System

Abstract

A system is provided.SOLUTION: The system includes means for inputting population information of a target area, means for inputting an age distribution of the target area, means for inputting information on an existing transportation operator, means for storing or updating the input information in a database, means for analyzing the population information and the age distribution stored in the database, means for analyzing information on the transportation operator stored in the database, means for calculating an appropriate fee based on the analysis result, and means for generating and presenting a detailed report on the appropriate fee.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] When introducing autonomous buses, it is important to set optimal fares for each region. However, it is difficult to set fares that fully take into account the population structure and the operating conditions of existing transportation operators. In particular, detailed data analysis is required to set fares appropriate for specific age groups, such as areas with a large elderly population or areas with a large young population. Another challenge is to set efficient operating routes and fare systems that avoid competition and overlap with existing public transportation services. [Means for solving the problem]

[0005] The present invention provides a system that collects and analyzes information on the population, age distribution, and existing transportation operators of a target area, and sets appropriate fares.

[0006] The present invention provides a system that includes a means for inputting population information for a target area, a means for inputting the age distribution of the target area, a means for inputting information about existing transportation operators, a means for saving or updating the input information in a database, a means for analyzing the population information and age distribution saved in the database, a means for analyzing information about transportation operators saved in the database, a means for calculating fair fares based on the analysis results, and a means for generating and presenting a detailed report on fair fares. The system further includes a means for setting differentiated fares for specific age groups based on the population information and age distribution, and a means for using a geographic information system (GIS) in analyzing information about transportation operators. This enables optimal fare setting that takes into account regional characteristics, resulting in efficient and competitive autonomous bus operations.

[0007] "Demographic information for a target area" means the total number of residents in a particular geographic area and their breakdown (age, gender, occupation, etc.).

[0008] "Age distribution" means information that indicates the proportion or number of people in each age group within a particular population.

[0009] "Information about existing transport operators" means detailed data about public transport operators already operating in a particular area, their operation status, pricing structures, ridership and routes.

[0010] "Database" means a collection of electronic information that is systematically organized so that the collected information can be efficiently stored, managed, searched, and analyzed.

[0011] "Means for analyzing demographic information and age distribution" means methods or techniques for analyzing data based on the population and its age structure of a target area to identify specific trends or characteristics.

[0012] "Means for analyzing information on transportation operators" means methods or technologies for analyzing operation data and fare information of existing transportation operators and evaluating the efficiency of operation routes and the appropriateness of fares, etc.

[0013] "Fair fare" means a fair and reasonable bus fare that takes into account the demographics and existing traffic conditions of the target area.

[0014] "Means for calculating fair fares" means a method or technology for calculating the most appropriate bus fare based on the collected and analyzed data.

[0015] "Means for generating and presenting a detailed report of fair rates" means a method or technology that organizes information about the calculated fair rates and displays or outputs it in an easy-to-understand format.

[0016] "Geographic Information System (GIS)" means any system or technology for inputting, storing, analyzing, and displaying geographic data. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] This invention relates to a system that collects and analyzes information on the population, age distribution, and existing transportation operators of a target area, and then sets appropriate fares. This system is realized through the interaction of a server, terminals, and users.

[0039] System configuration and operation

[0040] 1. Data collection and input

[0041] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs data for Machida City and presses the send button, sending this information to the server. The terminal then formats the input information and sends it to the server as data.

[0042] 2. Updating the database

[0043] The server validates the data received from the device and stores or updates it in its internal database. After receiving the data, the server validates its format, connects to the database, and updates existing information or inserts new data.

[0044] 3. Demographic and Age Data Analysis

[0045] The server analyzes the population distribution and age structure of the target area. The server retrieves population data from the database and analyzes this data using analytical tools such as Python's Pandas. For example, it performs a statistical analysis to determine that Machida City has a large elderly population and that the elderly make up 30% of the total population.

[0046] 4. Analysis of existing bus operator information

[0047] The server analyzes the routes, fare structures, and ridership numbers of existing transport operators. The server retrieves bus operator information from a database and evaluates trends in routes and ridership numbers using a geographic information system (GIS) and other analytical tools.

[0048] 5. Calculating the appropriate fee

[0049] The server calculates the appropriate fare based on the analysis results. For example, it might set a fare of 200 yen for seniors and 300 yen for general users. The server uses past fare data and local economic indicators to calculate the most appropriate bus fare through simulation.

[0050] 6. Generating and Presenting Pricing Proposals

[0051] The server generates a detailed report on fair pricing and sends it to the device. The report is generated in Markdown or HTML format, converted to PDF, and securely sent. The device notifies the user that a fair pricing proposal has been generated and displays the report. The user can review the details of the report and make a final pricing decision based on it.

[0052] Specific example explanation

[0053] A specific example is shown below.

[0054] scenario

[0055] Target area: Machida City, Tokyo

[0056] Population: 10,000 (3,000 elderly, 7,000 young)

[0057] Existing bus operators: Company A and Company B

[0058] Operating Procedure

[0059] 1. The user (city hall employee) enters Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information for Company A and Company B into the terminal and presses the send button.

[0060] 2. The device formats the input information and sends it to the server.

[0061] 3. The server saves or updates the received data in the database.

[0062] 4. The server retrieves population information from the database and analyzes it. For example, it uses Pandas to analyze the age distribution and finds that elderly people account for 30%.

[0063] 5. The server obtains bus operator information, analyzes bus routes using GIS, and analyzes existing fare structures and trends in user numbers.

[0064] 6. Based on the analysis results, the server calculates the appropriate fees, which are set at 200 yen for elderly people and 300 yen for general users.

[0065] 7. The server generates a detailed report of the fair charges and sends it to the terminal in PDF format.

[0066] 8. The terminal notifies the user and displays a report. The user (city hall employee) checks the analysis results and fee proposals and uses them in making a final decision.

[0067] In this way, the system of the present invention makes it possible to efficiently set optimal fares for autonomous buses in a target area.

[0068] The processing flow will be explained below.

[0069] Step 1:

[0070] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, they input "population information for Machida City, Tokyo" and "operation routes and fare information for Company A and Company B." Once the input is complete, they press the send button.

[0071] Step 2:

[0072] The device receives the information entered by the user, formats the data in an appropriate format (e.g., JSON), and sends the formatted data to the server using an HTTP POST request.

[0073] Step 3:

[0074] The server then checks the data received and verifies that it is in the correct format. Once the data has been validated, it connects to a database and saves or updates the information in the database. The saved data includes the area's population information, age distribution, and information about existing transport operators.

[0075] Step 4:

[0076] The server retrieves population information and age distribution for the target area from the database. Using the retrieved data, it analyzes the population distribution and age structure using Python's Pandas library, for example. For example, it calculates the proportion of elderly people and identifies the characteristics of age groups specific to that area.

[0077] Step 5:

[0078] The server retrieves information about existing transportation operators from a database. It uses a GIS (geographic information system) API to perform a geographic analysis of the routes. It also performs statistical analysis of fare information and ridership numbers to evaluate trends in existing fare structures and ridership numbers.

[0079] Step 6:

[0080] The server calculates appropriate fees based on the acquired and analyzed data. For example, it calculates different fees for different age groups, such as setting a fee of 200 yen for seniors and 300 yen for general users. It also references past fee data and regional economic indicators to create an optimal fee model.

[0081] Step 7:

[0082] The server generates a detailed report of the calculated fair fares in Markdown and HTML formats, and finally in PDF format, including demographics, transit operator information, analysis results, and recommended fares.

[0083] Step 8:

[0084] The server sends the generated report to the terminal, which notifies the user when the report has been sent.

[0085] Step 9:

[0086] The terminal notifies the user that the report has been received via a pop-up notification or email. The user can view the report on the terminal and check the details. The user (city hall employee) uses the report as reference material to determine the final fee setting.

[0087] In this way, the system of the present invention sets efficient and appropriate fares for autonomous buses based on regional characteristics.

[0088] Example 1

[0089] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0090] In modern society, changes in demographics and fluctuations in transportation operator operating conditions require the establishment of appropriate fares. However, existing systems often lack reliability and accuracy in fare setting due to insufficient analysis of population distribution and age groups, or the collection and analysis of information on existing transportation operators. Furthermore, the generation and presentation of detailed reports on appropriate fares based on the analysis results is not automated, which can lead to manual errors and time-consuming work. Therefore, there is a need for the development of a system that can efficiently collect and analyze data on population information, age distribution, and existing transportation operators, and automatically calculate appropriate fares.

[0091] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0092] In this invention, the server includes a means for formatting population data and transportation operator information for the target area and sending it to the server, a means for verifying the format of the received data and saving or updating it in an internal database, and a means for utilizing data analysis tools to analyze the population distribution and age structure of the target area. This enables rapid analysis of population distribution and age structure and accurate evaluation of transportation operator operation information. Furthermore, a detailed report of appropriate fares can be automatically generated and presented, improving the reliability and efficiency of fare setting.

[0093] "Area of ​​Interest" means the specific geographic area that is the subject of an analysis or calculation.

[0094] "Population information" refers to statistical information such as the total number of residents in the target area, their gender, and their age group.

[0095] "Age distribution" refers to data showing the age structure of residents in the target area.

[0096] "Transportation operator" means a company or organization that operates public transportation such as buses and trains.

[0097] "Database" refers to a system for organizing, storing, efficiently retrieving, and updating information.

[0098] "Formatting" refers to the process of unifying the data format and making it consistent.

[0099] "Analysis" refers to the process of evaluating collected data and making sense of it.

[0100] "Data analysis tools" refers to software for analyzing collected data and performing statistical evaluations.

[0101] "Geographic Information System (GIS)" means a system for collecting, managing, analyzing, and visualizing geographic information.

[0102] "Fair rates" refer to rates that are calculated based on the analysis results and are considered fair and reasonable for users.

[0103] "Report" means a document summarizing the results of analysis or calculations.

[0104] This invention relates to a system that collects and analyzes information on the population, age distribution, and existing transportation operators of a target area, and then sets appropriate fares. This system is realized through the interaction of a server, terminals, and users.

[0105] Data collection and input

[0106] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information of Company A and Company B into the terminal, and then presses the send button. This operation completes the data input process.

[0107] Data transmission and preprocessing

[0108] The terminal formats the information entered by the user, converts it to JSON format, and sends it to the server. The HTTPS protocol is used for data transmission, ensuring secure data transmission. The server temporarily stores the received data in memory, checks the format, and performs preprocessing.

[0109] Database Update

[0110] The server validates the preprocessed data and saves or updates it in an internal database. Specifically, the server validates the format of the received data, connects to a database (MySQL (registered trademark), PostgreSQL, etc.), and updates existing information or inserts new data. In this process, the server uses transactions to maintain data consistency while proceeding with the process.

[0111] Population and age data analysis

[0112] The server analyzes the population distribution and age structure of the target area. Specifically, it retrieves population data from the database and performs statistical analysis using Python's Pandas library. For example, it confirms that Machida City has a high elderly population and outputs analysis results such as elderly people making up 30% of the total population.

[0113] Analysis of existing bus operator information

[0114] The server analyzes the routes, fare structures, and number of users of existing transportation operators. Specifically, it retrieves bus operator information from a database and visualizes and analyzes route data using geographic information system (GIS) software (ArcGIS or QGIS). It also graphs and evaluates trends in fare structures and user numbers using Python's Matplotlib and Seaborn.

[0115] Calculating fair fees

[0116] The server calculates the appropriate fee based on the analysis results. The server references past fee data and local economic indicators and executes algorithms to perform simulations. For example, it uses regression analysis to calculate the appropriate fee of 200 yen for the elderly and 300 yen for general users. These calculations are performed using Python's Scikit-learn library.

[0117] Generate and present reports

[0118] The server generates a detailed report on fair pricing and sends it to the device. Specifically, the report is generated in Markdown or HTML format and then converted to PDF format. The generated PDF is attached to an email or sent to the device via a secure channel. The device notifies the user of the analysis results and pricing proposals and displays the report. The user can then make a final pricing decision based on the report.

[0119] Prompt Sentence Examples

[0120] "Calculate the appropriate fares for the transportation business based on Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information for companies A and B. Then, referencing various statistical data and regional economic indicators, generate a report proposing a fare of 200 yen for elderly people and 300 yen for general users."

[0121] By using the system of the present invention, it is possible to efficiently set fares for autonomous buses that are optimal for the target area, contributing to improving the efficiency and convenience of local transportation.

[0122] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0123] Program processing flow

[0124] Step 1: Data collection and entry

[0125] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs population data for Machida City, such as 3,000 elderly people and 7,000 young people, as well as route and fare information for companies A and B, into the terminal, confirms the input data, and then presses the send button. This sends the information entered by the user to the terminal, where it is formatted and prepared for transmission.

[0126] Input: population information of the target area, age distribution, transportation operator information

[0127] Output: The formatted input data

[0128] Step 2: Data transmission and preprocessing

[0129] The terminal converts the information entered by the user into JSON format and sends it to the server using HTTPS. The server temporarily stores the received data in memory and verifies whether the data format is correct. For example, if the data format is correct, the formatted data is prepared for storage on the server.

[0130] Input: Formatted input data

[0131] Output: Data sent to the server

[0132] Step 3: Update the database

[0133] The server saves or updates the received data in an internal database (for example, MySQL or PostgreSQL). If the same information already exists, the corresponding record is updated, and if not, a new record is inserted. Data consistency is maintained through transaction management.

[0134] Input: Data sent to the server

[0135] Output: Data saved or updated in the database

[0136] Step 4: Population and age data analysis

[0137] The server retrieves population data from the database and performs statistical analysis using Python's Pandas library, such as calculating the ratio of elderly to young people and finding that elderly people account for 30% of the total population in Machida City.

[0138] Input: Population data retrieved from the database

[0139] Output: Statistical analysis results (e.g., elderly people account for 30% of the total)

[0140] Step 5: Analyze existing bus operator information

[0141] The server retrieves bus operator information from the database and uses GIS tools (such as ArcGIS or QGIS) to visualize and analyze routes. It also uses Python's Matplotlib and Seaborn to graph and evaluate trends in fare structures and ridership. For example, it can conclude that Company A has more riders than Company B, but its fares are higher, so it needs to review its pricing.

[0142] Input: Bus operator information retrieved from the database

[0143] Output: Visualization of operation routes using GIS, evaluation of fare structures and trends in number of users

[0144] Step 6: Calculate the fair price

[0145] The server calculates the appropriate fee based on the analysis results. It sets the fee using regression analysis, referencing past fee data and regional economic indicators. For example, it calculates a fee of 200 yen for the elderly and 300 yen for general users through simulation.

[0146] Input: Analysis results, historical pricing data, local economic indicators

[0147] Output: Fair fee calculation result

[0148] Step 7: Generate and present the report

[0149] The server generates a detailed report on fair pricing in Markdown or HTML format, converts it to PDF format, and sends it to the terminal. The terminal notifies the user of the received PDF and displays the report so that the user can review it. The user then determines the final pricing based on the analysis results and pricing proposals.

[0150] Input: Calculation result of fair fee

[0151] Output: Generated report (PDF format), notification to user

[0152] By following the above steps, this system can automate and efficiently set optimal rates for the target area.

