtains the user's current location information (latitude and longitude). The obtained location information is sent from the device to the server. Specifically, the device's GPS function reads the current location, generates data in the format of latitude 35.681236, longitude 139.767125, and sends it to the server via an HTTP request. At this time, the input is the location data from the GPS sensor, and the output is the latitude and longitude data sent to the server.

[0821] Step 2:

[0822] Get real-time availability data

[0823] The server sends an API request to each station's coin locker management system to obtain real-time availability data. For example, the server sends a request like "GET / coinlocker / status?station=tokyo". The obtained data shows the real-time availability of each locker. The input is the API request, and the output is availability data that is saved in the server's database. Specifically, the data obtained is "10 available lockers in the east exit area and 5 available lockers in the west exit area" and stored in the server's database.

[0824] Step 3:

[0825] AI-based selection of optimal lockers

[0826] The server inputs multiple factors, such as the user's location, real-time availability data, past usage data, weather information, reviews, and luggage size, into an AI algorithm for comprehensive analysis. Specifically, this data is compiled into a single data frame and then input into a machine learning model. For example, data such as latitude 35.681236, longitude 139.767125, rain, and large suitcase are input. The AI ​​algorithm analyzes this data and selects the most suitable coin locker. The input is the user's location and other related data, and the output is the result that "lockers in the east exit area are optimal."

[0827] Step 4:

[0828] Providing recommended results

[0829] The server sends the selected information about the optimal coin locker to the terminal. The terminal displays the received information on the screen and makes suggestions to the user. The input is the optimal locker information sent from the server, and the output is a message displayed on the terminal screen saying, "There is an L-size coin locker that is optimal in the East Exit area." Specifically, the terminal receives an HTTP request and displays the information on the screen.

[0830] Step 5:

[0831] Locker reservation and navigation

[0832] When the user selects a suggested locker, the device sends this information to the server. The server then sends an API request to the locker management system to reserve the selected locker. For example, a request like "POST / locker / reserve?id=12345" is sent. The server receives confirmation of reservation completion from the locker management system. The server then sends a notification of reservation completion to the device, which then notifies the user. The device then provides the user with navigation information to the locker. The input is the user's selection information and a reservation completion notification, and the output is a notification from the device such as "Reservation completed" and navigation information. Specifically, the device launches a map application and displays a guide message saying, "Proceed to the east exit area. It is on your right."

[0833] (Application example 1)

[0834] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0835] In urban and congested areas, it is difficult for users to efficiently and quickly find the optimal facilities and services. In particular, food delivery services require the selection of the optimal delivery location or store, taking into account the user's location, weather, congestion, and other factors. Furthermore, there is no established system for navigating users to their destination after selection, which hinders convenience.

[0836] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0837] In this invention, the server includes means for users to acquire location information, means for acquiring real-time availability data, means for predicting usage trends based on past data, means for comprehensively analyzing multiple factors, means for recommending optimal facilities, means for presenting information to users, means for users to reserve facilities, means for providing users with navigation information to their destination, and means for acquiring congestion and operation status of various bases in real time and recommending optimal delivery bases. This enables users to efficiently and quickly find optimal delivery bases and stores, improving convenience.

[0838] "User location information" is data that indicates the user's current geographic location and is obtained using sensors such as GPS.

[0839] "Real-time availability data" refers to data that indicates the availability status of each facility or service in real time.

[0840] "Past data" refers to data that indicates past usage history and trends, and is used to predict future usage trends.

[0841] "Multiple factors" refers to the variety of information the system takes into account, such as user location information, availability data, historical data, weather information, and reviews.

[0842] "Comprehensive analysis" refers to a data processing method that combines multiple factors to derive optimal results.

[0843] "Optimal facilities" refers to facilities and services that are most suitable for users under specific conditions.

[0844] "Recommending" means that the system suggests the best option to the user based on the analysis results.

[0845] "Presenting information" means that the system visually displays the analysis results and recommendations to the user.

[0846] "Reserving facilities" refers to the process by which a user reserves selected facilities or services in advance through the system.

[0847] "Navigation information" refers to information that provides directions and instructions for a user to reach a destination.

[0848] "Delivery base" refers to a location for receiving and shipping food in food delivery.

[0849] "Crowding status" is information that indicates how crowded a particular location or facility is currently.

[0850] "Operation status" is information that indicates the current level of operation of a facility or base.

[0851] MODE FOR CARRYING OUT THE INVENTION

[0852] This invention is a system that allows users to efficiently find the optimal facilities and services (hereinafter referred to as "delivery locations") in congested areas such as urban areas. This system is particularly applicable to food delivery, and provides a function to recommend the optimal delivery location by comprehensively analyzing the user's current location, real-time congestion status of locations, past usage trends, weather information, word-of-mouth reviews, etc.

[0853] Program Generation

[0854] In a specific embodiment, the system operates in the following steps.

[0855] Hardware and software used

[0856] The main components of this system are as follows:

[0857] User device: A smartphone or tablet equipped with a GPS sensor. Examples include iPhone and Android devices.

[0858] Server: Processes and optimizes the data sent by the user. Examples: AWS EC2, Google Cloud Platform.

[0859] AI algorithms: Comprehensive analysis of multiple factors. Examples: TensorFlow, PyTorch.

[0860] Navigation API: Showing users directions to their destination. Example: Google Maps API.

[0861] Data processing and calculation

[0862] Obtaining user location information: The user's device obtains the latitude and longitude using the GPS sensor and sends it to the server. For example, if the user is currently in Tokyo, their exact location information will be obtained.

[0863] Obtaining real-time availability data: Data is obtained from an API that manages the congestion status and capacity of each delivery location on the server.

[0864] Comprehensive data analysis: The server inputs the user's location, real-time availability, past data, weather information, reviews, etc. into an AI algorithm to select the optimal delivery location.

[0865] Presentation of recommendation results: The selection results are sent to the user's device and the information is presented visually. For example, "The optimal delivery point is here."

[0866] Providing navigation information: Using the Google Maps API, route information to the user's selected location is provided.

[0867] Specific examples

[0868] When a user attempts to use food delivery at home, the smartphone obtains the user's current location and recommends the most suitable restaurant, taking into account that it is a rainy day. This system allows users to efficiently and quickly find the optimal delivery location. For example, if a user inputs, "I am looking for the best food delivery option at home. It is a rainy day, and there are three restaurants: A, B, and C. Please recommend the best delivery location based on the location and availability of each," the system will analyze all factors and recommend the optimal location.

[0869] Prompt Sentence Examples

[0870] "A user is looking for the best restaurant delivery service in their current location. It's a rainy day, and there are three restaurants: A, B, and C. Please recommend the best delivery location based on their location and availability."

[0871] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0872] Step 1:

[0873] The user device activates the GPS sensor and acquires the user's current location (latitude and longitude). The input data is the location information from the GPS sensor, and the output data is the latitude and longitude information recorded on the device. The acquired location information is sent from the device to the server.

[0874] Step 2:

[0875] The server sends a request to an API that manages the congestion and operation status of each delivery location, and obtains real-time availability data. The input data is the request information to the API, and the output data is the real-time congestion and capacity data obtained by the server. The obtained data is stored in the server's database.

[0876] Step 3:

[0877] The server retrieves past usage data, weather information, and review data from the database. The input data is a database query, and the output data is the retrieved past usage history, current weather information, and review data. These data are used in the next step.

[0878] Step 4:

[0879] The server inputs multiple factors, such as the user's current location, real-time availability data, past usage data, weather information, and reviews, into an AI algorithm for comprehensive analysis. This diverse information constitutes the input data, and the output data is the optimal delivery point calculated by the AI ​​algorithm. Prediction processing is performed using an AI model (TensorFlow or PyTorch) to process the data.

[0880] Step 5:

[0881] The server recommends the optimal delivery point to the user based on the analysis results of the AI ​​algorithm. The input data is the AI ​​analysis results, and the output data is the recommendation information sent to the user's device. The device displays the recommendation results on the screen and tells the user, "Here is the optimal delivery point."

[0882] Step 6:

[0883] When the user selects a suggested delivery location, the user terminal sends the information to the server. The input data is the user's selection information, and the output data is the selection information sent to the server. The server then confirms the order at the selected delivery location.

[0884] Step 7:

[0885] The server sends reservation and order confirmation information to the delivery base for confirmation. The input data is reservation and order information, and the output data is reservation confirmation information from the delivery base. The server obtains the confirmation information and notifies the user's terminal.

[0886] Step 8:

[0887] The user's device uses the Google Maps API to provide the user with navigation information to the optimal delivery location. The input data is the request information to the Google Maps API, and the output data is the navigation information. The device presents this information to the user and begins navigation.

[0888] By following these steps, users can efficiently and quickly find the optimal delivery location and use food delivery services.

[0889] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0890] This invention provides a system that allows users to quickly find the best coin locker near urban stations, and also has the function of recognizing the user's emotions and recommending the best locker based on that.The system recommends the best coin locker to the user by comprehensively analyzing the user's current location, real-time locker availability, past usage data, weather information, word-of-mouth and reputation information, and user emotional data.

[0891] The program of this system operates in the following steps:

[0892] Program Operation

[0893] 1. Obtaining user location information

[0894] The device activates the GPS sensor and acquires the user's current location information (latitude and longitude). The acquired location information is then sent from the device to the server.

[0895] 2. Get real-time availability data

[0896] The server sends an API request to each station's coin locker management system to obtain real-time availability data for each locker, which is then stored in the server's database.

[0897] 3. AI-based selection of optimal lockers

[0898] The server inputs multiple factors, such as the user's location information, real-time availability data, past usage data, weather data, reviews and reputation, and emotional data from an emotion engine, into an AI algorithm for comprehensive analysis, and the most suitable coin locker is selected as the result.

[0899] 4. Presentation of recommended results

[0900] The server sends information about the best coin locker to the terminal, which visually displays the received information to the user and suggests the best locker according to the user's emotional state.

[0901] 5. Locker Reservation and Navigation

[0902] When the user selects a suggested locker, the terminal sends the information to the server. The server reserves the selected locker and receives confirmation of the reservation from the locker management system. The server then sends a reservation completion notification to the terminal, which notifies the user. In addition, the terminal provides the user with navigation information to the locker.

[0903] Specific examples

[0904] Consider a case where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage.

[0905] 1. Obtaining user location information

[0906] The user's device activates the GPS sensor and obtains the current location (e.g., latitude 35.681236, longitude 139.767125). The device then sends this location information to the server.

[0907] 2. Get real-time availability data

[0908] The server sends an API request to the Tokyo Station coin locker management system to obtain availability data. For example, suppose there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[0909] 3. AI-based selection of optimal lockers

[0910] The server inputs the user's current location, real-time availability, past usage data (the West Exit area tends to be crowded at 5 p.m. on weekdays), weather information (rainy weather), luggage size (large suitcase), user reviews, and user sentiment data obtained from an emotion engine into an AI model for comprehensive analysis. As a result, it is determined that a locker in the East Exit area is the most suitable.

[0911] 4. Presentation of recommended results

[0912] The server sends locker information for the East Exit area to the device, which then displays to the user, "There are large coin lockers ideal for the East Exit area." If the user is nervous, the device will also display a message that reflects their emotions, such as, "Don't worry, you'll easily find a locker in the East Exit area."

[0913] 5. Locker Reservation and Navigation

[0914] When the user selects a suggested locker, the device sends this selection to the server. The server reserves the locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the device. The device displays a reservation completion notification to the user and also launches a map application to navigate the user to the locker. For example, the device may display information such as "Proceed to the East Exit area. It is on your right," and guidance is given in a tone that reflects the user's emotional state.

[0915] In this way, the system can recommend the most suitable coin locker based on the user's emotions, and further improve the user experience by adjusting the way information is presented and the navigation method.

[0916] The processing flow will be explained below.

[0917] Step 1:

[0918] The device activates the GPS sensor and obtains the user's current location information. For example, the location information obtained is 35.681236 latitude and 139.767125 longitude. The obtained location information is sent from the device to the server.

[0919] Step 2:

[0920] The server sends an API request to each station's coin locker management system. The server receives real-time availability data returned from each management system and stores it in the server's database. For example, suppose there are 10 available lockers in the east exit area and 5 available lockers in the west exit area.

[0921] Step 3:

[0922] The device uses the user's facial expressions and voice data to collect data to input into the emotion engine, which analyzes the user's current emotional state (e.g., tense, relaxed), and sends that data from the device to the server.

[0923] Step 4:

[0924] The server inputs the user's current location, real-time availability data, past usage data, weather data, user reviews and reputation information, and sentiment data into an AI algorithm, which then comprehensively analyzes this information and calculates the suitability of each locker.

[0925] Step 5:

[0926] The server identifies the most suitable coin locker and sends that information to the terminal. For example, it may determine that the most suitable large coin locker is located in the East Exit area.

[0927] Step 6:

[0928] The device displays the received locker information to the user. For example, it may notify the user that "there is a large-size coin locker that is perfect for you in the East Exit area." In addition, messages based on the user's emotional state may also be displayed. For example, if the user is nervous, the device may display a message saying, "Relax, you'll easily find a locker in the East Exit area."

[0929] Step 7:

[0930] The user selects a suggested locker on the device screen, and the device sends the selection information to the server.

[0931] Step 8:

[0932] The server reserves the selected locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the terminal.

[0933] Step 9:

[0934] The device will notify the user that the reservation is complete and then launch the navigation function, which will launch the map application and display a route from the user's current location to the desired locker.

[0935] Step 10:

[0936] The device provides users with real-time information about directions and turns. For example, it displays specific instructions such as, "Go to the East Exit area. It's on your right." The device also adjusts the tone of the instructions based on the user's emotions.

[0937] This series of processes enables users to quickly and stresslessly find the best coin locker even in complex urban stations. In addition, the emotion engine is used to provide appropriate responses and guidance to users.

[0938] Example 2

[0939] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0940] Conventional coin locker management systems have problems in that it takes a lot of time for users to find the best locker, and they lack support that responds to the user's individual needs and emotional state. In particular, around urban stations, where there are many users, it is difficult to grasp availability in real time, and accurate recommendations are often not possible. Furthermore, there is a risk that the user experience will be poor because the service does not sufficiently take into account external factors such as the user's emotions and weather.

[0941] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for acquiring location information from the user, a means for acquiring real-time availability data, a means for predicting locker usage trends based on past usage data, a means for comprehensively analyzing multiple elements (location information, availability data, past usage data, weather information, emotional data, and word-of-mouth / reputation information), a means for recommending the most suitable locker, a means for presenting visual and emotional information to the user, a means for the user to reserve a locker, and a means for providing navigation information to the user to their destination. This allows the user to quickly find the most suitable coin locker and enjoy services tailored to the user's individual needs and emotional state.

[0942] "User" refers to the entity that uses this system to find the most suitable coin locker.

[0943] "Location Information" refers to latitude and longitude data that indicates a user's current location.

[0944] "Real-time availability data" refers to data regarding the current usage status of coin lockers.

[0945] "Past usage data" refers to data showing the past usage history and trends of coin lockers.

[0946] "Weather Information" refers to data regarding current and future weather.

[0947] "Emotional Data" refers to data that indicates a user's current emotional state.

[0948] "Word of mouth and reputation information" refers to data including ratings and impressions from past users of the coin locker.

[0949] "AI algorithm" refers to artificial intelligence technology that comprehensively analyzes multiple factors such as user location information, real-time availability data, past usage data, weather information, emotional data, and word-of-mouth and reputation information.

[0950] "Means for recommending the most suitable locker" refers to a function that uses an AI algorithm to guide users to the coin locker that is most suitable for them.

[0951] "Means for presenting visually and emotionally relevant information" refers to the ability to display information to users in a visually accessible format and provide messages tailored to the user's emotional state.

[0952] "Means of reservation" refers to the function that allows a user to reserve a coin locker of their choice via the system.

[0953] "Means for providing navigation information" refers to a function that provides route guidance to help users reach their desired coin locker without any hassle.

[0954] This invention provides a system that allows users to quickly find the best coin locker near urban stations, and also has the function of recognizing the user's emotions and recommending the best locker based on that.The system recommends the best coin locker to the user by comprehensively analyzing the user's current location, real-time locker availability, past usage data, weather information, word-of-mouth and reputation information, and user emotional data.

[0955] To implement this system, the following hardware and software are required:

[0956] Hardware:

[0957] 1. Device: A smartphone or tablet held by a user. It has a built-in GPS sensor and can obtain current location information.

[0958] 2. Server: A server computer for data processing and analysis, including a database for sending API requests and receiving and storing various data.

[0959] software:

[0960] 1. GPS module: Software that controls the GPS sensor in the device and obtains current location information.

[0961] 2. API Handler: A server-side program, software for obtaining real-time availability data from the coin locker management system.

[0962] 3. Database system: A system for storing and managing various data within a server. Examples include MySQL and PostgreSQL.

[0963] 4. AI algorithm: Software that comprehensively analyzes multiple data to select the optimal coin locker. The generated model is often implemented in a language such as Python.

[0964] 5. Emotion engine: Software for analyzing user emotion data and sending the results to the server. For example, it uses an emotion analysis library.

[0965] 6. User Interface: An application that visually presents information to the user on a device. Frameworks such as React Native may be used.

[0966] Examples:

[0967] Consider a case where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage in. In this case, the system operates as follows:

[0968] 1. Obtaining location information: The user's device activates the GPS sensor and obtains the current location (latitude 35.681236, longitude 139.767125). The device then sends this location information to the server.

[0969] 2. Obtaining real-time availability data: The server sends an API request to Tokyo Station's coin locker management system to obtain availability data. For example, suppose there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[0970] 3. AI-based selection of the best locker: The server inputs the user's current location, real-time availability, past usage data, weather information, user reviews and reputation data, and user sentiment data obtained from an emotion engine into an AI model for comprehensive analysis. As a result, a locker in the East Exit area may be determined to be the best choice.