[0153] (Application example 1)

[0154] 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."

[0155] Conventional pricing systems for autonomous vehicles do not fully consider the population information and age distribution of the target area, or information on existing transportation operators, making it difficult to calculate appropriate fares. Furthermore, there was no efficient system for collecting and analyzing this information, making operation cumbersome. Furthermore, there was a need to present the analysis results in a user-friendly format.

[0156] 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.

[0157] In this invention, the server includes: means for inputting population information for a target area; means for inputting age distribution for the target area; means for inputting information about existing transportation operators; means for saving or updating the input information in a database; means for analyzing the population information and age distribution saved in the database; means for analyzing information about transportation operators saved in the database; means for calculating an appropriate fare to display on a smartphone, smart glasses, or head-mounted display; means for generating and presenting a detailed report of the appropriate fare; means for using a generative AI model to generate a report of analysis results regarding fare setting for autonomous vehicles; and means for using a generative AI model to generate a prompt message for an appropriate fare based on the analysis results. This enables efficient and accurate fare setting that takes into account the population information, age distribution, and information about existing transportation operators for the target area.

[0158] A "target area" is an area for which specific population information, age distribution, and transportation operator information are analyzed.

[0159] "Population information" is data on the number and distribution of people living in a target area.

[0160] "Age distribution" is information that shows the proportion of the population of various age groups in the target area.

[0161] "Transportation operator information" is data related to transportation such as buses that operate within the target area.

[0162] "Database" means a system for storing or updating collected population information, age distribution, and transportation operator information.

[0163] "Analysis methods" are methods for analyzing population distribution and transportation company routes based on information stored in the database.

[0164] The "fair fare calculation method" is a method for calculating fair fares for autonomous vehicles based on the results of an analysis of population information, age distribution, and transportation operator information.

[0165] The "report generation means" is a method for generating a detailed report of the calculation results of the fair fee and related information, and presenting it to the user.

[0166] A "smartphone" is a mobile device that combines the functions of a mobile phone and a computer.

[0167] "Smart glasses" are eyeglass-shaped wearable devices that have the function of displaying information.

[0168] A "head-mounted display" is a display device worn on the head, and is a device that has the function of displaying digital information in the field of vision.

[0169] A "generative AI model" is a system that uses artificial intelligence (AI) to analyze data and automatically generate effective pricing calculations and reports.

[0170] A "prompt" is an instruction generated by an AI model to present appropriate pricing and related information.

[0171] MODE FOR CARRYING OUT THE INVENTION

[0172] The embodiment of the present invention is a system that collects and analyzes information on the population, age distribution, and existing transportation operators of a target area to set appropriate fares. This system is realized through the interaction of a server, terminals, and users.

[0173] System configuration and operation

[0174] 1. Data collection and input

[0175] Users use a smartphone, smart glasses, or head-mounted display to input information about the target area's population, age distribution, and existing transportation operators. For example, a government official inputs data for a city and presses the send button, which sends the information to the server. The device then formats the input information and sends it to the server as data.

[0176] 2. Updating the database

[0177] The server checks the data received from the device and saves or updates it in its internal database. After receiving the data, the server verifies its format, connects to the database, and updates existing information or inserts new data. This database uses SQLite.

[0178] 3. Demographic and Age Data Analysis

[0179] The server analyzes the population distribution and age structure of the target area. The server retrieves population data from the database and analyzes this data using analytical tools such as Python's Pandas. For example, it performs statistical analysis to determine that there are many elderly people in a particular area and that the elderly make up 30% of the total population.

[0180] 4. Analysis of existing bus operator information

[0181] The server analyzes the routes, fare structures, and ridership numbers of existing transport operators. The server retrieves information about transport operators from a database and evaluates trends in routes and ridership numbers using a geographic information system (GIS) and other analytical tools.

[0182] 5. Calculating the appropriate fee

[0183] The server calculates the appropriate fee based on the analysis results. For example, it may set the fee at 200 yen for seniors and 300 yen for general users. The server calculates the most appropriate fee through simulations based on past fee data and local economic indicators.

[0184] 6. Generating and Presenting Pricing Proposals

[0185] The server generates a detailed report on fair pricing and sends it to the device. The report is generated in Markdown or HTML format and sent securely. The device notifies the user that fair pricing suggestions have been generated and displays the report. Using a generative AI model, fair pricing prompts are also generated to make the report user-friendly.

[0186] Hardware and software used

[0187] Hardware: Standard servers (e.g., AWS®, Google® Cloud), smartphones, smart glasses, head-mounted displays

[0188] Software: Python (Pandas, GeoPandas), SQLite, generative AI models

[0189] Specific examples

[0190] scenario:

[0191] Target area: A city

[0192] Population: 50,000 (15,000 elderly, 35,000 young)

[0193] Existing bus operators: Transportation companies A and B

[0194] Operation steps:

[0195] 1. An administrative official enters the city's population data (15,000 elderly people, 35,000 young people) and the route and fare information for companies A and B into the terminal and presses the send button.

[0196] 2. The device formats the input information and sends it to the server.

[0197] 3. The server saves or updates the received data in the database.

[0198] 4. The server retrieves population information from the database, analyzes the age distribution using Pandas, and confirms that elderly people account for 30%.

[0199] 5. The server obtains transportation operator information, analyzes routes using GeoPandas, and analyzes existing fare structures and trends in ridership.

[0200] 6. Based on the analysis results, the server calculates the appropriate fees, which are set at 200 yen for elderly people and 300 yen for general users.

[0201] 7. The server generates a detailed report of the fair charges and sends it to the terminal in PDF format.

[0202] 8. The device notifies the user and displays a report, and also generates prompts regarding fair pricing using a generative AI model.

[0203] Example prompt sentence:

[0204] "Use generative AI to analyze the appropriate fare for a city's autonomous buses. Consider the following data:

[0205] Population data (e.g., 15,000 elderly people, 35,000 young people)

[0206] Route and fare information for existing bus operators

[0207] As a result of the analysis, please calculate the appropriate fees for elderly people and general users and create a detailed report. For example, set the fees at 200 yen for elderly people and 300 yen for general users.

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

[0209] Step 1:

[0210] Entering and Submitting Data

[0211] The user uses a smartphone, smart glasses, or head-mounted display to input information about the target area's population, age distribution, and information about existing transportation operators into the terminal and presses the send button. At this time, the input information is formatted in JSON format or similar. The input data (population information, age distribution, transportation operator information) from the terminal is sent to the server.

[0212] Input: population information of the target area, age distribution, transportation operator information

[0213] Output: Send formatted data to the server

[0214] Step 2:

[0215] Save or update to database

[0216] The server checks the data received from the device and stores or updates it in its internal database. The server first verifies the format of the received data, then connects to the SQLite database to update existing information or insert new data.

[0217] Input: Data received from the device (JSON format population information, age distribution, transportation operator information)

[0218] Output: Database update status

[0219] Step 3:

[0220] Analysis of population and age data

[0221] The server retrieves population information and age distributions from the database and analyzes this data using Python's Pandas library, calculating the population percentage for each age group and analyzing, for example, what percentage of the population is elderly.

[0222] Input: Population information and age distribution obtained from the database

[0223] Output: Population percentage by age group (e.g., 30% elderly)

[0224] Step 4:

[0225] Analysis of transportation operator information

[0226] The server retrieves the transportation operator's route, fare structure, and number of users from the database and performs geographic information analysis using libraries such as GeoPandas, thereby analyzing route efficiency and user trends.

[0227] Input: Transport operator information obtained from the database (operation route, fare structure, number of users)

[0228] Output: Route efficiency, ridership trends

[0229] Step 5:

[0230] Calculating fair fees

[0231] The server calculates appropriate fares based on the analysis of population information, age distribution, and transportation company operation information. For example, it simulates and sets fares of 200 yen for seniors and 300 yen for general users. Fares are set more precisely using a generative AI model.

[0232] Input: Analysis results of population information, age distribution, and transportation company operation information

[0233] Output: Reasonable fee (200 yen for seniors, 300 yen for general users)

[0234] Step 6:

[0235] Generate and present pricing proposals

[0236] The server generates a detailed report on fair pricing and sends it to the device. The report is generated in Markdown or HTML format and then converted to PDF. The device notifies the user and displays the report. Additionally, a generative AI model is used to generate prompts based on the analysis results.

[0237] Input: Calculation result of fair fee

[0238] Output: Detailed report (PDF format), prompt statement

[0239] Examples:

[0240] Example prompt sentence:

[0241] "Use generative AI to analyze the appropriate fare for a city's autonomous buses. Consider the following data:

[0242] Population data (e.g., 15,000 elderly people, 35,000 young people)

[0243] Route and fare information for existing bus operators

[0244] As a result of the analysis, please calculate the appropriate fees for elderly people and general users and create a detailed report. For example, set the fees at 200 yen for elderly people and 300 yen for general users.

[0245] 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.

[0246] This invention combines an emotion engine with a system that collects and analyzes information on the population, age distribution, and existing transportation operators in the target area to set appropriate fares. This system is realized through the interaction of servers, terminals, and users.

[0247] System configuration and operation

[0248] 1. Data collection and input

[0249] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs data for Machida City and presses the send button, sending this information to the server. The terminal then formats the input information and sends it to the server as data.

[0250] 2. Updating the database

[0251] The server validates the data received from the device and stores or updates it in its internal database. After receiving the data, the server validates its format, connects to the database, and updates existing information or inserts new data.

[0252] 3. Demographic and Age Data Analysis

[0253] The server analyzes the population distribution and age structure of the target area. The server retrieves population data from the database and analyzes this data using analytical tools such as Python's Pandas. For example, it performs a statistical analysis to determine that Machida City has a large elderly population and that the elderly make up 30% of the total population.

[0254] 4. Analysis of existing bus operator information

[0255] The server analyzes the routes, fare structures, and ridership numbers of existing transport operators. The server retrieves bus operator information from a database and evaluates trends in routes and ridership numbers using a geographic information system (GIS) and other analytical tools.

[0256] 5. Calculating the appropriate fee

[0257] The server calculates the appropriate fare based on the analysis results. For example, it might set a fare of 200 yen for seniors and 300 yen for general users. The server uses past fare data and local economic indicators to calculate the most appropriate bus fare through simulation.

[0258] 6. Incorporating an Emotional Engine

[0259] In the present invention, an emotion engine is used to collect user emotion data and apply the data to pricing and report display, for example, by collecting emotion data in real time when a user is using an emotion recognition device.

[0260] 7. Generating and Presenting Pricing Proposals

[0261] The server generates a detailed report on fair fares in Markdown and HTML formats, and finally in PDF format. The report includes demographics, operator information, analysis results, and fare recommendations. The report's content and presentation can be tailored based on data from the sentiment engine.

[0262] 8. User Notification and Feedback

[0263] The server sends the generated report to the device. Once the report has been sent, the device notifies the user. The user can view the report on the device and check the details. If emotion data has been collected, it can also be used as user feedback.

[0264] Specific example explanation

[0265] A specific example is shown below.

[0266] scenario

[0267] Target area: Machida City, Tokyo

[0268] Population: 10,000 (3,000 elderly, 7,000 young)

[0269] Existing bus operators: Company A and Company B

[0270] Operating Procedure

[0271] 1. The user (city hall employee) enters Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information for Company A and Company B into the terminal and presses the send button.

[0272] 2. The device formats the input information and sends it to the server.

[0273] 3. The server saves or updates the received data in the database.

[0274] 4. The server retrieves population information from the database and analyzes it. For example, it uses Pandas to analyze the age distribution and finds that elderly people account for 30% of the population.

[0275] 5. The server obtains bus operator information, analyzes bus routes using GIS, and analyzes existing fare structures and trends in user numbers.

[0276] 6. Based on the analysis results, the server calculates the appropriate fees, which are set at 200 yen for elderly people and 300 yen for general users.

[0277] 7. The server generates a detailed report of the fair charges and sends it to the terminal in PDF format.

[0278] 8. The emotion engine collects user emotion data, and the server uses that data to adjust the content and presentation of the report.

[0279] 9. The terminal notifies the user and displays a report. The user (city hall employee) checks the analysis results and pricing proposal and uses them in making a final decision. Emotional data is also used as a reference for the final decision.

[0280] In this way, the system of the present invention sets efficient and appropriate fares for autonomous buses based on regional characteristics, and by taking user emotions into consideration, it becomes possible to set fares more adaptively.

[0281] The processing flow will be explained below.

[0282] Step 1:

[0283] Users input information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee might input "Machida City's population data" (3,000 elderly people, 7,000 young people) and "operation routes and fare information for Company A and Company B," then press the send button.

[0284] Step 2:

[0285] The device receives the information entered by the user, formats the data in an appropriate format (e.g., JSON), and sends the formatted data to the server using an HTTP POST request.

[0286] Step 3:

[0287] The server checks the received data and verifies that it is in the correct format. Once the data is verified, it connects to a database and saves or updates the information in the database. For example, the database records the population information, age distribution, and information about existing transport operators in the target area.

[0288] Step 4:

[0289] The server retrieves population information and age distribution for the target area from the database. Using Python's Pandas library, the server analyzes the population distribution and age structure. For example, it calculates that the proportion of elderly people is 30%.

[0290] Step 5:

[0291] The server retrieves information about existing transport operators from a database, uses a GIS (geographic information system) API to perform a geographic analysis of the routes, and performs statistical analysis of fare information and user numbers.

[0292] Step 6:

[0293] The server calculates the appropriate fee based on the acquired and analyzed data. For example, the fee for seniors may be set at 200 yen, and the fee for general users at 300 yen. This allows different fees to be calculated for each age group.

[0294] Step 7:

[0295] The server generates a detailed report of the generated fair fares in Markdown and HTML format, which is then converted to PDF format, and includes demographics, operator information, analysis results, and recommended fares.

[0296] Step 8:

[0297] The server collects user emotion data using an emotion engine. For example, if the user uses an emotion recognition device, the server acquires the user's emotional state (satisfied, dissatisfied, excited, etc.) in real time.

[0298] Step 9:

[0299] The server adjusts the content and presentation of the report based on the emotion data. For example, if the user is frustrated, it adjusts the tone of the report to provide a more understandable explanation.

[0300] Step 10:

[0301] The server sends the generated report to the terminal, which notifies the user when the report has been sent.

[0302] Step 11:

[0303] The device will notify the user via a pop-up notification or email that the report has been received. The user can view the report on the device and check the details. Emotional data will also be referenced and used as user feedback. The user (city hall employee) will use the report as reference material to determine the final pricing.

[0304] In this way, the system of the present invention sets efficient and appropriate fares for autonomous buses based on regional characteristics, and by taking user emotions into consideration, it becomes possible to set fares more adaptively.

[0305] Example 2

[0306] 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."

[0307] The current transportation fare system does not effectively utilize information on the local population structure, age distribution, or existing transportation operators, making it difficult to set fair and appropriate fares.Furthermore, the system does not take into account user emotions when setting fares or displaying reports, resulting in low user satisfaction.