[0971] 4. Presentation of recommended results: The server sends locker information for the East Exit area to the terminal, which then displays to the user, "There are large-size coin lockers ideal for the East Exit area." If the user is nervous, the terminal also displays a message appropriate to their emotions, such as, "Don't worry, you'll easily find a locker in the East Exit area."

[0972] 5. Locker reservation and navigation: Once the user selects a suggested locker, the device sends this selection to the server. The server reserves the locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the device. The device displays a reservation completion notification to the user and also launches a map application to navigate the user to the locker. For example, it displays information such as "Proceed to the East Exit area. It is on your right."

[0973] Example prompt sentence:

[0974] "Write a natural language description of a system for quickly finding the best coin locker near an urban station. Include examples of each step: obtaining user location information, obtaining real-time availability data, using AI to select the best locker, providing recommendations, reserving the locker, and navigating. Finally, include how to respond if the user is nervous."

[0975] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0976] Step 1:

[0977] Obtaining user location information

[0978] Subject: Terminal

[0979] The device activates the GPS sensor and obtains the user's current location information (latitude and longitude). The input here is the GPS sensor data, and the output is the current location information. The device periodically obtains location information and sends the latest current location to the server. This location information is used in the next processing step.

[0980] Step 2:

[0981] Get real-time availability data

[0982] Subject: Server

[0983] The server sends an API request to the coin locker management system at each station to obtain real-time availability data for each locker. The input here is the API response from the locker management system, and the output is the availability data. The obtained data is stored in the server's database, and the data is used in the next processing step.

[0984] Step 3:

[0985] AI-based selection of optimal lockers

[0986] Subject: Server

[0987] The server inputs the following factors into an AI algorithm, which then performs a comprehensive analysis to select the most suitable coin locker:

[0988] Your location

[0989] Real-time availability data

[0990] Historical usage data

[0991] Weather information

[0992] Reviews and reputation information

[0993] Emotional Data

[0994] The input here is data on the multiple factors mentioned above, and the output is information on the most suitable coin locker. The AI ​​algorithm comprehensively analyzes the data and selects the locker that best suits the user's current needs.

[0995] Step 4:

[0996] Presentation of recommendation results

[0997] Subject: Server and Terminal

[0998] The server sends information about the best coin locker to the terminal. The input here is the locker data from the server, and the output is the information display on the user's terminal. The terminal presents this information visually to the user, and if necessary, displays further encouraging or guiding messages based on the emotion data.

[0999] Step 5:

[1000] Locker reservation and navigation

[1001] Subject: Server and Terminal

[1002] When the user selects a suggested locker, the device sends that information to the server. The input here is the user's selection information, and the output is reservation data for the locker management system. The server reserves the locker and notifies the device that the reservation is complete. The device displays a reservation completion notification to the user and also launches a map application to provide navigation information to the destination.

[1003] (Application example 2)

[1004] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1005] Conventional coin locker recommendation systems can take into account the user's current location, real-time availability data, past usage data, weather information, word-of-mouth reviews, and reputation information, but they lack the functionality to recommend the optimal locker by taking the user's emotional state into account.As a result, they are unable to provide detailed services based on the user's emotions and psychological state, and are unable to sufficiently improve the user experience, which is an issue.

[1006] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1007] In this invention, the server includes a means for obtaining location information from the user, a means for obtaining real-time availability data, a means for predicting locker usage trends based on past data, a means for comprehensively analyzing multiple factors, a means for recommending the most suitable locker, a means for presenting information to the user, a means for recognizing the user's emotional state and presenting information accordingly, a means for the user to reserve a locker, and a means for providing the user with navigation information to their destination. This makes it possible to recommend the most suitable locker and present effective information taking into account the user's emotional state.

[1008] "Means by which users obtain location information" refers to methods of identifying the user's current location using a GPS sensor or communication network, etc., and sending that information to a server.

[1009] "Means of obtaining real-time availability data" refers to methods such as API requests for obtaining availability data in real time from the coin locker management system.

[1010] "Means for predicting locker usage trends based on past data" refers to algorithms and databases that analyze past coin locker usage data and predict future usage trends.

[1011] The "means for comprehensively analyzing multiple factors" refers to an AI algorithm that comprehensively analyzes data obtained from multiple sources, such as the user's location information, real-time availability, past usage data, weather information, word-of-mouth and reputation information, and emotional data.

[1012] The "means for recommending the optimal locker" is an algorithm that recommends the coin locker location that is optimal for the user based on the results of comprehensive data analysis.

[1013] The "means of presenting information to the user" refers to a user interface that provides information on the most suitable coin locker on the user's device through screen display, voice, etc.

[1014] "Means for recognizing the user's emotional state and presenting information accordingly" refers to a system that recognizes the user's emotions using sensors or image analysis, and provides messages and recommended information according to that emotional state.

[1015] "Means for users to reserve a locker" refers to the procedures and system that allow users to remotely reserve a selected locker using a device such as a smartphone.

[1016] "Means for providing users with navigation information to their destination" refers to a map application or navigation system that provides directions from the user's current location to the selected coin locker.

[1017] The system of this invention is designed to help users quickly find the best coin locker near urban train stations. The system comprehensively analyzes the user's current location, real-time locker availability, past usage data, weather information, word-of-mouth and reputation information, and emotional data, and then recommends the best coin locker for the user.

[1018] First, the user's smartphone acquires location information (latitude and longitude) using the built-in GPS sensor and sends this information to the server. The server then makes an API request to the coin locker management system at each station to obtain real-time availability data and store it in a database.

[1019] The server then inputs the acquired user location information, real-time availability data, past usage data, weather information, user reviews and reputation, and emotion data acquired from an emotion recognition engine into an AI algorithm for comprehensive analysis. This AI algorithm is implemented using TensorFlow and PyTorch, for example. As a result of the analysis, the optimal coin locker is selected.

[1020] Information about the selected coin locker is sent from the server to the user's smartphone and displayed visually. Furthermore, messages are displayed according to the user's emotional state. For example, if the user is feeling nervous, a reassuring message such as "Remain calm, you'll find it in the designated location soon" will be displayed.

[1021] Once the user selects a suggested locker, the information is sent to the server, which then reserves the selected locker. Once the reservation is complete, a confirmation is sent to the user's smartphone. The user is also given navigation information via a map application, which guides them to the locker.

[1022] This system allows users to receive recommendations for the best coin lockers that take their emotional state into account, and allows for consistent reservation and navigation. A specific scenario is shown below.

[1023] Specific examples

[1024] Consider a situation where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage.

[1025] Step 1: Get the user's location

[1026] The user's smartphone activates the GPS sensor and acquires the current location (e.g., latitude 35.681236, longitude 139.767125). The location information is sent to the server.

[1027] Step 2: Get real-time availability data

[1028] The server sends an API request to the Tokyo Station coin locker management system to obtain availability data. For example, suppose there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[1029] Step 3: AI-based selection of optimal lockers

[1030] The server inputs and analyzes the current location, real-time availability, past usage data (the West Exit area tends to be crowded at 5 PM on weekdays), weather information (rainy weather), luggage size (large suitcase), user reviews, and sentiment data into an AI model. As a result, it determines that a locker in the East Exit area is the best option.

[1031] Step 4: Providing recommendations

[1032] The server sends locker information for the East Exit area to the smartphone, and the message "There are large coin lockers perfect for the East Exit area" is displayed. If the user is nervous, the message "Don't worry, you'll find it in the designated location soon" is also displayed.

[1033] Step 5: Locker reservation and navigation

[1034] Once the user selects a suggested locker, the smartphone sends this selection to the server, which reserves the locker and retrieves the reservation information. The smartphone then displays a reservation completion notification and launches a map application to provide navigation information, such as "Proceed to the East Exit area. It's on your right."

[1035] Prompt Sentence Examples

[1036] "The user is located in Chuo Ward, Tokyo, and is looking for the best coin locker to store his luggage. It's currently 5 PM, it's raining, and the user is feeling a bit nervous. Based on past data, the West Exit area tends to be crowded around this time of day. Please suggest the best location for the coin locker and how to reserve it."

[1037] In this way, the system can recommend the most suitable coin locker based on the user's emotions, and further improve the user experience by adjusting the way information is presented and the navigation method.

[1038] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1039] Step 1:

[1040] The user's device activates the GPS sensor and acquires current location information (latitude and longitude). The acquired location information is sent to the server. The input is location information from the GPS sensor, and the output is the current location data sent to the server. Specifically, the user's smartphone acquires the current location and generates data such as latitude 35.681236 and longitude 139.767125.

[1041] Step 2:

[1042] The server sends an API request to the coin locker management system at each station to obtain real-time availability data. The input is the API request to the coin locker management system at each station, and the output is availability data. The data obtained by the server is saved in the server's database. Specifically, the server returns the availability of 10 lockers in the east exit area and 5 lockers in the west exit area.

[1043] Step 3:

[1044] The server collects and centralizes past usage data, weather information, reviews, and user sentiment data. The input is data from the server's database and external APIs, and the output is integrated analytical data. Specifically, it collects past weekday usage trends, current weather (rainy weather), review ratings, and sentiment data from an emotion recognition engine.