[0308] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0309] In this invention, the server includes means for inputting population information for a target area, means for inputting the age distribution of the target area, means for inputting information about existing transportation operators, means for saving or updating the input information in a database, means for analyzing the population information and age distribution saved in the database, means for analyzing the information about transportation operators saved in the database, means for calculating an appropriate fare based on the analysis results, means for generating and presenting a detailed report of the appropriate fare, means for using an emotion engine to collect user emotion data, and means for applying the emotion data to fare setting and report display. This enables the transportation fare system to set appropriate fares and provide reports that take into account regional characteristics and user emotions.

[0310] "Target area" means a specific geographic area established for the purpose of collecting and analyzing population information, age distribution, and transportation operator information.

[0311] "Population information" refers to data that indicates the total number of people living in a particular area and their characteristics.

[0312] "Age distribution" refers to data that shows the proportion and composition of the population by age group living in a particular area.

[0313] A "transportation operator" is a company or organization that operates public transportation such as buses and trains.

[0314] A "database" is a system for organizing, efficiently storing, and managing information.

[0315] "Analysis" refers to the techniques used to examine collected data in detail and extract meaningful information.

[0316] "Fair fare" means a fair and reasonable fare that users can accept for the transportation services provided.

[0317] A "report" is a document that clearly presents the results of the analysis and recommendations.

[0318] "Emotion data" refers to information that quantifies the user's emotions and psychological state.

[0319] An "emotion engine" is a piece of software or hardware dedicated to collecting and analyzing users' emotional data.

[0320] "Pricing" refers to the process of determining prices for transportation services.

[0321] "Report display" refers to the visual presentation of a generated report to a user.

[0322] This invention combines an emotion engine with a system that collects and analyzes information on the population, age distribution, and existing transportation operators in the target area to set appropriate fares. This system is realized through the interaction of a server, terminals, and users.

[0323] Hardware and software used

[0324] server

[0325] The server handles all major processing, from data storage, analysis, billing, and report generation. The software that runs on the server includes:

[0326] Database management system (e.g. MySQL)

[0327] Data analysis tools (e.g., Python, Pandas, SciPy)

[0328] Geographic Information Systems (e.g. QGIS)

[0329] Emotion Recognition Software

[0330] Report generation tools (e.g., Markdown, HTML, PDF export)

[0331] Terminal

[0332] The terminal provides the interface for users to enter data and view and manipulate reports. Software running on the terminal includes:

[0333] A front-end framework that provides a form input screen (e.g., React, Angular)

[0334] API client to send and receive data

[0335] A viewer for displaying reports in the interface (e.g., a PDF viewer)

[0336] User

[0337] Users input the target area's population information, age distribution, and existing transport operators' information into the terminal, and then check the generated report. The devices used by users include regular PCs, tablets, and smartphones.

[0338] Data processing and calculation

[0339] 1. Data collection and input

[0340] The user inputs information about the target area into the terminal. For example, a city hall employee inputs the population data for Machida City (3,000 elderly people, 7,000 young people) and the route and fare information for existing bus operators A and B, and sends the data to the server.

[0341] 2. Sending and Receiving Data

[0342] The device formats the input information and sends it to the server, which receives the data and verifies that it is in the proper format.

[0343] 3. Updating the database

[0344] The server stores or updates the received data in the database: existing data is updated and new data is inserted.

[0345] 4. Analysis of Demographic and Age Data

[0346] The server retrieves population information from the database and analyzes the age distribution using Python's Pandas. Specifically, it confirms that elderly people account for 30% of the population.

[0347] 5. Analysis of existing bus operator information

[0348] The server uses GIS tools to analyze information such as bus operator routes and evaluate route overlaps and fare trends.

[0349] 6. Calculating the appropriate fee

[0350] The server calculates the appropriate fee based on the analysis results and runs a simulation to set the fee at 200 yen for the elderly and 300 yen for general users.

[0351] 7. Incorporating an Emotional Engine

[0352] The emotion engine collects user emotion data, for example, by using an emotion recognition device to capture the user's emotional state in real time and apply it to pricing and report display.

[0353] 8. Generating and Presenting Pricing Proposals

[0354] The server generates a detailed report on fair fares in Markdown and HTML formats, and finally sends it to the device in PDF format. The report includes demographics, transportation operator information, analysis results, and fare recommendations. The report presentation is adjusted based on sentiment data.

[0355] Specific example explanation

[0356] Specific examples of the present invention will be described below.

[0357] scenario

[0358] Target area: Machida City, Tokyo

[0359] Population: 10,000 (3,000 elderly, 7,000 young)

[0360] Existing bus operators: Company A and Company B

[0361] Operating Procedure

[0362] 1. The user (city hall employee) enters Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information for Company A and Company B into the terminal and presses the send button.

[0363] 2. The device formats the input information and sends it to the server.

[0364] 3. The server saves or updates the received data in the database.

[0365] 4. The server retrieves population information from the database and uses Pandas to analyze the age distribution. For example, it confirms that elderly people account for 30%.

[0366] 5. The server obtains bus operator information, analyzes bus routes using GIS, and analyzes existing fare structures and trends in ridership.

[0367] 6. Based on the analysis results, the server calculates the appropriate fees, which are set at 200 yen for elderly people and 300 yen for general users.

[0368] 7. The server generates a detailed report of the fair charges and sends it to the terminal in PDF format.

[0369] 8. The emotion engine collects user emotion data, and the server adjusts the report content and display method based on that data.

[0370] 9. The terminal notifies the user and displays a report. The user (city hall employee) checks the analysis results and pricing proposal and uses them in making a final decision. Emotional data is also used as a reference for the final decision.

[0371] In this way, the system of the present invention can realize efficient and appropriate pricing based on regional characteristics and user sentiment.

[0372] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0373] Step 1:

[0374] Data collection and input

[0375] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information of existing bus operators. The terminal formats this data and sends it to the server as JSON format data.

[0376] Input: population information of the target area, age distribution, transportation operator information

[0377] Output: Formatted JSON data

[0378] Step 2:

[0379] Sending and Receiving Data

[0380] The device sends the formatted data to the server via an HTTP POST request. The server receives this request and parses the data sent in JSON format. It checks whether the data is properly formatted and performs error handling if necessary.

[0381] Input: JSON format data

[0382] Output: Parsed data, error message (if needed)

[0383] Step 3:

[0384] Database Update

[0385] The server saves or updates the received data in a database. Existing data is updated and new data is inserted. For example, if population information already exists, it is updated, and if it does not exist, a new entry is added. MySQL or similar database management systems are used.

[0386] Input: Parsed data

[0387] Output: Updated or newly inserted database records

[0388] Step 4:

[0389] Analysis of population and age data

[0390] The server retrieves population information from the database and analyzes the age distribution using Python's Pandas. For example, it converts the population data into a data frame, groups it by the age column, and counts the number of people in each age group. This gives statistical information such as the fact that elderly people account for 30% of the total population.

[0391] Input: Population information retrieved from the database

[0392] Output: Age distribution analysis results

[0393] Step 5:

[0394] Analysis of existing bus operator information

[0395] The server retrieves information such as the routes, fare structures, and number of passengers of existing bus operators from the database and analyzes it using a GIS tool (e.g., QGIS). Specifically, it evaluates route overlaps and fare trends, and visualizes the number of passengers for each route using a heat map to identify areas with high demand.

[0396] Input: Transportation operator information obtained from the database

[0397] Output: Route analysis results using GIS, visualization of fare trends

[0398] Step 6:

[0399] Calculating fair fees

[0400] The server calculates the appropriate fare based on the analysis of population and transportation operator data. The pricing algorithm uses historical fare data and local economic indicators as inputs and uses Python's SciPy library to find the optimal fare through simulation. For example, the fare might be set at 200 yen for seniors and 300 yen for general users.

[0401] Input: Age distribution analysis results, transportation operator information analysis results

[0402] Output: Fair pricing results

[0403] Step 7:

[0404] Incorporating an emotion engine

[0405] The server uses an emotion engine to collect user emotion data. If the user is using an emotion recognition device (e.g., a facial recognition camera or biometric sensor), the emotion data is acquired in real time and applied to pricing and report display. For example, if the user is feeling stressed, the fee will be adjusted or the report display method will be changed.

[0406] Input: Emotion data obtained in real time from an emotion recognition device

[0407] Output: Emotion data analysis results

[0408] Step 8:

[0409] Generate and present pricing proposals

[0410] The server generates a detailed report on fair fares, which is then sent to the device in Markdown, HTML, and finally PDF format. The report includes demographics, operator information, analysis results, and fare recommendations. The report content and presentation are adjusted based on sentiment data.

[0411] Input: Results of appropriate pricing, analysis results of emotional data

[0412] Output: Generated report in PDF format

[0413] Step 9:

[0414] User Notification and Feedback

[0415] The device notifies the user of the report received from the server. The user can view the report on the device and check the details. For example, a notification message is displayed on the device, and the report can be opened by clicking the "View details" button. Feedback can also be sent to the server based on emotional data. For example, an interface is provided for rating satisfaction with the report.

[0416] Input: PDF report sent from the server

[0417] Output: User report viewing and feedback data

[0418] By using these detailed processing steps, the system of the present invention can realize efficient and appropriate pricing based on regional characteristics and user sentiment.

[0419] (Application example 2)

[0420] 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."

[0421] When setting fares for autonomous vehicles, it is necessary to realize more appropriate and flexible pricing by not only taking into account regional characteristics (population information and age distribution) but also by appropriately reflecting user emotional data. Furthermore, a method is needed to increase user satisfaction.

[0422] 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.

[0423] In this invention, the server includes means for inputting population information of the target area, means for inputting age distribution of the target area, and means for inputting information about existing transportation operators.

[0424] This will enable detailed analysis and pricing based on various data.

[0425] The system further includes means for collecting emotional data and reflecting the data in pricing and display, and means for adapting pricing using the user's emotional data.

[0426] This will enable flexible and appropriate pricing that takes into account the user's feelings, thereby improving user satisfaction.

[0427] "Population information for the target area" is statistical data on the total number, age, gender, etc. of people living in the area.

[0428] "Age distribution" is statistical data that classifies an unspecified number of people in a particular area by age.

[0429] "Information about transportation operators" refers to data on routes, fare structures, number of users, etc., of companies and organizations that provide transportation services.

[0430] A "database" is a collection of data that stores collected information and can be searched and updated as needed.

[0431] "Analysis results" are analytical results or conclusions obtained through statistical methods or calculations based on collected data.

[0432] A "fair price" is a price that is set based on the analysis results and is considered to be the most fair and reasonable price for each user.

[0433] "Emotion data" is information that indicates the user's current emotional state.

[0434] The "adaptive pricing mechanism" refers to a method or system for dynamically changing pricing in response to user emotional data.

[0435] The present invention is a system that collects and analyzes information on the population and age distribution of a target area, as well as information on existing transportation operators, and also reflects user emotional data in order to set appropriate fares for autonomous vehicles. Specific embodiments of this system are described below.

[0436] Hardware and Software Use

[0437] The system is constructed using smartphones, smart glasses, head-mounted displays, or robots as the server, terminal, and user interfaces. Python's Pandas is used for data analysis, and a geographic information system (GIS) is used for geographic information analysis. An appropriate emotion recognition engine is used to collect and analyze emotion data.

[0438] Data collection and input

[0439] The user, a city hall employee, inputs information about the target area's population, age distribution, and information about existing transportation operators into a terminal that serves as an interface. This data is sent from the terminal to a server and stored in a database. For example, this includes population data for Machida City and operation information for multiple bus operators.

[0440] Database Update

[0441] The server receives the data sent from the terminal and updates the database. After verifying that the data format is correct, new data is inserted or existing data is updated.

[0442] Data analysis

[0443] The server analyzes the population information and age distribution stored in the database using analytical tools such as Pandas. For example, it calculates the population percentage by age group and confirms that elderly people account for 30% of the total. It also analyzes information from transportation operators using a geographic information system (GIS) to evaluate trends in operation routes and user numbers.

[0444] Calculating fair fees

[0445] The server calculates the appropriate fee based on the analysis results. For example, it may set a fee of 200 yen for seniors and 300 yen for general users. Simulations are performed based on past fee data and regional economic indicators to determine the most appropriate fee setting.

[0446] Emotion engine integration

[0447] An emotion recognition device is used to collect real-time emotional data from users and send it to a server. The server analyzes the collected emotional data and reflects it in pricing and report display methods. For example, if the emotion is "happy," the system may adjust the fee slightly.

[0448] Generate and present pricing reports

[0449] The server generates a detailed report on fair pricing in Markdown or HTML format, and finally converts it to PDF format and sends it to the terminal. The user (city hall employee) can check the report on the terminal and use it to make a final decision.

[0450] Specific examples

[0451] For example, consider the following scenario in Machida City, Tokyo.

[0452] Target area: Machida City, Tokyo

[0453] Population: 10,000 (3,000 elderly, 7,000 young)

[0454] Existing bus operators: Multiple companies

[0455] City hall staff collect this information and enter it into a system that analyzes the data and calculates the appropriate fee.

[0456] Prompt Sentence Examples

[0457] Below is an example of an input prompt for a generative AI model.

[0458] Please calculate the appropriate fare for a self-driving bus in Machida City, Tokyo under the following conditions.

[0459] The total population is 10,000, of which 3,000 are elderly and 7,000 others.

[0460] There are multiple existing bus operators, each offering different routes.

[0461] Apply discounts for seniors to fair fares and also reflect emotional data.

[0462] In this way, the system of the present invention realizes efficient and fair pricing while taking into consideration regional characteristics and user sentiment.

[0463] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0464] Step 1:

[0465] The user (city hall employee) inputs population information, age distribution, and operation information of existing transportation operators for the target area into the terminal.

[0466] Input: Population information, age distribution, transportation operator operation data

[0467] Output: Formatted data

[0468] Specific operation: Through the interface, users input information about the population and age distribution of each region, as well as the routes and fares of each transportation company.

[0469] Step 2:

[0470] The device formats the input information and sends it to the server.

[0471] Input: User-entered population information, age distribution, and transportation operator operation data

[0472] Output: Formatted data sent to the server

[0473] Specific operation: The terminal standardizes the input data, converts it into CSV or JSON format, and sends it to the server.

[0474] Step 3:

[0475] The server saves or updates the received data in the database.

[0476] Input: Formatted data

[0477] Output: Information stored in the database

[0478] What happens: The server validates the format of the data and inserts new data or updates existing data in the database.

[0479] Step 4:

[0480] The server retrieves and analyzes demographic information and age distribution from the database.

[0481] Input: Population information and age distribution stored in a database

[0482] Output: Demographic data by age group

[0483] Specific operation: The server uses analytical tools such as Pandas to calculate the population percentage of each age group. For example, it calculates that the elderly make up 30% of the total population.

[0484] Step 5:

[0485] The server analyzes the transportation company's routes and number of users.

[0486] Input: Transport operator operation data stored in a database

[0487] Output: Statistical data on number of users by route

[0488] Specific operation: The server uses a geographic information system (GIS) to analyze trends in each route and the number of passengers.

[0489] Step 6:

[0490] The server calculates the appropriate fee based on the analysis results.