[1045] Step 4:

[1046] The server inputs location information, availability, past data, weather, reviews, and sentiment data into the AI ​​model, and performs an analysis to select the most suitable locker. The input is all collected data, and the output is the selection result of the most suitable locker. Specifically, the AI ​​model performs a comprehensive analysis and recommends the most suitable locker in the East Exit area for the user.

[1047] Step 5:

[1048] The server sends information about the optimal locker it has selected to the terminal. The terminal then visually displays the received information to the user. The input is the locker information selection result by the AI ​​model, and the output is the information displayed to the user. Specifically, the terminal displays, "There is an L-size coin locker that is ideal for the East Exit area." It also displays messages according to the user's emotional state. For example, if the user is nervous, a reassuring message will be displayed saying, "Remain calm, you will soon find it in the designated location."

[1049] Step 6:

[1050] When the user selects a suggested locker, the information is sent from the terminal to the server, which then reserves the selected locker. The input is the user's selection information, and the output is confirmation of the locker reservation. Specifically, the server sends the reservation information to the locker management system, and the reservation is completed.

[1051] Step 7:

[1052] Once the reservation is complete, the server notifies the user's device of the confirmation. The device then uses a map application to provide navigation information to the user. The input is reservation confirmation information, and the output is navigation information. Specifically, the device displays route guidance such as "Proceed to the East Exit area. It's on your right."

[1053] This series of processes allows users to use coin lockers quickly and optimally while taking into consideration their emotional state.

[1054] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1055] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1056] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1057] [Fourth embodiment]

[1058] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1059] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1060] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1061] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1062] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1063] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1064] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1065] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1066] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1067] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1068] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1069] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1070] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1071] This invention provides a system that allows users to quickly find the best coin locker near an urban station. The system comprehensively analyzes the user's current location, real-time locker availability, past usage data, weather information, and multiple other factors to suggest the best coin locker for the user.

[1072] The program of this system operates in the following steps:

[1073] Program Operation

[1074] 1. Obtaining user location information

[1075] The device activates the GPS sensor and acquires the user's current location information (latitude and longitude). The acquired location information is then sent from the device to the server.

[1076] 2. Get real-time availability data

[1077] The server sends an API request to each station's coin locker management system to obtain real-time availability data for each locker, which is then stored in the server's database.

[1078] 3. AI-based selection of optimal lockers

[1079] The server inputs multiple factors, such as the user's location, real-time availability data, past usage data, weather information, user reviews, and luggage size, into an AI algorithm for comprehensive analysis, and the most suitable coin locker is selected as the result.

[1080] 4. Presentation of recommended results

[1081] The server sends information about the most suitable coin locker to the terminal, which displays the received information on its screen and suggests the most suitable coin locker to the user.

[1082] 5. Locker Reservation and Navigation

[1083] When the user selects a suggested locker, the terminal sends the information to the server. The server reserves the selected locker and receives confirmation of the reservation from the locker management system. The server then sends a reservation completion notification to the terminal, which notifies the user. In addition, the terminal provides the user with navigation information to the locker.

[1084] Specific examples

[1085] Consider a case where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage.

[1086] 1. Obtaining user location information

[1087] The user's device activates the GPS sensor and obtains the current location (e.g., latitude 35.681236, longitude 139.767125). The device then sends this location information to the server.

[1088] 2. Get real-time availability data

[1089] The server sends an API request to the Tokyo Station coin locker management system to obtain availability data. For example, suppose there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[1090] 3. AI-based selection of optimal lockers

[1091] The server inputs the user's current location, real-time availability, past usage data (the West Exit area tends to be crowded at 5 p.m. on weekdays), weather information (rainy weather), luggage size (large suitcase), and user reviews into an AI model for comprehensive analysis. As a result, it is determined that a locker in the East Exit area is the most suitable.

[1092] 4. Presentation of recommended results

[1093] The server sends locker information for the east exit area to the terminal, and the terminal displays to the user, "There are large-size coin lockers that are ideal for the east exit area."

[1094] 5. Locker Reservation and Navigation

[1095] When the user selects a suggested locker, the device sends this selection to the server. The server reserves the locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the device. The device displays a reservation completion notification to the user and also launches a map application to navigate the user to the locker. For example, it displays information such as "Proceed to the East Exit area. It is on your right."

[1096] As described above, this system allows users to quickly and efficiently find the most suitable coin locker, making luggage storage in urban areas extremely convenient.

[1097] The processing flow will be explained below.

[1098] Step 1:

[1099] The device activates the GPS sensor to obtain the current latitude and longitude information, which is then sent to the server.

[1100] Step 2:

[1101] The server sends an API request to the coin locker management system at each station, receives real-time availability data returned from each management system, and stores it in a database.

[1102] Step 3:

[1103] The server obtains the user's current location and real-time availability data. Additionally, it also obtains past coin locker usage history data, weather data, current date and time, and user reviews and reputation information from the database.

[1104] Step 4:

[1105] The server inputs this data into an AI algorithm to calculate the suitability of each locker, which then identifies the coin locker that is best suited for the user.

[1106] Step 5:

[1107] The server sends information about the best coin locker to the terminal, which then visually displays the received information to the user.

[1108] Step 6:

[1109] The user selects a suggested locker on the device screen, and the device sends the user's selection information to the server.

[1110] Step 7:

[1111] The server reserves the selected locker and sends the reservation information to the locker management system. After receiving confirmation of the reservation, the server sends a notification to the terminal.

[1112] Step 8:

[1113] The device will notify the user that the reservation is complete and then launch the navigation function, which will launch the map application and display a route from the user's current location to the desired locker.

[1114] Step 9:

[1115] The device provides users with real-time information about directions and turns, such as "Please proceed to the East Exit area. It's on your right."

[1116] This will allow users to find the most suitable coin locker quickly and stress-free, even in complex city centers.

[1117] Example 1

[1118] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1119] As demand for coin lockers available around urban stations increases, users face the challenge of finding the most suitable locker quickly. In particular, since it is necessary to take into account numerous factors, such as the user's current location, real-time availability, past usage data, weather information, and user reviews, a system is needed that can comprehensively analyze these complex conditions in a short amount of time and suggest the most suitable locker.

[1120] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1121] In this invention, the server includes means for users to obtain location information, means for obtaining real-time availability data, means for predicting locker usage trends based on past data, means for comprehensively analyzing multiple factors, means for recommending the most suitable locker, means for presenting information to the user, means for the user to reserve a locker, means for providing the user with navigation information to the destination, means for comprehensively analyzing factors using an AI algorithm, and means for the server to send an API request to the locker management system and obtain real-time availability data. This allows users to quickly and efficiently find the most suitable coin locker, making it extremely convenient to store luggage in urban areas.

[1122] A "user" refers to someone who uses the system to search for a coin locker.

[1123] "Location information" refers to the latitude and longitude of a user's current location as determined using location measurement means such as GPS.

[1124] "Real-time availability data" refers to data that represents the current availability of coin lockers at each location.

[1125] "Historical data" refers to information showing the usage history and trends of coin lockers in the past.

[1126] "Multiple factors" refers to a variety of data, including user location information, real-time availability data, past usage data, weather information, and reviews.

[1127] "AI algorithm" refers to an algorithm that uses machine learning and artificial intelligence technology to analyze data and derive optimal results.

[1128] "API Request" means a request for data retrieval sent through an Application Program Interface (API).

[1129] A "locker management system" refers to a system that manages coin locker availability and reservation information.

[1130] "Reservation" refers to the process of making a specific coin locker available for use for a certain period of time.

[1131] "Navigation information" refers to information that includes routes and instructions for users to reach their destination (coin locker).

[1132] This invention provides a system that allows users to quickly find the best coin locker near an urban station. The system comprehensively analyzes the user's current location, real-time locker availability, past usage data, weather information, and multiple other factors to suggest the best coin locker for the user.

[1133] The system is implemented using the following hardware and software.

[1134] Hardware

[1135] Device: A mobile device such as a smartphone or tablet that is equipped with a GPS sensor and acquires the user's current location.

[1136] Server: A powerful computer system that runs databases and AI algorithms.

[1137] Locker management system: A system that manages the availability and reservation information of coin lockers installed at each station.

[1138] software

[1139] GPS function: Built into the device's operating system (OS) and obtains the user's location information.

[1140] API: Application Program Interface (API) for data exchange between the server and the locker management system.

[1141] AI algorithm: An algorithm that comprehensively analyzes data and selects the optimal locker. Specifically, it uses a machine learning model (e.g., a deep learning model).

[1142] System Operation

[1143] 1. Obtaining user location information

[1144] The device activates the GPS sensor and acquires the user's current location information (latitude and longitude). The acquired location information is then sent from the device to the server.

[1145] 2. Get real-time availability data

[1146] The server sends an API request to each station's coin locker management system to obtain real-time availability data for each locker, which is then stored in the server's database.