[0491] Input: Demographic data, transportation operator ridership data

[0492] Output: Proposed pricing

[0493] Specific operation: The server performs simulations based on past fee data and local economic indicators to calculate the optimal fee. For example, it may set the fee at 200 yen for seniors and 300 yen for general users.

[0494] Step 7:

[0495] The server collects sentiment data and incorporates it into pricing and reporting.

[0496] Input: Real-time emotion data from emotion recognition device

[0497] Output: Pricing reflecting sentiment data

[0498] Specific operation: Based on the emotional data, if the user is in a "happy" state, the system will adapt, such as reducing the general user fee by 10 yen.

[0499] Step 8:

[0500] The server generates a detailed report of the fair charges and sends it to the terminal.

[0501] Input: Data analysis results, sentiment data, pricing

[0502] Output: Detailed report in PDF format

[0503] Specific operation: The server generates a detailed report in Markdown or HTML format, and finally converts it to PDF format and sends it to the terminal. The user (city hall employee) checks the report on the terminal and uses it for final decision making.

[0504] 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.

[0505] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0506] 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.

[0507] [Second embodiment]

[0508] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0509] 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.

[0510] 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).

[0511] 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.

[0512] 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.

[0513] 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).

[0514] 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. 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.

[0515] 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.

[0516] 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.

[0517] 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.

[0518] 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.

[0519] 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."

[0520] This invention relates to a system that collects and analyzes information on the population, age distribution, and existing transportation operators of a target area, and then sets appropriate fares. This system is realized through the interaction of a server, terminals, and users.

[0521] System configuration and operation

[0522] 1. Data collection and input

[0523] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs data for Machida City and presses the send button, sending this information to the server. The terminal then formats the input information and sends it to the server as data.

[0524] 2. Updating the database

[0525] The server validates the data received from the device and stores or updates it in its internal database. After receiving the data, the server validates its format, connects to the database, and updates existing information or inserts new data.

[0526] 3. Demographic and Age Data Analysis

[0527] The server analyzes the population distribution and age structure of the target area. The server retrieves population data from the database and analyzes this data using analytical tools such as Python's Pandas. For example, it performs a statistical analysis to determine that Machida City has a large elderly population and that the elderly make up 30% of the total population.

[0528] 4. Analysis of existing bus operator information

[0529] The server analyzes the routes, fare structures, and ridership numbers of existing transport operators. The server retrieves bus operator information from a database and evaluates trends in routes and ridership numbers using a geographic information system (GIS) and other analytical tools.

[0530] 5. Calculating the appropriate fee

[0531] The server calculates the appropriate fare based on the analysis results. For example, it might set a fare of 200 yen for seniors and 300 yen for general users. The server uses past fare data and local economic indicators to calculate the most appropriate bus fare through simulation.

[0532] 6. Generating and Presenting Pricing Proposals

[0533] The server generates a detailed report on fair pricing and sends it to the device. The report is generated in Markdown or HTML format, converted to PDF, and securely sent. The device notifies the user that a fair pricing proposal has been generated and displays the report. The user can review the details of the report and make a final pricing decision based on it.

[0534] Specific example explanation

[0535] A specific example is shown below.

[0536] scenario

[0537] Target area: Machida City, Tokyo

[0538] Population: 10,000 (3,000 elderly, 7,000 young)

[0539] Existing bus operators: Company A and Company B

[0540] Operating Procedure

[0541] 1. The user (city hall employee) enters Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information for Company A and Company B into the terminal and presses the send button.

[0542] 2. The device formats the input information and sends it to the server.

[0543] 3. The server saves or updates the received data in the database.

[0544] 4. The server retrieves population information from the database and analyzes it. For example, it uses Pandas to analyze the age distribution and finds that elderly people account for 30%.

[0545] 5. The server obtains bus operator information, analyzes bus routes using GIS, and analyzes existing fare structures and trends in user numbers.

[0546] 6. Based on the analysis results, the server calculates the appropriate fees, which are set at 200 yen for elderly people and 300 yen for general users.

[0547] 7. The server generates a detailed report of the fair charges and sends it to the terminal in PDF format.

[0548] 8. The terminal notifies the user and displays a report. The user (city hall employee) checks the analysis results and fee proposals and uses them in making a final decision.

[0549] In this way, the system of the present invention makes it possible to efficiently set optimal fares for autonomous buses in a target area.

[0550] The processing flow will be explained below.

[0551] Step 1:

[0552] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, they input "population information for Machida City, Tokyo" and "operation routes and fare information for Company A and Company B." Once the input is complete, they press the send button.

[0553] Step 2:

[0554] The device receives the information entered by the user, formats the data in an appropriate format (e.g., JSON), and sends the formatted data to the server using an HTTP POST request.

[0555] Step 3:

[0556] The server then checks the data received and verifies that it is in the correct format. Once the data has been validated, it connects to a database and saves or updates the information in the database. The saved data includes the area's population information, age distribution, and information about existing transport operators.

[0557] Step 4:

[0558] The server retrieves population information and age distribution for the target area from the database. Using the retrieved data, it analyzes the population distribution and age structure using Python's Pandas library, for example. For example, it calculates the proportion of elderly people and identifies the characteristics of age groups specific to that area.

[0559] Step 5:

[0560] The server retrieves information about existing transportation operators from a database. It uses a GIS (geographic information system) API to perform a geographic analysis of the routes. It also performs statistical analysis of fare information and ridership numbers to evaluate trends in existing fare structures and ridership numbers.

[0561] Step 6:

[0562] The server calculates appropriate fees based on the acquired and analyzed data. For example, it calculates different fees for different age groups, such as setting a fee of 200 yen for seniors and 300 yen for general users. It also references past fee data and regional economic indicators to create an optimal fee model.

[0563] Step 7:

[0564] The server generates a detailed report of the calculated fair fares in Markdown and HTML formats, and finally in PDF format, including demographics, transit operator information, analysis results, and recommended fares.

[0565] Step 8:

[0566] The server sends the generated report to the terminal, which notifies the user when the report has been sent.

[0567] Step 9:

[0568] The terminal notifies the user that the report has been received via a pop-up notification or email. The user can view the report on the terminal and check the details. The user (city hall employee) uses the report as reference material to determine the final fee setting.

[0569] In this way, the system of the present invention sets efficient and appropriate fares for autonomous buses based on regional characteristics.

[0570] Example 1

[0571] 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."

[0572] In modern society, changes in demographics and fluctuations in transportation operator operating conditions require the establishment of appropriate fares. However, existing systems often lack reliability and accuracy in fare setting due to insufficient analysis of population distribution and age groups, or the collection and analysis of information on existing transportation operators. Furthermore, the generation and presentation of detailed reports on appropriate fares based on the analysis results is not automated, which can lead to manual errors and time-consuming work. Therefore, there is a need for the development of a system that can efficiently collect and analyze data on population information, age distribution, and existing transportation operators, and automatically calculate appropriate fares.

[0573] 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.

[0574] In this invention, the server includes a means for formatting population data and transportation operator information for the target area and sending it to the server, a means for verifying the format of the received data and saving or updating it in an internal database, and a means for utilizing data analysis tools to analyze the population distribution and age structure of the target area. This enables rapid analysis of population distribution and age structure and accurate evaluation of transportation operator operation information. Furthermore, a detailed report of appropriate fares can be automatically generated and presented, improving the reliability and efficiency of fare setting.

[0575] "Area of ​​Interest" means the specific geographic area that is the subject of an analysis or calculation.

[0576] "Population information" refers to statistical information such as the total number of residents in the target area, their gender, and their age group.

[0577] "Age distribution" refers to data showing the age structure of residents in the target area.

[0578] "Transportation operator" means a company or organization that operates public transportation such as buses and trains.

[0579] "Database" refers to a system for organizing, storing, efficiently retrieving, and updating information.

[0580] "Formatting" refers to the process of unifying the data format and making it consistent.

[0581] "Analysis" refers to the process of evaluating collected data and making sense of it.

[0582] "Data analysis tools" refers to software for analyzing collected data and performing statistical evaluations.

[0583] "Geographic Information System (GIS)" means a system for collecting, managing, analyzing, and visualizing geographic information.

[0584] "Fair rates" refer to rates that are calculated based on the analysis results and are considered fair and reasonable for users.

[0585] "Report" means a document summarizing the results of analysis or calculations.

[0586] This invention relates to a system that collects and analyzes information on the population, age distribution, and existing transportation operators of a target area, and then sets appropriate fares. This system is realized through the interaction of a server, terminals, and users.

[0587] Data collection and input

[0588] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information of Company A and Company B into the terminal, and then presses the send button. This operation completes the data input process.

[0589] Data transmission and preprocessing

[0590] The terminal formats the information entered by the user, converts it to JSON format, and sends it to the server. The HTTPS protocol is used for data transmission, ensuring secure data transmission. The server temporarily stores the received data in memory, checks the format, and performs preprocessing.

[0591] Database Update

[0592] The server validates the pre-processed data and saves or updates it in an internal database. Specifically, the server validates the format of the incoming data, connects to the database (e.g., MySQL or PostgreSQL), and updates existing information or inserts new data. During this process, the server uses transactions to ensure data consistency.

[0593] Population and age data analysis

[0594] The server analyzes the population distribution and age structure of the target area. Specifically, it retrieves population data from the database and performs statistical analysis using Python's Pandas library. For example, it confirms that Machida City has a high elderly population and outputs analysis results such as elderly people making up 30% of the total population.

[0595] Analysis of existing bus operator information

[0596] The server analyzes the routes, fare structures, and number of users of existing transportation operators. Specifically, it retrieves bus operator information from a database and visualizes and analyzes route data using geographic information system (GIS) software (ArcGIS or QGIS). It also graphs and evaluates trends in fare structures and user numbers using Python's Matplotlib and Seaborn.

[0597] Calculating fair fees

[0598] The server calculates the appropriate fee based on the analysis results. The server references past fee data and local economic indicators and executes algorithms to perform simulations. For example, it uses regression analysis to calculate the appropriate fee of 200 yen for the elderly and 300 yen for general users. These calculations are performed using Python's Scikit-learn library.

[0599] Generate and present reports

[0600] The server generates a detailed report on fair pricing and sends it to the device. Specifically, the report is generated in Markdown or HTML format and then converted to PDF format. The generated PDF is attached to an email or sent to the device via a secure channel. The device notifies the user of the analysis results and pricing proposals and displays the report. The user can then make a final pricing decision based on the report.

[0601] Prompt Sentence Examples

[0602] "Calculate the appropriate fares for the transportation business based on Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information for companies A and B. Then, referencing various statistical data and regional economic indicators, generate a report proposing a fare of 200 yen for elderly people and 300 yen for general users."

[0603] By using the system of the present invention, it is possible to efficiently set fares for autonomous buses that are optimal for the target area, contributing to improving the efficiency and convenience of local transportation.

[0604] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0605] Program processing flow

[0606] Step 1: Data collection and entry

[0607] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs population data for Machida City, such as 3,000 elderly people and 7,000 young people, as well as route and fare information for companies A and B, into the terminal, confirms the input data, and then presses the send button. This sends the information entered by the user to the terminal, where it is formatted and prepared for transmission.

[0608] Input: population information of the target area, age distribution, transportation operator information

[0609] Output: The formatted input data

[0610] Step 2: Data transmission and preprocessing

[0611] The terminal converts the information entered by the user into JSON format and sends it to the server using HTTPS. The server temporarily stores the received data in memory and verifies whether the data format is correct. For example, if the data format is correct, the formatted data is prepared for storage on the server.

[0612] Input: Formatted input data

[0613] Output: Data sent to the server

[0614] Step 3: Update the database

[0615] The server saves or updates the received data in an internal database (for example, MySQL or PostgreSQL). If the same information already exists, the corresponding record is updated, and if not, a new record is inserted. Data consistency is maintained through transaction management.

[0616] Input: Data sent to the server

[0617] Output: Data saved or updated in the database

[0618] Step 4: Population and age data analysis

[0619] The server retrieves population data from the database and performs statistical analysis using Python's Pandas library, such as calculating the ratio of elderly to young people and finding that elderly people account for 30% of the total population in Machida City.

[0620] Input: Population data retrieved from the database

[0621] Output: Statistical analysis results (e.g., elderly people account for 30% of the total)

[0622] Step 5: Analyze existing bus operator information

[0623] The server retrieves bus operator information from the database and uses GIS tools (such as ArcGIS or QGIS) to visualize and analyze routes. It also uses Python's Matplotlib and Seaborn to graph and evaluate trends in fare structures and ridership. For example, it can conclude that Company A has more riders than Company B, but its fares are higher, so it needs to review its pricing.

[0624] Input: Bus operator information retrieved from the database

[0625] Output: Visualization of operation routes using GIS, evaluation of fare structures and trends in number of users

[0626] Step 6: Calculate the fair price

[0627] The server calculates the appropriate fee based on the analysis results. It sets the fee using regression analysis, referencing past fee data and regional economic indicators. For example, it calculates a fee of 200 yen for the elderly and 300 yen for general users through simulation.

[0628] Input: Analysis results, historical pricing data, local economic indicators

[0629] Output: Fair fee calculation result

[0630] Step 7: Generate and present the report

[0631] The server generates a detailed report on fair pricing in Markdown or HTML format, converts it to PDF format, and sends it to the terminal. The terminal notifies the user of the received PDF and displays the report so that the user can review it. The user then determines the final pricing based on the analysis results and pricing proposals.

[0632] Input: Calculation result of fair fee

[0633] Output: Generated report (PDF format), notification to user

[0634] By following the above steps, this system can automate and efficiently set optimal rates for the target area.

[0635] (Application example 1)

[0636] 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."

[0637] Conventional pricing systems for autonomous vehicles do not fully consider the population information and age distribution of the target area, or information on existing transportation operators, making it difficult to calculate appropriate fares. Furthermore, there was no efficient system for collecting and analyzing this information, making operation cumbersome. Furthermore, there was a need to present the analysis results in a user-friendly format.

[0638] 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.

[0639] In this invention, the server includes: means for inputting population information for a target area; means for inputting age distribution for the target area; means for inputting information about existing transportation operators; means for saving or updating the input information in a database; means for analyzing the population information and age distribution saved in the database; means for analyzing information about transportation operators saved in the database; means for calculating an appropriate fare to display on a smartphone, smart glasses, or head-mounted display; means for generating and presenting a detailed report of the appropriate fare; means for using a generative AI model to generate a report of analysis results regarding fare setting for autonomous vehicles; and means for using a generative AI model to generate a prompt message for an appropriate fare based on the analysis results. This enables efficient and accurate fare setting that takes into account the population information, age distribution, and information about existing transportation operators for the target area.

[0640] A "target area" is an area for which specific population information, age distribution, and transportation operator information are analyzed.

[0641] "Population information" is data on the number and distribution of people living in a target area.

[0642] "Age distribution" is information that shows the proportion of the population of various age groups in the target area.

[0643] "Transportation operator information" is data related to transportation such as buses that operate within the target area.

[0644] "Database" means a system for storing or updating collected population information, age distribution, and transportation operator information.

[0645] "Analysis methods" are methods for analyzing population distribution and transportation company routes based on information stored in the database.

[0646] The "fair fare calculation method" is a method for calculating fair fares for autonomous vehicles based on the results of an analysis of population information, age distribution, and transportation operator information.

[0647] The "report generation means" is a method for generating a detailed report of the calculation results of the fair fee and related information, and presenting it to the user.

[0648] A "smartphone" is a mobile device that combines the functions of a mobile phone and a computer.

[0649] "Smart glasses" are eyeglass-shaped wearable devices that have the function of displaying information.

[0650] A "head-mounted display" is a display device worn on the head, and is a device that has the function of displaying digital information in the field of vision.

[0651] A "generative AI model" is a system that uses artificial intelligence (AI) to analyze data and automatically generate effective pricing calculations and reports.

[0652] A "prompt" is an instruction generated by an AI model to present appropriate pricing and related information.

[0653] MODE FOR CARRYING OUT THE INVENTION

[0654] The embodiment of the present invention is a system that collects and analyzes information on the population, age distribution, and existing transportation operators of a target area to set appropriate fares. This system is realized through the interaction of a server, terminals, and users.

[0655] System configuration and operation

[0656] 1. Data collection and input

[0657] Users use a smartphone, smart glasses, or head-mounted display to input information about the target area's population, age distribution, and existing transportation operators. For example, a government official inputs data for a city and presses the send button, which sends the information to the server. The device then formats the input information and sends it to the server as data.

[0658] 2. Updating the database

[0659] The server checks the data received from the device and saves or updates it in its internal database. After receiving the data, the server verifies its format, connects to the database, and updates existing information or inserts new data. This database uses SQLite.

[0660] 3. Demographic and Age Data Analysis

[0661] The server analyzes the population distribution and age structure of the target area. The server retrieves population data from the database and analyzes this data using analytical tools such as Python's Pandas. For example, it performs statistical analysis to determine that there are many elderly people in a particular area and that the elderly make up 30% of the total population.

[0662] 4. Analysis of existing bus operator information

[0663] The server analyzes the routes, fare structures, and ridership numbers of existing transport operators. The server retrieves information about transport operators from a database and evaluates trends in routes and ridership numbers using a geographic information system (GIS) and other analytical tools.

[0664] 5. Calculating the appropriate fee

[0665] The server calculates the appropriate fee based on the analysis results. For example, it may set the fee at 200 yen for seniors and 300 yen for general users. The server calculates the most appropriate fee through simulations based on past fee data and local economic indicators.

[0666] 6. Generating and Presenting Pricing Proposals

[0667] The server generates a detailed report on fair pricing and sends it to the device. The report is generated in Markdown or HTML format and sent securely. The device notifies the user that fair pricing suggestions have been generated and displays the report. Using a generative AI model, fair pricing prompts are also generated to make the report user-friendly.

[0668] Hardware and software used

[0669] Hardware: Standard servers (e.g. AWS, Google Cloud), smartphones, smart glasses, head-mounted displays

[0670] Software: Python (Pandas, GeoPandas), SQLite, generative AI models

[0671] Specific examples

[0672] scenario:

[0673] Target area: A city

[0674] Population: 50,000 (15,000 elderly, 35,000 young)

[0675] Existing bus operators: Transportation companies A and B

[0676] Operation steps:

[0677] 1. An administrative official enters the city's population data (15,000 elderly people, 35,000 young people) and the route and fare information for companies A and B into the terminal and presses the send button.

[0678] 2. The device formats the input information and sends it to the server.

[0679] 3. The server saves or updates the received data in the database.

[0680] 4. The server retrieves population information from the database, analyzes the age distribution using Pandas, and confirms that elderly people account for 30%.

[0681] 5. The server obtains transportation operator information, analyzes routes using GeoPandas, and analyzes existing fare structures and trends in ridership.

[0682] 6. Based on the analysis results, the server calculates the appropriate fees, which are set at 200 yen for elderly people and 300 yen for general users.

[0683] 7. The server generates a detailed report of the fair charges and sends it to the terminal in PDF format.

[0684] 8. The device notifies the user and displays a report, and also generates prompts regarding fair pricing using a generative AI model.

[0685] Example prompt sentence:

[0686] "Use generative AI to analyze the appropriate fare for a city's autonomous buses. Consider the following data:

[0687] Population data (e.g., 15,000 elderly people, 35,000 young people)

[0688] Route and fare information for existing bus operators

[0689] As a result of the analysis, please calculate the appropriate fees for elderly people and general users and create a detailed report. For example, set the fees at 200 yen for elderly people and 300 yen for general users.

[0690] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0691] Step 1:

[0692] Entering and Submitting Data

[0693] The user uses a smartphone, smart glasses, or head-mounted display to input information about the target area's population, age distribution, and information about existing transportation operators into the terminal and presses the send button. At this time, the input information is formatted in JSON format or similar. The input data (population information, age distribution, transportation operator information) from the terminal is sent to the server.

[0694] Input: population information of the target area, age distribution, transportation operator information

[0695] Output: Send formatted data to the server

[0696] Step 2:

[0697] Save or update to database

[0698] The server checks the data received from the device and stores or updates it in its internal database. The server first verifies the format of the received data, then connects to the SQLite database to update existing information or insert new data.

[0699] Input: Data received from the device (JSON format population information, age distribution, transportation operator information)

[0700] Output: Database update status

[0701] Step 3:

[0702] Analysis of population and age data

[0703] The server retrieves population information and age distributions from the database and analyzes this data using Python's Pandas library, calculating the population percentage for each age group and analyzing, for example, what percentage of the population is elderly.

[0704] Input: Population information and age distribution obtained from the database

[0705] Output: Population percentage by age group (e.g., 30% elderly)

[0706] Step 4:

[0707] Analysis of transportation operator information

[0708] The server retrieves the transportation operator's route, fare structure, and number of users from the database and performs geographic information analysis using libraries such as GeoPandas, thereby analyzing route efficiency and user trends.

[0709] Input: Transport operator information obtained from the database (operation route, fare structure, number of users)

[0710] Output: Route efficiency, ridership trends

[0711] Step 5:

[0712] Calculating fair fees

[0713] The server calculates appropriate fares based on the analysis of population information, age distribution, and transportation company operation information. For example, it simulates and sets fares of 200 yen for seniors and 300 yen for general users. Fares are set more precisely using a generative AI model.

[0714] Input: Analysis results of population information, age distribution, and transportation company operation information

[0715] Output: Reasonable fee (200 yen for seniors, 300 yen for general users)

[0716] Step 6:

[0717] Generate and present pricing proposals

[0718] The server generates a detailed report on fair pricing and sends it to the device. The report is generated in Markdown or HTML format and then converted to PDF. The device notifies the user and displays the report. Additionally, a generative AI model is used to generate prompts based on the analysis results.

[0719] Input: Calculation result of fair fee

[0720] Output: Detailed report (PDF format), prompt statement

[0721] Examples:

[0722] Example prompt sentence:

[0723] "Use generative AI to analyze the appropriate fare for a city's autonomous buses. Consider the following data:

[0724] Population data (e.g., 15,000 elderly people, 35,000 young people)

[0725] Route and fare information for existing bus operators

[0726] As a result of the analysis, please calculate the appropriate fees for elderly people and general users and create a detailed report. For example, set the fees at 200 yen for elderly people and 300 yen for general users.

[0727] 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.

[0728] This invention combines an emotion engine with a system that collects and analyzes information on the population, age distribution, and existing transportation operators in the target area to set appropriate fares. This system is realized through the interaction of servers, terminals, and users.

[0729] System configuration and operation

[0730] 1. Data collection and input

[0731] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs data for Machida City and presses the send button, sending this information to the server. The terminal then formats the input information and sends it to the server as data.

[0732] 2. Updating the database

[0733] The server validates the data received from the device and stores or updates it in its internal database. After receiving the data, the server validates its format, connects to the database, and updates existing information or inserts new data.

[0734] 3. Demographic and Age Data Analysis

[0735] The server analyzes the population distribution and age structure of the target area. The server retrieves population data from the database and analyzes this data using analytical tools such as Python's Pandas. For example, it performs a statistical analysis to determine that Machida City has a large elderly population and that the elderly make up 30% of the total population.

[0736] 4. Analysis of existing bus operator information

[0737] The server analyzes the routes, fare structures, and ridership numbers of existing transport operators. The server retrieves bus operator information from a database and evaluates trends in routes and ridership numbers using a geographic information system (GIS) and other analytical tools.

[0738] 5. Calculating the appropriate fee

[0739] The server calculates the appropriate fare based on the analysis results. For example, it might set a fare of 200 yen for seniors and 300 yen for general users. The server uses past fare data and local economic indicators to calculate the most appropriate bus fare through simulation.

[0740] 6. Incorporating an Emotional Engine

[0741] In the present invention, an emotion engine is used to collect user emotion data and apply the data to pricing and report display, for example, by collecting emotion data in real time when a user is using an emotion recognition device.

[0742] 7. Generating and Presenting Pricing Proposals

[0743] The server generates a detailed report on fair fares in Markdown and HTML formats, and finally in PDF format. The report includes demographics, operator information, analysis results, and fare recommendations. The report's content and presentation can be tailored based on data from the sentiment engine.

[0744] 8. User Notification and Feedback

[0745] The server sends the generated report to the device. Once the report has been sent, the device notifies the user. The user can view the report on the device and check the details. If emotion data has been collected, it can also be used as user feedback.

[0746] Specific example explanation

[0747] A specific example is shown below.

[0748] scenario

[0749] Target area: Machida City, Tokyo

[0750] Population: 10,000 (3,000 elderly, 7,000 young)

[0751] Existing bus operators: Company A and Company B

[0752] Operating Procedure

[0753] 1. The user (city hall employee) enters Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information for Company A and Company B into the terminal and presses the send button.

[0754] 2. The device formats the input information and sends it to the server.

[0755] 3. The server saves or updates the received data in the database.

[0756] 4. The server retrieves population information from the database and analyzes it. For example, it uses Pandas to analyze the age distribution and finds that elderly people account for 30% of the population.

[0757] 5. The server obtains bus operator information, analyzes bus routes using GIS, and analyzes existing fare structures and trends in user numbers.

[0758] 6. Based on the analysis results, the server calculates the appropriate fees, which are set at 200 yen for elderly people and 300 yen for general users.

[0759] 7. The server generates a detailed report of the fair charges and sends it to the terminal in PDF format.

[0760] 8. The emotion engine collects user emotion data, and the server uses that data to adjust the content and presentation of the report.

[0761] 9. The terminal notifies the user and displays a report. The user (city hall employee) checks the analysis results and pricing proposal and uses them in making a final decision. Emotional data is also used as a reference for the final decision.

[0762] In this way, the system of the present invention sets efficient and appropriate fares for autonomous buses based on regional characteristics, and by taking user emotions into consideration, it becomes possible to set fares more adaptively.

[0763] The processing flow will be explained below.

[0764] Step 1:

[0765] Users input information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee might input "Machida City's population data" (3,000 elderly people, 7,000 young people) and "operation routes and fare information for Company A and Company B," then press the send button.

[0766] Step 2:

[0767] The device receives the information entered by the user, formats the data in an appropriate format (e.g., JSON), and sends the formatted data to the server using an HTTP POST request.

[0768] Step 3:

[0769] The server checks the received data and verifies that it is in the correct format. Once the data is verified, it connects to a database and saves or updates the information in the database. For example, the database records the population information, age distribution, and information about existing transport operators in the target area.

[0770] Step 4:

[0771] The server retrieves population information and age distribution for the target area from the database. Using Python's Pandas library, the server analyzes the population distribution and age structure. For example, it calculates that the proportion of elderly people is 30%.

[0772] Step 5:

[0773] The server retrieves information about existing transport operators from a database, uses a GIS (geographic information system) API to perform a geographic analysis of the routes, and performs statistical analysis of fare information and user numbers.

[0774] Step 6:

[0775] The server calculates the appropriate fee based on the acquired and analyzed data. For example, the fee for seniors may be set at 200 yen, and the fee for general users at 300 yen. This allows different fees to be calculated for each age group.

[0776] Step 7:

[0777] The server generates a detailed report of the generated fair fares in Markdown and HTML format, which is then converted to PDF format, and includes demographics, operator information, analysis results, and recommended fares.

[0778] Step 8:

[0779] The server collects user emotion data using an emotion engine. For example, if the user uses an emotion recognition device, the server acquires the user's emotional state (satisfied, dissatisfied, excited, etc.) in real time.

[0780] Step 9:

[0781] The server adjusts the content and presentation of the report based on the emotion data. For example, if the user is frustrated, it adjusts the tone of the report to provide a more understandable explanation.

[0782] Step 10:

[0783] The server sends the generated report to the terminal, which notifies the user when the report has been sent.

[0784] Step 11:

[0785] The device will notify the user via a pop-up notification or email that the report has been received. The user can view the report on the device and check the details. Emotional data will also be referenced and used as user feedback. The user (city hall employee) will use the report as reference material to determine the final pricing.

[0786] In this way, the system of the present invention sets efficient and appropriate fares for autonomous buses based on regional characteristics, and by taking user emotions into consideration, it becomes possible to set fares more adaptively.

[0787] Example 2

[0788] 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."

[0789] The current transportation fare system does not effectively utilize information on the local population structure, age distribution, or existing transportation operators, making it difficult to set fair and appropriate fares.Furthermore, the system does not take into account user emotions when setting fares or displaying reports, resulting in low user satisfaction.

[0790] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0791] In this invention, the server includes means for inputting population information for a target area, means for inputting the age distribution of the target area, means for inputting information about existing transportation operators, means for saving or updating the input information in a database, means for analyzing the population information and age distribution saved in the database, means for analyzing the information about transportation operators saved in the database, means for calculating an appropriate fare based on the analysis results, means for generating and presenting a detailed report of the appropriate fare, means for using an emotion engine to collect user emotion data, and means for applying the emotion data to fare setting and report display. This enables the transportation fare system to set appropriate fares and provide reports that take into account regional characteristics and user emotions.

[0792] "Target area" means a specific geographic area established for the purpose of collecting and analyzing population information, age distribution, and transportation operator information.

[0793] "Population information" refers to data that indicates the total number of people living in a particular area and their characteristics.

[0794] "Age distribution" refers to data that shows the proportion and composition of the population by age group living in a particular area.

[0795] A "transportation operator" is a company or organization that operates public transportation such as buses and trains.

[0796] A "database" is a system for organizing, efficiently storing, and managing information.

[0797] "Analysis" refers to the techniques used to examine collected data in detail and extract meaningful information.

[0798] "Fair fare" means a fair and reasonable fare that users can accept for the transportation services provided.

[0799] A "report" is a document that clearly presents the results of the analysis and recommendations.

[0800] "Emotion data" refers to information that quantifies the user's emotions and psychological state.

[0801] An "emotion engine" is a piece of software or hardware dedicated to collecting and analyzing users' emotional data.

[0802] "Pricing" refers to the process of determining prices for transportation services.

[0803] "Report display" refers to the visual presentation of a generated report to a user.