[1147] 3. AI-based selection of optimal lockers

[1148] The server inputs multiple factors, such as the user's location, real-time availability data, past usage data, weather information, user reviews, and luggage size, into an AI algorithm for comprehensive analysis, and the most suitable coin locker is selected as the result.

[1149] 4. Presentation of recommended results

[1150] The server sends information about the most suitable coin locker to the terminal, which displays the received information on its screen and suggests the most suitable coin locker to the user.

[1151] 5. Locker Reservation and Navigation

[1152] When the user selects a suggested locker, the terminal sends the information to the server. The server reserves the selected locker and receives confirmation of the reservation from the locker management system. The server then sends a reservation completion notification to the terminal, which notifies the user. In addition, the terminal provides the user with navigation information to the locker.

[1153] Specific examples

[1154] As a concrete example, let's consider the case where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage.

[1155] Obtaining user location information: The user's device activates the GPS sensor and obtains the current location (latitude 35.681236, longitude 139.767125). The device then sends this location information to the server.

[1156] Obtaining real-time availability data: The server sends an API request to Tokyo Station's coin locker management system to obtain availability data. For example, there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[1157] AI-based selection of the best locker: The server inputs the user's current location, real-time availability, past usage data, weather information, luggage size, and customer reviews into an AI model for comprehensive analysis. As a result, it determines that a locker in the East Exit area is the best option.

[1158] Presentation of recommended results: The server sends locker information for the East Exit area to the terminal, and the terminal displays to the user, "There are large-size coin lockers that are ideal for the East Exit area."

[1159] Locker reservation and navigation: When the user selects a suggested locker, the device sends this selection to the server. The server reserves the locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the device. The device displays a reservation completion notification to the user and also launches a map application to navigate the user to the locker. For example, it may display information such as "Proceed to the East Exit area. It is on your right."

[1160] Prompt Sentence Examples

[1161] Prompt: "I've arrived at Tokyo Station. My current location is latitude 35.681236, longitude 139.767125. Can you tell me the best coin locker location?"

[1162] As described above, this system allows users to quickly and efficiently find the most suitable coin locker, making luggage storage in urban areas extremely convenient.

[1163] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1164] Step 1:

[1165] Obtaining user location information

[1166] The device activates the GPS sensor and obtains the user's current location information (latitude and longitude). The obtained location information is sent from the device to the server. Specifically, the device's GPS function reads the current location, generates data in the format of latitude 35.681236, longitude 139.767125, and sends it to the server via an HTTP request. At this time, the input is the location data from the GPS sensor, and the output is the latitude and longitude data sent to the server.

[1167] Step 2:

[1168] Get real-time availability data

[1169] The server sends an API request to each station's coin locker management system to obtain real-time availability data. For example, the server sends a request like "GET / coinlocker / status?station=tokyo". The obtained data shows the real-time availability of each locker. The input is the API request, and the output is availability data that is saved in the server's database. Specifically, the data obtained is "10 available lockers in the east exit area and 5 available lockers in the west exit area" and stored in the server's database.

[1170] Step 3:

[1171] AI-based selection of optimal lockers

[1172] The server inputs multiple factors, such as the user's location, real-time availability data, past usage data, weather information, reviews, and luggage size, into an AI algorithm for comprehensive analysis. Specifically, this data is compiled into a single data frame and then input into a machine learning model. For example, data such as latitude 35.681236, longitude 139.767125, rain, and large suitcase are input. The AI ​​algorithm analyzes this data and selects the most suitable coin locker. The input is the user's location and other related data, and the output is the result that "lockers in the east exit area are optimal."

[1173] Step 4:

[1174] Providing recommended results

[1175] The server sends the selected information about the optimal coin locker to the terminal. The terminal displays the received information on the screen and makes suggestions to the user. The input is the optimal locker information sent from the server, and the output is a message displayed on the terminal screen saying, "There is an L-size coin locker that is optimal in the East Exit area." Specifically, the terminal receives an HTTP request and displays the information on the screen.

[1176] Step 5:

[1177] Locker reservation and navigation

[1178] When the user selects a suggested locker, the device sends this information to the server. The server then sends an API request to the locker management system to reserve the selected locker. For example, a request like "POST / locker / reserve?id=12345" is sent. The server receives confirmation of reservation completion from the locker management system. The server then sends a notification of reservation completion to the device, which then notifies the user. The device then provides the user with navigation information to the locker. The input is the user's selection information and a reservation completion notification, and the output is a notification from the device such as "Reservation completed" and navigation information. Specifically, the device launches a map application and displays a guide message saying, "Proceed to the east exit area. It is on your right."

[1179] (Application example 1)

[1180] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1181] In urban and congested areas, it is difficult for users to efficiently and quickly find the optimal facilities and services. In particular, food delivery services require the selection of the optimal delivery location or store, taking into account the user's location, weather, congestion, and other factors. Furthermore, there is no established system for navigating users to their destination after selection, which hinders convenience.

[1182] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1183] In this invention, the server includes means for users to acquire location information, means for acquiring real-time availability data, means for predicting usage trends based on past data, means for comprehensively analyzing multiple factors, means for recommending optimal facilities, means for presenting information to users, means for users to reserve facilities, means for providing users with navigation information to their destination, and means for acquiring congestion and operation status of various bases in real time and recommending optimal delivery bases. This enables users to efficiently and quickly find optimal delivery bases and stores, improving convenience.

[1184] "User location information" is data that indicates the user's current geographic location and is obtained using sensors such as GPS.

[1185] "Real-time availability data" refers to data that indicates the availability status of each facility or service in real time.

[1186] "Past data" refers to data that indicates past usage history and trends, and is used to predict future usage trends.

[1187] "Multiple factors" refers to the variety of information the system takes into account, such as user location information, availability data, historical data, weather information, and reviews.

[1188] "Comprehensive analysis" refers to a data processing method that combines multiple factors to derive optimal results.

[1189] "Optimal facilities" refers to facilities and services that are most suitable for users under specific conditions.

[1190] "Recommending" means that the system suggests the best option to the user based on the analysis results.

[1191] "Presenting information" means that the system visually displays the analysis results and recommendations to the user.

[1192] "Reserving facilities" refers to the process by which a user reserves selected facilities or services in advance through the system.

[1193] "Navigation information" refers to information that provides directions and instructions for a user to reach a destination.

[1194] "Delivery base" refers to a location for receiving and shipping food in food delivery.

[1195] "Crowding status" is information that indicates how crowded a particular location or facility is currently.

[1196] "Operation status" is information that indicates the current level of operation of a facility or base.

[1197] MODE FOR CARRYING OUT THE INVENTION

[1198] This invention is a system that allows users to efficiently find the optimal facilities and services (hereinafter referred to as "delivery locations") in congested areas such as urban areas. This system is particularly applicable to food delivery, and provides a function to recommend the optimal delivery location by comprehensively analyzing the user's current location, real-time congestion status of locations, past usage trends, weather information, word-of-mouth reviews, etc.

[1199] Program Generation

[1200] In a specific embodiment, the system operates in the following steps.

[1201] Hardware and software used

[1202] The main components of this system are as follows:

[1203] User device: A smartphone or tablet equipped with a GPS sensor. Examples include iPhone and Android devices.

[1204] Server: Processes and optimizes the data sent by the user. Examples: AWS EC2, Google Cloud Platform.

[1205] AI algorithms: Comprehensive analysis of multiple factors. Examples: TensorFlow, PyTorch.

[1206] Navigation API: Showing users directions to their destination. Example: Google Maps API.

[1207] Data processing and calculation

[1208] Obtaining user location information: The user's device obtains the latitude and longitude using the GPS sensor and sends it to the server. For example, if the user is currently in Tokyo, their exact location information will be obtained.

[1209] Obtaining real-time availability data: Data is obtained from an API that manages the congestion status and capacity of each delivery location on the server.

[1210] Comprehensive data analysis: The server inputs the user's location, real-time availability, past data, weather information, reviews, etc. into an AI algorithm to select the optimal delivery location.

[1211] Presentation of recommendation results: The selection results are sent to the user's device and the information is presented visually. For example, "The optimal delivery point is here."

[1212] Providing navigation information: Using the Google Maps API, route information to the user's selected location is provided.

[1213] Specific examples

[1214] When a user attempts to use food delivery at home, the smartphone obtains the user's current location and recommends the most suitable restaurant, taking into account that it is a rainy day. This system allows users to efficiently and quickly find the optimal delivery location. For example, if a user inputs, "I am looking for the best food delivery option at home. It is a rainy day, and there are three restaurants: A, B, and C. Please recommend the best delivery location based on the location and availability of each," the system will analyze all factors and recommend the optimal location.

[1215] Prompt Sentence Examples

[1216] "A user is looking for the best restaurant delivery service in their current location. It's a rainy day, and there are three restaurants: A, B, and C. Please recommend the best delivery location based on their location and availability."

[1217] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1218] Step 1:

[1219] The user device activates the GPS sensor and acquires the user's current location (latitude and longitude). The input data is the location information from the GPS sensor, and the output data is the latitude and longitude information recorded on the device. The acquired location information is sent from the device to the server.