[0804] This invention combines an emotion engine with a system that collects and analyzes information on the population, age distribution, and existing transportation operators in the target area to set appropriate fares. This system is realized through the interaction of a server, terminals, and users.

[0805] Hardware and software used

[0806] server

[0807] The server handles all major processing, from data storage, analysis, billing, and report generation. The software that runs on the server includes:

[0808] Database management system (e.g. MySQL)

[0809] Data analysis tools (e.g., Python, Pandas, SciPy)

[0810] Geographic Information Systems (e.g. QGIS)

[0811] Emotion Recognition Software

[0812] Report generation tools (e.g., Markdown, HTML, PDF export)

[0813] Terminal

[0814] The terminal provides the interface for users to enter data and view and manipulate reports. Software running on the terminal includes:

[0815] A front-end framework that provides a form input screen (e.g., React, Angular)

[0816] API client to send and receive data

[0817] A viewer for displaying reports in the interface (e.g., a PDF viewer)

[0818] User

[0819] Users input the target area's population information, age distribution, and existing transport operators' information into the terminal, and then check the generated report. The devices used by users include regular PCs, tablets, and smartphones.

[0820] Data processing and calculation

[0821] 1. Data collection and input

[0822] The user inputs information about the target area into the terminal. For example, a city hall employee inputs the population data for Machida City (3,000 elderly people, 7,000 young people) and the route and fare information for existing bus operators A and B, and sends the data to the server.

[0823] 2. Sending and Receiving Data

[0824] The device formats the input information and sends it to the server, which receives the data and verifies that it is in the proper format.

[0825] 3. Updating the database

[0826] The server stores or updates the received data in the database: existing data is updated and new data is inserted.

[0827] 4. Analysis of Demographic and Age Data

[0828] The server retrieves population information from the database and analyzes the age distribution using Python's Pandas. Specifically, it confirms that elderly people account for 30% of the population.

[0829] 5. Analysis of existing bus operator information

[0830] The server uses GIS tools to analyze information such as bus operator routes and evaluate route overlaps and fare trends.

[0831] 6. Calculating the appropriate fee

[0832] The server calculates the appropriate fee based on the analysis results and runs a simulation to set the fee at 200 yen for the elderly and 300 yen for general users.

[0833] 7. Incorporating an Emotional Engine

[0834] The emotion engine collects user emotion data, for example, by using an emotion recognition device to capture the user's emotional state in real time and apply it to pricing and report display.

[0835] 8. Generating and Presenting Pricing Proposals

[0836] The server generates a detailed report on fair fares in Markdown and HTML formats, and finally sends it to the device in PDF format. The report includes demographics, transportation operator information, analysis results, and fare recommendations. The report presentation is adjusted based on sentiment data.

[0837] Specific example explanation

[0838] Specific examples of the present invention will be described below.

[0839] scenario

[0840] Target area: Machida City, Tokyo

[0841] Population: 10,000 (3,000 elderly, 7,000 young)

[0842] Existing bus operators: Company A and Company B

[0843] Operating Procedure

[0844] 1. The user (city hall employee) enters Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information for Company A and Company B into the terminal and presses the send button.

[0845] 2. The device formats the input information and sends it to the server.

[0846] 3. The server saves or updates the received data in the database.

[0847] 4. The server retrieves population information from the database and uses Pandas to analyze the age distribution. For example, it confirms that elderly people account for 30%.

[0848] 5. The server obtains bus operator information, analyzes bus routes using GIS, and analyzes existing fare structures and trends in ridership.

[0849] 6. Based on the analysis results, the server calculates the appropriate fees, which are set at 200 yen for elderly people and 300 yen for general users.

[0850] 7. The server generates a detailed report of the fair charges and sends it to the terminal in PDF format.

[0851] 8. The emotion engine collects user emotion data, and the server adjusts the report content and display method based on that data.

[0852] 9. The terminal notifies the user and displays a report. The user (city hall employee) checks the analysis results and pricing proposal and uses them in making a final decision. Emotional data is also used as a reference for the final decision.

[0853] In this way, the system of the present invention can realize efficient and appropriate pricing based on regional characteristics and user sentiment.

[0854] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0855] Step 1:

[0856] Data collection and input

[0857] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information of existing bus operators. The terminal formats this data and sends it to the server as JSON format data.

[0858] Input: population information of the target area, age distribution, transportation operator information

[0859] Output: Formatted JSON data

[0860] Step 2:

[0861] Sending and Receiving Data

[0862] The device sends the formatted data to the server via an HTTP POST request. The server receives this request and parses the data sent in JSON format. It checks whether the data is properly formatted and performs error handling if necessary.

[0863] Input: JSON format data

[0864] Output: Parsed data, error message (if needed)

[0865] Step 3:

[0866] Database Update

[0867] The server saves or updates the received data in a database. Existing data is updated and new data is inserted. For example, if population information already exists, it is updated, and if it does not exist, a new entry is added. MySQL or similar database management systems are used.

[0868] Input: Parsed data

[0869] Output: Updated or newly inserted database records

[0870] Step 4:

[0871] Analysis of population and age data

[0872] The server retrieves population information from the database and analyzes the age distribution using Python's Pandas. For example, it converts the population data into a data frame, groups it by the age column, and counts the number of people in each age group. This gives statistical information such as the fact that elderly people account for 30% of the total population.

[0873] Input: Population information retrieved from the database

[0874] Output: Age distribution analysis results

[0875] Step 5:

[0876] Analysis of existing bus operator information

[0877] The server retrieves information such as the routes, fare structures, and number of passengers of existing bus operators from the database and analyzes it using a GIS tool (e.g., QGIS). Specifically, it evaluates route overlaps and fare trends, and visualizes the number of passengers for each route using a heat map to identify areas with high demand.

[0878] Input: Transportation operator information obtained from the database

[0879] Output: Route analysis results using GIS, visualization of fare trends

[0880] Step 6:

[0881] Calculating fair fees

[0882] The server calculates the appropriate fare based on the analysis of population and transportation operator data. The pricing algorithm uses historical fare data and local economic indicators as inputs and uses Python's SciPy library to find the optimal fare through simulation. For example, the fare might be set at 200 yen for seniors and 300 yen for general users.

[0883] Input: Age distribution analysis results, transportation operator information analysis results

[0884] Output: Fair pricing results

[0885] Step 7:

[0886] Incorporating an emotion engine

[0887] The server uses an emotion engine to collect user emotion data. If the user is using an emotion recognition device (e.g., a facial recognition camera or biometric sensor), the emotion data is acquired in real time and applied to pricing and report display. For example, if the user is feeling stressed, the fee will be adjusted or the report display method will be changed.

[0888] Input: Emotion data obtained in real time from an emotion recognition device

[0889] Output: Emotion data analysis results

[0890] Step 8:

[0891] Generate and present pricing proposals

[0892] The server generates a detailed report on fair fares, which is then sent to the device in Markdown, HTML, and finally PDF format. The report includes demographics, operator information, analysis results, and fare recommendations. The report content and presentation are adjusted based on sentiment data.

[0893] Input: Results of appropriate pricing, analysis results of emotional data

[0894] Output: Generated report in PDF format

[0895] Step 9:

[0896] User Notification and Feedback

[0897] The device notifies the user of the report received from the server. The user can view the report on the device and check the details. For example, a notification message is displayed on the device, and the report can be opened by clicking the "View details" button. Feedback can also be sent to the server based on emotional data. For example, an interface is provided for rating satisfaction with the report.

[0898] Input: PDF report sent from the server

[0899] Output: User report viewing and feedback data

[0900] By using these detailed processing steps, the system of the present invention can realize efficient and appropriate pricing based on regional characteristics and user sentiment.

[0901] (Application example 2)

[0902] 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."

[0903] When setting fares for autonomous vehicles, it is necessary to realize more appropriate and flexible pricing by not only taking into account regional characteristics (population information and age distribution) but also by appropriately reflecting user emotional data. Furthermore, a method is needed to increase user satisfaction.

[0904] 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.

[0905] In this invention, the server includes means for inputting population information of the target area, means for inputting age distribution of the target area, and means for inputting information about existing transportation operators.

[0906] This will enable detailed analysis and pricing based on various data.

[0907] The system further includes means for collecting emotional data and reflecting the data in pricing and display, and means for adapting pricing using the user's emotional data.

[0908] This will enable flexible and appropriate pricing that takes into account the user's feelings, thereby improving user satisfaction.

[0909] "Population information for the target area" is statistical data on the total number, age, gender, etc. of people living in the area.

[0910] "Age distribution" is statistical data that classifies an unspecified number of people in a particular area by age.

[0911] "Information about transportation operators" refers to data on routes, fare structures, number of users, etc., of companies and organizations that provide transportation services.

[0912] A "database" is a collection of data that stores collected information and can be searched and updated as needed.

[0913] "Analysis results" are analytical results or conclusions obtained through statistical methods or calculations based on collected data.

[0914] A "fair price" is a price that is set based on the analysis results and is considered to be the most fair and reasonable price for each user.

[0915] "Emotion data" is information that indicates the user's current emotional state.

[0916] The "adaptive pricing mechanism" refers to a method or system for dynamically changing pricing in response to user emotional data.

[0917] The present invention is a system that collects and analyzes information on the population and age distribution of a target area, as well as information on existing transportation operators, and also reflects user emotional data in order to set appropriate fares for autonomous vehicles. Specific embodiments of this system are described below.

[0918] Hardware and Software Use

[0919] The system is constructed using smartphones, smart glasses, head-mounted displays, or robots as the server, terminal, and user interfaces. Python's Pandas is used for data analysis, and a geographic information system (GIS) is used for geographic information analysis. An appropriate emotion recognition engine is used to collect and analyze emotion data.

[0920] Data collection and input

[0921] The user, a city hall employee, inputs information about the target area's population, age distribution, and information about existing transportation operators into a terminal that serves as an interface. This data is sent from the terminal to a server and stored in a database. For example, this includes population data for Machida City and operation information for multiple bus operators.

[0922] Database Update

[0923] The server receives the data sent from the terminal and updates the database. After verifying that the data format is correct, new data is inserted or existing data is updated.

[0924] Data analysis

[0925] The server analyzes the population information and age distribution stored in the database using analytical tools such as Pandas. For example, it calculates the population percentage by age group and confirms that elderly people account for 30% of the total. It also analyzes information from transportation operators using a geographic information system (GIS) to evaluate trends in operation routes and user numbers.

[0926] Calculating fair fees

[0927] The server calculates the appropriate fee based on the analysis results. For example, it may set a fee of 200 yen for seniors and 300 yen for general users. Simulations are performed based on past fee data and regional economic indicators to determine the most appropriate fee setting.

[0928] Emotion engine integration

[0929] An emotion recognition device is used to collect real-time emotional data from users and send it to a server. The server analyzes the collected emotional data and reflects it in pricing and report display methods. For example, if the emotion is "happy," the system may adjust the fee slightly.

[0930] Generate and present pricing reports

[0931] The server generates a detailed report on fair pricing in Markdown or HTML format, and finally converts it to PDF format and sends it to the terminal. The user (city hall employee) can check the report on the terminal and use it to make a final decision.

[0932] Specific examples

[0933] For example, consider the following scenario in Machida City, Tokyo.

[0934] Target area: Machida City, Tokyo

[0935] Population: 10,000 (3,000 elderly, 7,000 young)

[0936] Existing bus operators: Multiple companies

[0937] City hall staff collect this information and enter it into a system that analyzes the data and calculates the appropriate fee.

[0938] Prompt Sentence Examples

[0939] Below is an example of an input prompt for a generative AI model.

[0940] Please calculate the appropriate fare for a self-driving bus in Machida City, Tokyo under the following conditions.

[0941] The total population is 10,000, of which 3,000 are elderly and 7,000 others.

[0942] There are multiple existing bus operators, each offering different routes.

[0943] Apply discounts for seniors to fair fares and also reflect emotional data.

[0944] In this way, the system of the present invention realizes efficient and fair pricing while taking into consideration regional characteristics and user sentiment.

[0945] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0946] Step 1:

[0947] The user (city hall employee) inputs population information, age distribution, and operation information of existing transportation operators for the target area into the terminal.

[0948] Input: Population information, age distribution, transportation operator operation data

[0949] Output: Formatted data

[0950] Specific operation: Through the interface, users input information about the population and age distribution of each region, as well as the routes and fares of each transportation company.

[0951] Step 2:

[0952] The device formats the input information and sends it to the server.

[0953] Input: User-entered population information, age distribution, and transportation operator operation data

[0954] Output: Formatted data sent to the server

[0955] Specific operation: The terminal standardizes the input data, converts it into CSV or JSON format, and sends it to the server.

[0956] Step 3:

[0957] The server saves or updates the received data in the database.

[0958] Input: Formatted data

[0959] Output: Information stored in the database

[0960] What happens: The server validates the format of the data and inserts new data or updates existing data in the database.

[0961] Step 4:

[0962] The server retrieves and analyzes demographic information and age distribution from the database.

[0963] Input: Population information and age distribution stored in a database

[0964] Output: Demographic data by age group

[0965] Specific operation: The server uses analytical tools such as Pandas to calculate the population percentage of each age group. For example, it calculates that the elderly make up 30% of the total population.

[0966] Step 5:

[0967] The server analyzes the transportation company's routes and number of users.

[0968] Input: Transport operator operation data stored in a database

[0969] Output: Statistical data on number of users by route

[0970] Specific operation: The server uses a geographic information system (GIS) to analyze trends in each route and the number of passengers.

[0971] Step 6:

[0972] The server calculates the appropriate fee based on the analysis results.

[0973] Input: Demographic data, transportation operator ridership data

[0974] Output: Proposed pricing

[0975] Specific operation: The server performs simulations based on past fee data and local economic indicators to calculate the optimal fee. For example, it may set the fee at 200 yen for seniors and 300 yen for general users.

[0976] Step 7:

[0977] The server collects sentiment data and incorporates it into pricing and reporting.

[0978] Input: Real-time emotion data from emotion recognition device

[0979] Output: Pricing reflecting sentiment data

[0980] Specific operation: Based on the emotional data, if the user is in a "happy" state, the system will adapt, such as reducing the general user fee by 10 yen.

[0981] Step 8:

[0982] The server generates a detailed report of the fair charges and sends it to the terminal.

[0983] Input: Data analysis results, sentiment data, pricing

[0984] Output: Detailed report in PDF format

[0985] Specific operation: The server generates a detailed report in Markdown or HTML format, and finally converts it to PDF format and sends it to the terminal. The user (city hall employee) checks the report on the terminal and uses it for final decision making.

[0986] 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.

[0987] 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.

[0988] 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.

[0989] [Third embodiment]

[0990] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0991] 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.

[0992] 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).

[0993] 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.

[0994] 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.

[0995] 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).

[0996] 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. 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.

[0997] 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.

[0998] 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.

[0999] 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.

[1000] 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.

[1001] 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."

[1002] This invention relates to a system that collects and analyzes information on the population, age distribution, and existing transportation operators of a target area, and then sets appropriate fares. This system is realized through the interaction of a server, terminals, and users.

[1003] System configuration and operation

[1004] 1. Data collection and input

[1005] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs data for Machida City and presses the send button, sending this information to the server. The terminal then formats the input information and sends it to the server as data.