[1220] Step 2:

[1221] The server sends a request to an API that manages the congestion and operation status of each delivery location, and obtains real-time availability data. The input data is the request information to the API, and the output data is the real-time congestion and capacity data obtained by the server. The obtained data is stored in the server's database.

[1222] Step 3:

[1223] The server retrieves past usage data, weather information, and review data from the database. The input data is a database query, and the output data is the retrieved past usage history, current weather information, and review data. These data are used in the next step.

[1224] Step 4:

[1225] The server inputs multiple factors, such as the user's current location, real-time availability data, past usage data, weather information, and reviews, into an AI algorithm for comprehensive analysis. This diverse information constitutes the input data, and the output data is the optimal delivery point calculated by the AI ​​algorithm. Prediction processing is performed using an AI model (TensorFlow or PyTorch) to process the data.

[1226] Step 5:

[1227] The server recommends the optimal delivery point to the user based on the analysis results of the AI ​​algorithm. The input data is the AI ​​analysis results, and the output data is the recommendation information sent to the user's device. The device displays the recommendation results on the screen and tells the user, "Here is the optimal delivery point."

[1228] Step 6:

[1229] When the user selects a suggested delivery location, the user terminal sends the information to the server. The input data is the user's selection information, and the output data is the selection information sent to the server. The server then confirms the order at the selected delivery location.

[1230] Step 7:

[1231] The server sends reservation and order confirmation information to the delivery base for confirmation. The input data is reservation and order information, and the output data is reservation confirmation information from the delivery base. The server obtains the confirmation information and notifies the user's terminal.

[1232] Step 8:

[1233] The user's device uses the Google Maps API to provide the user with navigation information to the optimal delivery location. The input data is the request information to the Google Maps API, and the output data is the navigation information. The device presents this information to the user and begins navigation.

[1234] By following these steps, users can efficiently and quickly find the optimal delivery location and use food delivery services.

[1235] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1236] This invention provides a system that allows users to quickly find the best coin locker near urban stations, and also has the function of recognizing the user's emotions and recommending the best locker based on that.The system recommends the best coin locker to the user by comprehensively analyzing the user's current location, real-time locker availability, past usage data, weather information, word-of-mouth and reputation information, and user emotional data.

[1237] The program of this system operates in the following steps:

[1238] Program Operation

[1239] 1. Obtaining user location information

[1240] The device activates the GPS sensor and acquires the user's current location information (latitude and longitude). The acquired location information is then sent from the device to the server.

[1241] 2. Get real-time availability data

[1242] The server sends an API request to each station's coin locker management system to obtain real-time availability data for each locker, which is then stored in the server's database.

[1243] 3. AI-based selection of optimal lockers

[1244] The server inputs multiple factors, such as the user's location information, real-time availability data, past usage data, weather data, reviews and reputation, and emotional data from an emotion engine, into an AI algorithm for comprehensive analysis, and the most suitable coin locker is selected as the result.

[1245] 4. Presentation of recommended results

[1246] The server sends information about the best coin locker to the terminal, which visually displays the received information to the user and suggests the best locker according to the user's emotional state.

[1247] 5. Locker Reservation and Navigation

[1248] When the user selects a suggested locker, the terminal sends the information to the server. The server reserves the selected locker and receives confirmation of the reservation from the locker management system. The server then sends a reservation completion notification to the terminal, which notifies the user. In addition, the terminal provides the user with navigation information to the locker.

[1249] Specific examples

[1250] Consider a case where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage.

[1251] 1. Obtaining user location information

[1252] The user's device activates the GPS sensor and obtains the current location (e.g., latitude 35.681236, longitude 139.767125). The device then sends this location information to the server.

[1253] 2. Get real-time availability data

[1254] The server sends an API request to the Tokyo Station coin locker management system to obtain availability data. For example, suppose there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[1255] 3. AI-based selection of optimal lockers

[1256] The server inputs the user's current location, real-time availability, past usage data (the West Exit area tends to be crowded at 5 p.m. on weekdays), weather information (rainy weather), luggage size (large suitcase), user reviews, and user sentiment data obtained from an emotion engine into an AI model for comprehensive analysis. As a result, it is determined that a locker in the East Exit area is the most suitable.

[1257] 4. Presentation of recommended results

[1258] The server sends locker information for the East Exit area to the device, which then displays to the user, "There are large coin lockers ideal for the East Exit area." If the user is nervous, the device will also display a message that reflects their emotions, such as, "Don't worry, you'll easily find a locker in the East Exit area."

[1259] 5. Locker Reservation and Navigation

[1260] When the user selects a suggested locker, the device sends this selection to the server. The server reserves the locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the device. The device displays a reservation completion notification to the user and also launches a map application to navigate the user to the locker. For example, the device may display information such as "Proceed to the East Exit area. It is on your right," and guidance is given in a tone that reflects the user's emotional state.

[1261] In this way, the system can recommend the most suitable coin locker based on the user's emotions, and further improve the user experience by adjusting the way information is presented and the navigation method.

[1262] The processing flow will be explained below.

[1263] Step 1:

[1264] The device activates the GPS sensor and obtains the user's current location information. For example, the location information obtained is 35.681236 latitude and 139.767125 longitude. The obtained location information is sent from the device to the server.

[1265] Step 2:

[1266] The server sends an API request to each station's coin locker management system. The server receives real-time availability data returned from each management system and stores it in the server's database. For example, suppose there are 10 available lockers in the east exit area and 5 available lockers in the west exit area.

[1267] Step 3:

[1268] The device uses the user's facial expressions and voice data to collect data to input into the emotion engine, which analyzes the user's current emotional state (e.g., tense, relaxed), and sends that data from the device to the server.

[1269] Step 4:

[1270] The server inputs the user's current location, real-time availability data, past usage data, weather data, user reviews and reputation information, and sentiment data into an AI algorithm, which then comprehensively analyzes this information and calculates the suitability of each locker.

[1271] Step 5:

[1272] The server identifies the most suitable coin locker and sends that information to the terminal. For example, it may determine that the most suitable large coin locker is located in the East Exit area.

[1273] Step 6:

[1274] The device displays the received locker information to the user. For example, it may notify the user that "there is a large-size coin locker that is perfect for you in the East Exit area." In addition, messages based on the user's emotional state may also be displayed. For example, if the user is nervous, the device may display a message saying, "Relax, you'll easily find a locker in the East Exit area."

[1275] Step 7:

[1276] The user selects a suggested locker on the device screen, and the device sends the selection information to the server.

[1277] Step 8:

[1278] The server reserves the selected locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the terminal.

[1279] Step 9:

[1280] The device will notify the user that the reservation is complete and then launch the navigation function, which will launch the map application and display a route from the user's current location to the desired locker.

[1281] Step 10:

[1282] The device provides users with real-time information about directions and turns. For example, it displays specific instructions such as, "Go to the East Exit area. It's on your right." The device also adjusts the tone of the instructions based on the user's emotions.

[1283] This series of processes enables users to quickly and stresslessly find the best coin locker even in complex urban stations. In addition, the emotion engine is used to provide appropriate responses and guidance to users.

[1284] Example 2

[1285] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1286] Conventional coin locker management systems have problems in that it takes a lot of time for users to find the best locker, and they lack support that responds to the user's individual needs and emotional state. In particular, around urban stations, where there are many users, it is difficult to grasp availability in real time, and accurate recommendations are often not possible. Furthermore, there is a risk that the user experience will be poor because the service does not sufficiently take into account external factors such as the user's emotions and weather.

[1287] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for acquiring location information from the user, a means for acquiring real-time availability data, a means for predicting locker usage trends based on past usage data, a means for comprehensively analyzing multiple elements (location information, availability data, past usage data, weather information, emotional data, and word-of-mouth / reputation information), a means for recommending the most suitable locker, a means for presenting visual and emotional information to the user, a means for the user to reserve a locker, and a means for providing navigation information to the user to their destination. This allows the user to quickly find the most suitable coin locker and enjoy services tailored to the user's individual needs and emotional state.

[1288] "User" refers to the entity that uses this system to find the most suitable coin locker.

[1289] "Location Information" refers to latitude and longitude data that indicates a user's current location.

[1290] "Real-time availability data" refers to data regarding the current usage status of coin lockers.

[1291] "Past usage data" refers to data showing the past usage history and trends of coin lockers.

[1292] "Weather Information" refers to data regarding current and future weather.

[1293] "Emotional Data" refers to data that indicates a user's current emotional state.

[1294] "Word of mouth and reputation information" refers to data including ratings and impressions from past users of the coin locker.

[1295] "AI algorithm" refers to artificial intelligence technology that comprehensively analyzes multiple factors such as user location information, real-time availability data, past usage data, weather information, emotional data, and word-of-mouth and reputation information.

[1296] "Means for recommending the most suitable locker" refers to a function that uses an AI algorithm to guide users to the coin locker that is most suitable for them.

[1297] "Means for presenting visually and emotionally relevant information" refers to the ability to display information to users in a visually accessible format and provide messages tailored to the user's emotional state.

[1298] "Means of reservation" refers to the function that allows a user to reserve a coin locker of their choice via the system.