[1006] 2. Updating the database

[1007] The server validates the data received from the device and stores or updates it in its internal database. After receiving the data, the server validates its format, connects to the database, and updates existing information or inserts new data.

[1008] 3. Demographic and Age Data Analysis

[1009] The server analyzes the population distribution and age structure of the target area. The server retrieves population data from the database and analyzes this data using analytical tools such as Python's Pandas. For example, it performs a statistical analysis to determine that Machida City has a large elderly population and that the elderly make up 30% of the total population.

[1010] 4. Analysis of existing bus operator information

[1011] The server analyzes the routes, fare structures, and ridership numbers of existing transport operators. The server retrieves bus operator information from a database and evaluates trends in routes and ridership numbers using a geographic information system (GIS) and other analytical tools.

[1012] 5. Calculating the appropriate fee

[1013] The server calculates the appropriate fare based on the analysis results. For example, it might set a fare of 200 yen for seniors and 300 yen for general users. The server uses past fare data and local economic indicators to calculate the most appropriate bus fare through simulation.

[1014] 6. Generating and Presenting Pricing Proposals

[1015] The server generates a detailed report on fair pricing and sends it to the device. The report is generated in Markdown or HTML format, converted to PDF, and securely sent. The device notifies the user that a fair pricing proposal has been generated and displays the report. The user can review the details of the report and make a final pricing decision based on it.

[1016] Specific example explanation

[1017] A specific example is shown below.

[1018] scenario

[1019] Target area: Machida City, Tokyo

[1020] Population: 10,000 (3,000 elderly, 7,000 young)

[1021] Existing bus operators: Company A and Company B

[1022] Operating Procedure

[1023] 1. The user (city hall employee) enters Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information for Company A and Company B into the terminal and presses the send button.

[1024] 2. The device formats the input information and sends it to the server.

[1025] 3. The server saves or updates the received data in the database.

[1026] 4. The server retrieves population information from the database and analyzes it. For example, it uses Pandas to analyze the age distribution and finds that elderly people account for 30%.

[1027] 5. The server obtains bus operator information, analyzes bus routes using GIS, and analyzes existing fare structures and trends in user numbers.

[1028] 6. Based on the analysis results, the server calculates the appropriate fees, which are set at 200 yen for elderly people and 300 yen for general users.

[1029] 7. The server generates a detailed report of the fair charges and sends it to the terminal in PDF format.

[1030] 8. The terminal notifies the user and displays a report. The user (city hall employee) checks the analysis results and fee proposals and uses them in making a final decision.

[1031] In this way, the system of the present invention makes it possible to efficiently set optimal fares for autonomous buses in a target area.

[1032] The processing flow will be explained below.

[1033] Step 1:

[1034] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, they input "population information for Machida City, Tokyo" and "operation routes and fare information for Company A and Company B." Once the input is complete, they press the send button.

[1035] Step 2:

[1036] The device receives the information entered by the user, formats the data in an appropriate format (e.g., JSON), and sends the formatted data to the server using an HTTP POST request.

[1037] Step 3:

[1038] The server then checks the data received and verifies that it is in the correct format. Once the data has been validated, it connects to a database and saves or updates the information in the database. The saved data includes the area's population information, age distribution, and information about existing transport operators.

[1039] Step 4:

[1040] The server retrieves population information and age distribution for the target area from the database. Using the retrieved data, it analyzes the population distribution and age structure using Python's Pandas library, for example. For example, it calculates the proportion of elderly people and identifies the characteristics of age groups specific to that area.

[1041] Step 5:

[1042] The server retrieves information about existing transportation operators from a database. It uses a GIS (geographic information system) API to perform a geographic analysis of the routes. It also performs statistical analysis of fare information and ridership numbers to evaluate trends in existing fare structures and ridership numbers.

[1043] Step 6:

[1044] The server calculates appropriate fees based on the acquired and analyzed data. For example, it calculates different fees for different age groups, such as setting a fee of 200 yen for seniors and 300 yen for general users. It also references past fee data and regional economic indicators to create an optimal fee model.

[1045] Step 7:

[1046] The server generates a detailed report of the calculated fair fares in Markdown and HTML formats, and finally in PDF format, including demographics, transit operator information, analysis results, and recommended fares.

[1047] Step 8:

[1048] The server sends the generated report to the terminal, which notifies the user when the report has been sent.

[1049] Step 9:

[1050] The terminal notifies the user that the report has been received via a pop-up notification or email. The user can view the report on the terminal and check the details. The user (city hall employee) uses the report as reference material to determine the final fee setting.

[1051] In this way, the system of the present invention sets efficient and appropriate fares for autonomous buses based on regional characteristics.

[1052] Example 1

[1053] 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."

[1054] In modern society, changes in demographics and fluctuations in transportation operator operating conditions require the establishment of appropriate fares. However, existing systems often lack reliability and accuracy in fare setting due to insufficient analysis of population distribution and age groups, or the collection and analysis of information on existing transportation operators. Furthermore, the generation and presentation of detailed reports on appropriate fares based on the analysis results is not automated, which can lead to manual errors and time-consuming work. Therefore, there is a need for the development of a system that can efficiently collect and analyze data on population information, age distribution, and existing transportation operators, and automatically calculate appropriate fares.

[1055] 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.

[1056] In this invention, the server includes a means for formatting population data and transportation operator information for the target area and sending it to the server, a means for verifying the format of the received data and saving or updating it in an internal database, and a means for utilizing data analysis tools to analyze the population distribution and age structure of the target area. This enables rapid analysis of population distribution and age structure and accurate evaluation of transportation operator operation information. Furthermore, a detailed report of appropriate fares can be automatically generated and presented, improving the reliability and efficiency of fare setting.

[1057] "Area of ​​Interest" means the specific geographic area that is the subject of an analysis or calculation.

[1058] "Population information" refers to statistical information such as the total number of residents in the target area, their gender, and their age group.

[1059] "Age distribution" refers to data showing the age structure of residents in the target area.

[1060] "Transportation operator" means a company or organization that operates public transportation such as buses and trains.

[1061] "Database" refers to a system for organizing, storing, efficiently retrieving, and updating information.

[1062] "Formatting" refers to the process of unifying the data format and making it consistent.

[1063] "Analysis" refers to the process of evaluating collected data and making sense of it.

[1064] "Data analysis tools" refers to software for analyzing collected data and performing statistical evaluations.

[1065] "Geographic Information System (GIS)" means a system for collecting, managing, analyzing, and visualizing geographic information.

[1066] "Fair rates" refer to rates that are calculated based on the analysis results and are considered fair and reasonable for users.

[1067] "Report" means a document summarizing the results of analysis or calculations.

[1068] This invention relates to a system that collects and analyzes information on the population, age distribution, and existing transportation operators of a target area, and then sets appropriate fares. This system is realized through the interaction of a server, terminals, and users.

[1069] Data collection and input

[1070] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information of Company A and Company B into the terminal, and then presses the send button. This operation completes the data input process.

[1071] Data transmission and preprocessing

[1072] The terminal formats the information entered by the user, converts it to JSON format, and sends it to the server. The HTTPS protocol is used for data transmission, ensuring secure data transmission. The server temporarily stores the received data in memory, checks the format, and performs preprocessing.

[1073] Database Update

[1074] The server validates the pre-processed data and saves or updates it in an internal database. Specifically, the server validates the format of the incoming data, connects to the database (e.g., MySQL or PostgreSQL), and updates existing information or inserts new data. During this process, the server uses transactions to ensure data consistency.

[1075] Population and age data analysis

[1076] The server analyzes the population distribution and age structure of the target area. Specifically, it retrieves population data from the database and performs statistical analysis using Python's Pandas library. For example, it confirms that Machida City has a high elderly population and outputs analysis results such as elderly people making up 30% of the total population.

[1077] Analysis of existing bus operator information

[1078] The server analyzes the routes, fare structures, and number of users of existing transportation operators. Specifically, it retrieves bus operator information from a database and visualizes and analyzes route data using geographic information system (GIS) software (ArcGIS or QGIS). It also graphs and evaluates trends in fare structures and user numbers using Python's Matplotlib and Seaborn.

[1079] Calculating fair fees

[1080] The server calculates the appropriate fee based on the analysis results. The server references past fee data and local economic indicators and executes algorithms to perform simulations. For example, it uses regression analysis to calculate the appropriate fee of 200 yen for the elderly and 300 yen for general users. These calculations are performed using Python's Scikit-learn library.

[1081] Generate and present reports

[1082] The server generates a detailed report on fair pricing and sends it to the device. Specifically, the report is generated in Markdown or HTML format and then converted to PDF format. The generated PDF is attached to an email or sent to the device via a secure channel. The device notifies the user of the analysis results and pricing proposals and displays the report. The user can then make a final pricing decision based on the report.

[1083] Prompt Sentence Examples

[1084] "Calculate the appropriate fares for the transportation business based on Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information for companies A and B. Then, referencing various statistical data and regional economic indicators, generate a report proposing a fare of 200 yen for elderly people and 300 yen for general users."

[1085] By using the system of the present invention, it is possible to efficiently set fares for autonomous buses that are optimal for the target area, contributing to improving the efficiency and convenience of local transportation.

[1086] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1087] Program processing flow

[1088] Step 1: Data collection and entry

[1089] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs population data for Machida City, such as 3,000 elderly people and 7,000 young people, as well as route and fare information for companies A and B, into the terminal, confirms the input data, and then presses the send button. This sends the information entered by the user to the terminal, where it is formatted and prepared for transmission.

[1090] Input: population information of the target area, age distribution, transportation operator information

[1091] Output: The formatted input data

[1092] Step 2: Data transmission and preprocessing

[1093] The terminal converts the information entered by the user into JSON format and sends it to the server using HTTPS. The server temporarily stores the received data in memory and verifies whether the data format is correct. For example, if the data format is correct, the formatted data is prepared for storage on the server.

[1094] Input: Formatted input data

[1095] Output: Data sent to the server

[1096] Step 3: Update the database

[1097] The server saves or updates the received data in an internal database (for example, MySQL or PostgreSQL). If the same information already exists, the corresponding record is updated, and if not, a new record is inserted. Data consistency is maintained through transaction management.

[1098] Input: Data sent to the server

[1099] Output: Data saved or updated in the database

[1100] Step 4: Population and age data analysis

[1101] The server retrieves population data from the database and performs statistical analysis using Python's Pandas library, such as calculating the ratio of elderly to young people and finding that elderly people account for 30% of the total population in Machida City.

[1102] Input: Population data retrieved from the database

[1103] Output: Statistical analysis results (e.g., elderly people account for 30% of the total)

[1104] Step 5: Analyze existing bus operator information

[1105] The server retrieves bus operator information from the database and uses GIS tools (such as ArcGIS or QGIS) to visualize and analyze routes. It also uses Python's Matplotlib and Seaborn to graph and evaluate trends in fare structures and ridership. For example, it can conclude that Company A has more riders than Company B, but its fares are higher, so it needs to review its pricing.

[1106] Input: Bus operator information retrieved from the database

[1107] Output: Visualization of operation routes using GIS, evaluation of fare structures and trends in number of users

[1108] Step 6: Calculate the fair price

[1109] The server calculates the appropriate fee based on the analysis results. It sets the fee using regression analysis, referencing past fee data and regional economic indicators. For example, it calculates a fee of 200 yen for the elderly and 300 yen for general users through simulation.

[1110] Input: Analysis results, historical pricing data, local economic indicators

[1111] Output: Fair fee calculation result

[1112] Step 7: Generate and present the report

[1113] The server generates a detailed report on fair pricing in Markdown or HTML format, converts it to PDF format, and sends it to the terminal. The terminal notifies the user of the received PDF and displays the report so that the user can review it. The user then determines the final pricing based on the analysis results and pricing proposals.

[1114] Input: Calculation result of fair fee

[1115] Output: Generated report (PDF format), notification to user

[1116] By following the above steps, this system can automate and efficiently set optimal rates for the target area.

[1117] (Application example 1)

[1118] 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."

[1119] Conventional pricing systems for autonomous vehicles do not fully consider the population information and age distribution of the target area, or information on existing transportation operators, making it difficult to calculate appropriate fares. Furthermore, there was no efficient system for collecting and analyzing this information, making operation cumbersome. Furthermore, there was a need to present the analysis results in a user-friendly format.

[1120] 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.

[1121] In this invention, the server includes: means for inputting population information for a target area; means for inputting age distribution for the target area; means for inputting information about existing transportation operators; means for saving or updating the input information in a database; means for analyzing the population information and age distribution saved in the database; means for analyzing information about transportation operators saved in the database; means for calculating an appropriate fare to display on a smartphone, smart glasses, or head-mounted display; means for generating and presenting a detailed report of the appropriate fare; means for using a generative AI model to generate a report of analysis results regarding fare setting for autonomous vehicles; and means for using a generative AI model to generate a prompt message for an appropriate fare based on the analysis results. This enables efficient and accurate fare setting that takes into account the population information, age distribution, and information about existing transportation operators for the target area.

[1122] A "target area" is an area for which specific population information, age distribution, and transportation operator information are analyzed.

[1123] "Population information" is data on the number and distribution of people living in a target area.

[1124] "Age distribution" is information that shows the proportion of the population of various age groups in the target area.

[1125] "Transportation operator information" is data related to transportation such as buses that operate within the target area.

[1126] "Database" means a system for storing or updating collected population information, age distribution, and transportation operator information.

[1127] "Analysis methods" are methods for analyzing population distribution and transportation company routes based on information stored in the database.

[1128] The "fair fare calculation method" is a method for calculating fair fares for autonomous vehicles based on the results of an analysis of population information, age distribution, and transportation operator information.

[1129] The "report generation means" is a method for generating a detailed report of the calculation results of the fair fee and related information, and presenting it to the user.

[1130] A "smartphone" is a mobile device that combines the functions of a mobile phone and a computer.

[1131] "Smart glasses" are eyeglass-shaped wearable devices that have the function of displaying information.

[1132] A "head-mounted display" is a display device worn on the head, and is a device that has the function of displaying digital information in the field of vision.

[1133] A "generative AI model" is a system that uses artificial intelligence (AI) to analyze data and automatically generate effective pricing calculations and reports.

[1134] A "prompt" is an instruction generated by an AI model to present appropriate pricing and related information.

[1135] MODE FOR CARRYING OUT THE INVENTION

[1136] The embodiment of the present invention is a system that collects and analyzes information on the population, age distribution, and existing transportation operators of a target area to set appropriate fares. This system is realized through the interaction of a server, terminals, and users.

[1137] System configuration and operation

[1138] 1. Data collection and input

[1139] Users use a smartphone, smart glasses, or head-mounted display to input information about the target area's population, age distribution, and existing transportation operators. For example, a government official inputs data for a city and presses the send button, which sends the information to the server. The device then formats the input information and sends it to the server as data.

[1140] 2. Updating the database

[1141] The server checks the data received from the device and saves or updates it in its internal database. After receiving the data, the server verifies its format, connects to the database, and updates existing information or inserts new data. This database uses SQLite.