[1299] "Means for providing navigation information" refers to a function that provides route guidance to help users reach their desired coin locker without any hassle.

[1300] This invention provides a system that allows users to quickly find the best coin locker near urban stations, and also has the function of recognizing the user's emotions and recommending the best locker based on that.The system recommends the best coin locker to the user by comprehensively analyzing the user's current location, real-time locker availability, past usage data, weather information, word-of-mouth and reputation information, and user emotional data.

[1301] To implement this system, the following hardware and software are required:

[1302] Hardware:

[1303] 1. Device: A smartphone or tablet held by a user. It has a built-in GPS sensor and can obtain current location information.

[1304] 2. Server: A server computer for data processing and analysis, including a database for sending API requests and receiving and storing various data.

[1305] software:

[1306] 1. GPS module: Software that controls the GPS sensor in the device and obtains current location information.

[1307] 2. API Handler: A server-side program, software for obtaining real-time availability data from the coin locker management system.

[1308] 3. Database system: A system for storing and managing various data within a server. Examples include MySQL and PostgreSQL.

[1309] 4. AI algorithm: Software that comprehensively analyzes multiple data to select the optimal coin locker. The generated model is often implemented in a language such as Python.

[1310] 5. Emotion engine: Software for analyzing user emotion data and sending the results to the server. For example, it uses an emotion analysis library.

[1311] 6. User Interface: An application that visually presents information to the user on a device. Frameworks such as React Native may be used.

[1312] Examples:

[1313] Consider a case where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage in. In this case, the system operates as follows:

[1314] 1. Obtaining location information: The user's device activates the GPS sensor and obtains the current location (latitude 35.681236, longitude 139.767125). The device then sends this location information to the server.

[1315] 2. Obtaining real-time availability data: The server sends an API request to Tokyo Station's coin locker management system to obtain availability data. For example, suppose there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[1316] 3. AI-based selection of the best locker: The server inputs the user's current location, real-time availability, past usage data, weather information, user reviews and reputation data, and user sentiment data obtained from an emotion engine into an AI model for comprehensive analysis. As a result, a locker in the East Exit area may be determined to be the best choice.

[1317] 4. Presentation of recommended results: The server sends locker information for the East Exit area to the terminal, which then displays to the user, "There are large-size coin lockers ideal for the East Exit area." If the user is nervous, the terminal also displays a message appropriate to their emotions, such as, "Don't worry, you'll easily find a locker in the East Exit area."

[1318] 5. Locker reservation and navigation: Once the user selects a suggested locker, the device sends this selection to the server. The server reserves the locker and sends the reservation information to the locker management system. The server receives confirmation of the reservation and notifies the device. The device displays a reservation completion notification to the user and also launches a map application to navigate the user to the locker. For example, it displays information such as "Proceed to the East Exit area. It is on your right."

[1319] Example prompt sentence:

[1320] "Write a natural language description of a system for quickly finding the best coin locker near an urban station. Include examples of each step: obtaining user location information, obtaining real-time availability data, using AI to select the best locker, providing recommendations, reserving the locker, and navigating. Finally, include how to respond if the user is nervous."

[1321] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1322] Step 1:

[1323] Obtaining user location information

[1324] Subject: Terminal

[1325] The device activates the GPS sensor and obtains the user's current location information (latitude and longitude). The input here is the GPS sensor data, and the output is the current location information. The device periodically obtains location information and sends the latest current location to the server. This location information is used in the next processing step.

[1326] Step 2:

[1327] Get real-time availability data

[1328] Subject: Server

[1329] The server sends an API request to the coin locker management system at each station to obtain real-time availability data for each locker. The input here is the API response from the locker management system, and the output is the availability data. The obtained data is stored in the server's database, and the data is used in the next processing step.

[1330] Step 3:

[1331] AI-based selection of optimal lockers

[1332] Subject: Server

[1333] The server inputs the following factors into an AI algorithm, which then performs a comprehensive analysis to select the most suitable coin locker:

[1334] Your location

[1335] Real-time availability data

[1336] Historical usage data

[1337] Weather information

[1338] Reviews and reputation information

[1339] Emotional Data

[1340] The input here is data on the multiple factors mentioned above, and the output is information on the most suitable coin locker. The AI ​​algorithm comprehensively analyzes the data and selects the locker that best suits the user's current needs.

[1341] Step 4:

[1342] Presentation of recommendation results

[1343] Subject: Server and Terminal

[1344] The server sends information about the best coin locker to the terminal. The input here is the locker data from the server, and the output is the information display on the user's terminal. The terminal presents this information visually to the user, and if necessary, displays further encouraging or guiding messages based on the emotion data.

[1345] Step 5:

[1346] Locker reservation and navigation

[1347] Subject: Server and Terminal

[1348] When the user selects a suggested locker, the device sends that information to the server. The input here is the user's selection information, and the output is reservation data for the locker management system. The server reserves the locker and notifies the device that the reservation is complete. The device displays a reservation completion notification to the user and also launches a map application to provide navigation information to the destination.

[1349] (Application example 2)

[1350] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1351] Conventional coin locker recommendation systems can take into account the user's current location, real-time availability data, past usage data, weather information, word-of-mouth reviews, and reputation information, but they lack the functionality to recommend the optimal locker by taking the user's emotional state into account.As a result, they are unable to provide detailed services based on the user's emotions and psychological state, and are unable to sufficiently improve the user experience, which is an issue.

[1352] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1353] In this invention, the server includes a means for obtaining location information from the user, a means for obtaining real-time availability data, a means for predicting locker usage trends based on past data, a means for comprehensively analyzing multiple factors, a means for recommending the most suitable locker, a means for presenting information to the user, a means for recognizing the user's emotional state and presenting information accordingly, a means for the user to reserve a locker, and a means for providing the user with navigation information to their destination. This makes it possible to recommend the most suitable locker and present effective information taking into account the user's emotional state.

[1354] "Means by which users obtain location information" refers to methods of identifying the user's current location using a GPS sensor or communication network, etc., and sending that information to a server.

[1355] "Means of obtaining real-time availability data" refers to methods such as API requests for obtaining availability data in real time from the coin locker management system.

[1356] "Means for predicting locker usage trends based on past data" refers to algorithms and databases that analyze past coin locker usage data and predict future usage trends.

[1357] The "means for comprehensively analyzing multiple factors" refers to an AI algorithm that comprehensively analyzes data obtained from multiple sources, such as the user's location information, real-time availability, past usage data, weather information, word-of-mouth and reputation information, and emotional data.

[1358] The "means for recommending the optimal locker" is an algorithm that recommends the coin locker location that is optimal for the user based on the results of comprehensive data analysis.

[1359] The "means of presenting information to the user" refers to a user interface that provides information on the most suitable coin locker on the user's device through screen display, voice, etc.

[1360] "Means for recognizing the user's emotional state and presenting information accordingly" refers to a system that recognizes the user's emotions using sensors or image analysis, and provides messages and recommended information according to that emotional state.

[1361] "Means for users to reserve a locker" refers to the procedures and system that allow users to remotely reserve a selected locker using a device such as a smartphone.

[1362] "Means for providing users with navigation information to their destination" refers to a map application or navigation system that provides directions from the user's current location to the selected coin locker.

[1363] The system of this invention is designed to help users quickly find the best coin locker near urban train stations. The system comprehensively analyzes the user's current location, real-time locker availability, past usage data, weather information, word-of-mouth and reputation information, and emotional data, and then recommends the best coin locker for the user.

[1364] First, the user's smartphone acquires location information (latitude and longitude) using the built-in GPS sensor and sends this information to the server. The server then makes an API request to the coin locker management system at each station to obtain real-time availability data and store it in a database.

[1365] The server then inputs the acquired user location information, real-time availability data, past usage data, weather information, user reviews and reputation, and emotion data acquired from an emotion recognition engine into an AI algorithm for comprehensive analysis. This AI algorithm is implemented using TensorFlow and PyTorch, for example. As a result of the analysis, the optimal coin locker is selected.

[1366] Information about the selected coin locker is sent from the server to the user's smartphone and displayed visually. Furthermore, messages are displayed according to the user's emotional state. For example, if the user is feeling nervous, a reassuring message such as "Remain calm, you'll find it in the designated location soon" will be displayed.

[1367] Once the user selects a suggested locker, the information is sent to the server, which then reserves the selected locker. Once the reservation is complete, a confirmation is sent to the user's smartphone. The user is also given navigation information via a map application, which guides them to the locker.

[1368] This system allows users to receive recommendations for the best coin lockers that take their emotional state into account, and allows for consistent reservation and navigation. A specific scenario is shown below.

[1369] Specific examples

[1370] Consider a situation where a user arrives at Tokyo Station and is looking for a coin locker to store their luggage.

[1371] Step 1: Get the user's location

[1372] The user's smartphone activates the GPS sensor and acquires the current location (e.g., latitude 35.681236, longitude 139.767125). The location information is sent to the server.

[1373] Step 2: Get real-time availability data

[1374] The server sends an API request to the Tokyo Station coin locker management system to obtain availability data. For example, suppose there are 10 available lockers in the East Exit area and 5 available lockers in the West Exit area. This data is stored in the server's database.

[1375] Step 3: AI-based selection of optimal lockers

[1376] The server inputs and analyzes the current location, real-time availability, past usage data (the West Exit area tends to be crowded at 5 PM on weekdays), weather information (rainy weather), luggage size (large suitcase), user reviews, and sentiment data into an AI model. As a result, it determines that a locker in the East Exit area is the best option.

[1377] Step 4: Providing recommendations

[1378] The server sends locker information for the East Exit area to the smartphone, and the message "There are large coin lockers perfect for the East Exit area" is displayed. If the user is nervous, the message "Don't worry, you'll find it in the designated location soon" is also displayed.

[1379] Step 5: Locker reservation and navigation

[1380] Once the user selects a suggested locker, the smartphone sends this selection to the server, which reserves the locker and retrieves the reservation information. The smartphone then displays a reservation completion notification and launches a map application to provide navigation information, such as "Proceed to the East Exit area. It's on your right."

[1381] Prompt Sentence Examples

[1382] "The user is located in Chuo Ward, Tokyo, and is looking for the best coin locker to store his luggage. It's currently 5 PM, it's raining, and the user is feeling a bit nervous. Based on past data, the West Exit area tends to be crowded around this time of day. Please suggest the best location for the coin locker and how to reserve it."

[1383] In this way, the system can recommend the most suitable coin locker based on the user's emotions, and further improve the user experience by adjusting the way information is presented and the navigation method.

[1384] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1385] Step 1:

[1386] The user's device activates the GPS sensor and acquires current location information (latitude and longitude). The acquired location information is sent to the server. The input is location information from the GPS sensor, and the output is the current location data sent to the server. Specifically, the user's smartphone acquires the current location and generates data such as latitude 35.681236 and longitude 139.767125.

[1387] Step 2:

[1388] The server sends an API request to the coin locker management system at each station to obtain real-time availability data. The input is the API request to the coin locker management system at each station, and the output is availability data. The data obtained by the server is saved in the server's database. Specifically, the server returns the availability of 10 lockers in the east exit area and 5 lockers in the west exit area.

[1389] Step 3:

[1390] The server collects and centralizes past usage data, weather information, reviews, and user sentiment data. The input is data from the server's database and external APIs, and the output is integrated analytical data. Specifically, it collects past weekday usage trends, current weather (rainy weather), review ratings, and sentiment data from an emotion recognition engine.

[1391] Step 4:

[1392] The server inputs location information, availability, past data, weather, reviews, and sentiment data into the AI ​​model, and performs an analysis to select the most suitable locker. The input is all collected data, and the output is the selection result of the most suitable locker. Specifically, the AI ​​model performs a comprehensive analysis and recommends the most suitable locker in the East Exit area for the user.

[1393] Step 5:

[1394] The server sends information about the optimal locker it has selected to the terminal. The terminal then visually displays the received information to the user. The input is the locker information selection result by the AI ​​model, and the output is the information displayed to the user. Specifically, the terminal displays, "There is an L-size coin locker that is ideal for the East Exit area." It also displays messages according to the user's emotional state. For example, if the user is nervous, a reassuring message will be displayed saying, "Remain calm, you will soon find it in the designated location."

[1395] Step 6:

[1396] When the user selects a suggested locker, the information is sent from the terminal to the server, which then reserves the selected locker. The input is the user's selection information, and the output is confirmation of the locker reservation. Specifically, the server sends the reservation information to the locker management system, and the reservation is completed.

[1397] Step 7:

[1398] Once the reservation is complete, the server notifies the user's device of the confirmation. The device then uses a map application to provide navigation information to the user. The input is reservation confirmation information, and the output is navigation information. Specifically, the device displays route guidance such as "Proceed to the East Exit area. It's on your right."

[1399] This series of processes allows users to use coin lockers quickly and optimally while taking into consideration their emotional state.

[1400] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1401] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1402] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1403] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1404] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1405] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1406] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1407] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1408] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1409] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1410] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1411] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1412] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1413] 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.

[1414] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1415] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1416] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1417] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1418] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1419] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1420] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1421] The following is further disclosed regarding the above embodiment.

[1422] (Claim 1)

[1423] A means by which a user obtains location information;

[1424] a means of obtaining real-time availability data; and

[1425] A means of predicting locker usage trends based on past data, and

[1426] A means of comprehensively analyzing multiple elements,

[1427] A means of recommending the best locker;

[1428] a means for presenting information to a user;

[1429] A means for users to reserve lockers;

[1430] a means for providing a user with navigation information to a destination;

[1431] A system including:

[1432] (Claim 2)

[1433] The system of claim 1, further comprising means for obtaining weather information and incorporating it into the recommendation of the optimal locker.

[1434] (Claim 3)

[1435] The system of claim 1, further comprising means for acquiring word-of-mouth and reputation information and reflecting this information in recommending the most suitable locker.

[1436] "Example 1"

[1437] (Claim 1)

[1438] A means by which a user obtains location information;

[1439] a means of obtaining real-time availability data; and

[1440] A means of predicting locker usage trends based on past data, and

[1441] A means of comprehensively analyzing multiple elements,

[1442] A means of recommending the best locker;

[1443] a means for presenting information to a user;

[1444] A means for users to reserve lockers;

[1445] a means for providing a user with navigation information to a destination;

[1446] A means of comprehensively analyzing elements using AI algorithms,

[1447] A means for the server to send an API request to the locker management system to obtain real-time availability data;

[1448] A system including:

[1449] (Claim 2)

[1450] The system of claim 1, further comprising means for obtaining weather information and incorporating it into the recommendation of the optimal locker.

[1451] (Claim 3)

[1452] The system of claim 1, further comprising means for acquiring word-of-mouth and reputation information and reflecting this information in recommending the most suitable locker.

[1453] "Application Example 1"

[1454] (Claim 1)

[1455] A means by which a user obtains location information;

[1456] a means of obtaining real-time availability data; and

[1457] A means of predicting usage trends based on past data;

[1458] A means of comprehensively analyzing multiple elements,

[1459] A means of recommending the most suitable equipment;

[1460] a means for presenting information to a user;

[1461] a means for users to reserve facilities;

[1462] a means for providing a user with navigation information to a destination;

[1463] A system including:

[1464] (Claim 2)

[1465] The system according to claim 1, further comprising means for acquiring weather information and incorporating it into the recommendation of optimal facilities.

[1466] (Claim 3)

[1467] The system according to claim 1, further comprising means for acquiring word-of-mouth and reputation information and reflecting the information in recommending optimal facilities.

[1468] (Claim 4)

[1469] The system according to claim 1, further comprising means for obtaining real-time information on congestion and operation status of various bases and recommending the most suitable delivery base.

[1470] "Example 2: Combining Emotion Engines"

[1471] (Claim 1)

[1472] A means by which a user obtains location information;

[1473] a means of obtaining real-time availability data; and

[1474] A means of predicting locker usage trends based on past usage data, and

[1475] A means of comprehensively analyzing multiple factors (location information, availability data, past usage data, weather information, emotional data, word-of-mouth and reputation information),

[1476] A means of recommending the best locker;

[1477] a means for presenting visual and emotional information to a user;

[1478] A means for users to reserve lockers;

[1479] a means for providing a user with navigation information to a destination;

[1480] A system including:

[1481] (Claim 2)

[1482] The system of claim 1, further comprising means for obtaining weather information and incorporating it into the recommendation of the optimal locker.

[1483] (Claim 3)

[1484] The system of claim 1, further comprising means for acquiring word-of-mouth and reputation information and reflecting this information in recommending the most suitable locker.

[1485] "Application example 2 when combining emotion engines"

[1486] (Claim 1)

[1487] A means by which a user obtains location information;

[1488] a means of obtaining real-time availability data; and

[1489] A means of predicting locker usage trends based on past data, and

[1490] A means of comprehensively analyzing multiple elements,

[1491] A means of recommending the best locker;

[1492] a means for presenting information to a user;

[1493] a means for recognizing a user's emotional state and presenting information accordingly;

[1494] A means for users to reserve lockers;

[1495] a means for providing a user with navigation information to a destination;

[1496] A system including:

[1497] (Claim 2)

[1498] The system of claim 1, further comprising means for obtaining weather information and incorporating it into the recommendation of the optimal locker.

[1499] (Claim 3)

[1500] The system of claim 1, further comprising means for acquiring word-of-mouth and reputation information and reflecting this information in recommending the most suitable locker. [Explanation of symbols]

[1501] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means by which a user obtains location information; a means of obtaining real-time availability data; and A means of predicting locker usage trends based on past data, and A means of comprehensively analyzing multiple elements, A means of recommending the best locker; a means for presenting information to a user; A means for users to reserve lockers; a means for providing a user with navigation information to a destination; A system including:

2. The system according to claim 1, further comprising means for acquiring weather information and incorporating it into the recommendation of the most suitable locker.

3. The system according to claim 1, further comprising means for acquiring word-of-mouth and reputation information and reflecting this information in recommending the most suitable locker.

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