[1142] 3. Demographic and Age Data Analysis

[1143] The server analyzes the population distribution and age structure of the target area. The server retrieves population data from the database and analyzes this data using analytical tools such as Python's Pandas. For example, it performs statistical analysis to determine that there are many elderly people in a particular area and that the elderly make up 30% of the total population.

[1144] 4. Analysis of existing bus operator information

[1145] The server analyzes the routes, fare structures, and ridership numbers of existing transport operators. The server retrieves information about transport operators from a database and evaluates trends in routes and ridership numbers using a geographic information system (GIS) and other analytical tools.

[1146] 5. Calculating the appropriate fee

[1147] The server calculates the appropriate fee based on the analysis results. For example, it may set the fee at 200 yen for seniors and 300 yen for general users. The server calculates the most appropriate fee through simulations based on past fee data and local economic indicators.

[1148] 6. Generating and Presenting Pricing Proposals

[1149] The server generates a detailed report on fair pricing and sends it to the device. The report is generated in Markdown or HTML format and sent securely. The device notifies the user that fair pricing suggestions have been generated and displays the report. Using a generative AI model, fair pricing prompts are also generated to make the report user-friendly.

[1150] Hardware and software used

[1151] Hardware: Standard servers (e.g. AWS, Google Cloud), smartphones, smart glasses, head-mounted displays

[1152] Software: Python (Pandas, GeoPandas), SQLite, generative AI models

[1153] Specific examples

[1154] scenario:

[1155] Target area: A city

[1156] Population: 50,000 (15,000 elderly, 35,000 young)

[1157] Existing bus operators: Transportation companies A and B

[1158] Operation steps:

[1159] 1. An administrative official enters the city's population data (15,000 elderly people, 35,000 young people) and the route and fare information for companies A and B into the terminal and presses the send button.

[1160] 2. The device formats the input information and sends it to the server.

[1161] 3. The server saves or updates the received data in the database.

[1162] 4. The server retrieves population information from the database, analyzes the age distribution using Pandas, and confirms that elderly people account for 30%.

[1163] 5. The server obtains transportation operator information, analyzes routes using GeoPandas, and analyzes existing fare structures and trends in ridership.

[1164] 6. Based on the analysis results, the server calculates the appropriate fees, which are set at 200 yen for elderly people and 300 yen for general users.

[1165] 7. The server generates a detailed report of the fair charges and sends it to the terminal in PDF format.

[1166] 8. The device notifies the user and displays a report, and also generates prompts regarding fair pricing using a generative AI model.

[1167] Example prompt sentence:

[1168] "Use generative AI to analyze the appropriate fare for a city's autonomous buses. Consider the following data:

[1169] Population data (e.g., 15,000 elderly people, 35,000 young people)

[1170] Route and fare information for existing bus operators

[1171] As a result of the analysis, please calculate the appropriate fees for elderly people and general users and create a detailed report. For example, set the fees at 200 yen for elderly people and 300 yen for general users.

[1172] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1173] Step 1:

[1174] Entering and Submitting Data

[1175] The user uses a smartphone, smart glasses, or head-mounted display to input information about the target area's population, age distribution, and information about existing transportation operators into the terminal and presses the send button. At this time, the input information is formatted in JSON format or similar. The input data (population information, age distribution, transportation operator information) from the terminal is sent to the server.

[1176] Input: population information of the target area, age distribution, transportation operator information

[1177] Output: Send formatted data to the server

[1178] Step 2:

[1179] Save or update to database

[1180] The server checks the data received from the device and stores or updates it in its internal database. The server first verifies the format of the received data, then connects to the SQLite database to update existing information or insert new data.

[1181] Input: Data received from the device (JSON format population information, age distribution, transportation operator information)

[1182] Output: Database update status

[1183] Step 3:

[1184] Analysis of population and age data

[1185] The server retrieves population information and age distributions from the database and analyzes this data using Python's Pandas library, calculating the population percentage for each age group and analyzing, for example, what percentage of the population is elderly.

[1186] Input: Population information and age distribution obtained from the database

[1187] Output: Population percentage by age group (e.g., 30% elderly)

[1188] Step 4:

[1189] Analysis of transportation operator information

[1190] The server retrieves the transportation operator's route, fare structure, and number of users from the database and performs geographic information analysis using libraries such as GeoPandas, thereby analyzing route efficiency and user trends.

[1191] Input: Transport operator information obtained from the database (operation route, fare structure, number of users)

[1192] Output: Route efficiency, ridership trends

[1193] Step 5:

[1194] Calculating fair fees

[1195] The server calculates appropriate fares based on the analysis of population information, age distribution, and transportation company operation information. For example, it simulates and sets fares of 200 yen for seniors and 300 yen for general users. Fares are set more precisely using a generative AI model.

[1196] Input: Analysis results of population information, age distribution, and transportation company operation information

[1197] Output: Reasonable fee (200 yen for seniors, 300 yen for general users)

[1198] Step 6:

[1199] Generate and present pricing proposals

[1200] The server generates a detailed report on fair pricing and sends it to the device. The report is generated in Markdown or HTML format and then converted to PDF. The device notifies the user and displays the report. Additionally, a generative AI model is used to generate prompts based on the analysis results.

[1201] Input: Calculation result of fair fee

[1202] Output: Detailed report (PDF format), prompt statement

[1203] Examples:

[1204] Example prompt sentence:

[1205] "Use generative AI to analyze the appropriate fare for a city's autonomous buses. Consider the following data:

[1206] Population data (e.g., 15,000 elderly people, 35,000 young people)

[1207] Route and fare information for existing bus operators

[1208] As a result of the analysis, please calculate the appropriate fees for elderly people and general users and create a detailed report. For example, set the fees at 200 yen for elderly people and 300 yen for general users.

[1209] 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.

[1210] This invention combines an emotion engine with a system that collects and analyzes information on the population, age distribution, and existing transportation operators in the target area to set appropriate fares. This system is realized through the interaction of servers, terminals, and users.

[1211] System configuration and operation

[1212] 1. Data collection and input

[1213] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs data for Machida City and presses the send button, sending this information to the server. The terminal then formats the input information and sends it to the server as data.

[1214] 2. Updating the database

[1215] The server validates the data received from the device and stores or updates it in its internal database. After receiving the data, the server validates its format, connects to the database, and updates existing information or inserts new data.

[1216] 3. Demographic and Age Data Analysis

[1217] The server analyzes the population distribution and age structure of the target area. The server retrieves population data from the database and analyzes this data using analytical tools such as Python's Pandas. For example, it performs a statistical analysis to determine that Machida City has a large elderly population and that the elderly make up 30% of the total population.

[1218] 4. Analysis of existing bus operator information

[1219] The server analyzes the routes, fare structures, and ridership numbers of existing transport operators. The server retrieves bus operator information from a database and evaluates trends in routes and ridership numbers using a geographic information system (GIS) and other analytical tools.

[1220] 5. Calculating the appropriate fee

[1221] The server calculates the appropriate fare based on the analysis results. For example, it might set a fare of 200 yen for seniors and 300 yen for general users. The server uses past fare data and local economic indicators to calculate the most appropriate bus fare through simulation.

[1222] 6. Incorporating an Emotional Engine

[1223] In the present invention, an emotion engine is used to collect user emotion data and apply the data to pricing and report display, for example, by collecting emotion data in real time when a user is using an emotion recognition device.

[1224] 7. Generating and Presenting Pricing Proposals

[1225] The server generates a detailed report on fair fares in Markdown and HTML formats, and finally in PDF format. The report includes demographics, operator information, analysis results, and fare recommendations. The report's content and presentation can be tailored based on data from the sentiment engine.

[1226] 8. User Notification and Feedback

[1227] The server sends the generated report to the device. Once the report has been sent, the device notifies the user. The user can view the report on the device and check the details. If emotion data has been collected, it can also be used as user feedback.

[1228] Specific example explanation

[1229] A specific example is shown below.

[1230] scenario

[1231] Target area: Machida City, Tokyo

[1232] Population: 10,000 (3,000 elderly, 7,000 young)

[1233] Existing bus operators: Company A and Company B

[1234] Operating Procedure

[1235] 1. The user (city hall employee) enters Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information for Company A and Company B into the terminal and presses the send button.

[1236] 2. The device formats the input information and sends it to the server.

[1237] 3. The server saves or updates the received data in the database.

[1238] 4. The server retrieves population information from the database and analyzes it. For example, it uses Pandas to analyze the age distribution and finds that elderly people account for 30% of the population.

[1239] 5. The server obtains bus operator information, analyzes bus routes using GIS, and analyzes existing fare structures and trends in user numbers.

[1240] 6. Based on the analysis results, the server calculates the appropriate fees, which are set at 200 yen for elderly people and 300 yen for general users.

[1241] 7. The server generates a detailed report of the fair charges and sends it to the terminal in PDF format.

[1242] 8. The emotion engine collects user emotion data, and the server uses that data to adjust the content and presentation of the report.

[1243] 9. The terminal notifies the user and displays a report. The user (city hall employee) checks the analysis results and pricing proposal and uses them in making a final decision. Emotional data is also used as a reference for the final decision.

[1244] In this way, the system of the present invention sets efficient and appropriate fares for autonomous buses based on regional characteristics, and by taking user emotions into consideration, it becomes possible to set fares more adaptively.

[1245] The processing flow will be explained below.

[1246] Step 1:

[1247] Users input information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee might input "Machida City's population data" (3,000 elderly people, 7,000 young people) and "operation routes and fare information for Company A and Company B," then press the send button.

[1248] Step 2:

[1249] The device receives the information entered by the user, formats the data in an appropriate format (e.g., JSON), and sends the formatted data to the server using an HTTP POST request.

[1250] Step 3:

[1251] The server checks the received data and verifies that it is in the correct format. Once the data is verified, it connects to a database and saves or updates the information in the database. For example, the database records the population information, age distribution, and information about existing transport operators in the target area.

[1252] Step 4:

[1253] The server retrieves population information and age distribution for the target area from the database. Using Python's Pandas library, the server analyzes the population distribution and age structure. For example, it calculates that the proportion of elderly people is 30%.

[1254] Step 5:

[1255] The server retrieves information about existing transport operators from a database, uses a GIS (geographic information system) API to perform a geographic analysis of the routes, and performs statistical analysis of fare information and user numbers.

[1256] Step 6:

[1257] The server calculates the appropriate fee based on the acquired and analyzed data. For example, the fee for seniors may be set at 200 yen, and the fee for general users at 300 yen. This allows different fees to be calculated for each age group.

[1258] Step 7:

[1259] The server generates a detailed report of the generated fair fares in Markdown and HTML format, which is then converted to PDF format, and includes demographics, operator information, analysis results, and recommended fares.

[1260] Step 8:

[1261] The server collects user emotion data using an emotion engine. For example, if the user uses an emotion recognition device, the server acquires the user's emotional state (satisfied, dissatisfied, excited, etc.) in real time.

[1262] Step 9:

[1263] The server adjusts the content and presentation of the report based on the emotion data. For example, if the user is frustrated, it adjusts the tone of the report to provide a more understandable explanation.

[1264] Step 10:

[1265] The server sends the generated report to the terminal, which notifies the user when the report has been sent.

[1266] Step 11:

[1267] The device will notify the user via a pop-up notification or email that the report has been received. The user can view the report on the device and check the details. Emotional data will also be referenced and used as user feedback. The user (city hall employee) will use the report as reference material to determine the final pricing.

[1268] In this way, the system of the present invention sets efficient and appropriate fares for autonomous buses based on regional characteristics, and by taking user emotions into consideration, it becomes possible to set fares more adaptively.

[1269] Example 2

[1270] 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."

[1271] The current transportation fare system does not effectively utilize information on the local population structure, age distribution, or existing transportation operators, making it difficult to set fair and appropriate fares.Furthermore, the system does not take into account user emotions when setting fares or displaying reports, resulting in low user satisfaction.

[1272] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1273] In this invention, the server includes means for inputting population information for a target area, means for inputting the age distribution of the target area, means for inputting information about existing transportation operators, means for saving or updating the input information in a database, means for analyzing the population information and age distribution saved in the database, means for analyzing the information about transportation operators saved in the database, means for calculating an appropriate fare based on the analysis results, means for generating and presenting a detailed report of the appropriate fare, means for using an emotion engine to collect user emotion data, and means for applying the emotion data to fare setting and report display. This enables the transportation fare system to set appropriate fares and provide reports that take into account regional characteristics and user emotions.

[1274] "Target area" means a specific geographic area established for the purpose of collecting and analyzing population information, age distribution, and transportation operator information.

[1275] "Population information" refers to data that indicates the total number of people living in a particular area and their characteristics.

[1276] "Age distribution" refers to data that shows the proportion and composition of the population by age group living in a particular area.

[1277] A "transportation operator" is a company or organization that operates public transportation such as buses and trains.

[1278] A "database" is a system for organizing, efficiently storing, and managing information.

[1279] "Analysis" refers to the techniques used to examine collected data in detail and extract meaningful information.

[1280] "Fair fare" means a fair and reasonable fare that users can accept for the transportation services provided.

[1281] A "report" is a document that clearly presents the results of the analysis and recommendations.

[1282] "Emotion data" refers to information that quantifies the user's emotions and psychological state.

[1283] An "emotion engine" is a piece of software or hardware dedicated to collecting and analyzing users' emotional data.

[1284] "Pricing" refers to the process of determining prices for transportation services.

[1285] "Report display" refers to the visual presentation of a generated report to a user.

[1286] This invention combines an emotion engine with a system that collects and analyzes information on the population, age distribution, and existing transportation operators in the target area to set appropriate fares. This system is realized through the interaction of a server, terminals, and users.

[1287] Hardware and software used

[1288] server

[1289] The server handles all major processing, from data storage, analysis, billing, and report generation. The software that runs on the server includes:

[1290] Database management system (e.g. MySQL)

[1291] Data analysis tools (e.g., Python, Pandas, SciPy)

[1292] Geographic Information Systems (e.g. QGIS)

[1293] Emotion Recognition Software

[1294] Report generation tools (e.g., Markdown, HTML, PDF export)

[1295] Terminal

[1296] The terminal provides the interface for users to enter data and view and manipulate reports. Software running on the terminal includes:

[1297] A front-end framework that provides a form input screen (e.g., React, Angular)

[1298] API client to send and receive data

[1299] A viewer for displaying reports in the interface (e.g., a PDF viewer)

[1300] User

[1301] Users input the target area's population information, age distribution, and existing transport operators' information into the terminal, and then check the generated report. The devices used by users include regular PCs, tablets, and smartphones.

[1302] Data processing and calculation

[1303] 1. Data collection and input

[1304] The user inputs information about the target area into the terminal. For example, a city hall employee inputs the population data for Machida City (3,000 elderly people, 7,000 young people) and the route and fare information for existing bus operators A and B, and sends the data to the server.

[1305] 2. Sending and Receiving Data

[1306] The device formats the input information and sends it to the server, which receives the data and verifies that it is in the proper format.

[1307] 3. Updating the database

[1308] The server stores or updates the received data in the database: existing data is updated and new data is inserted.

[1309] 4. Analysis of Demographic and Age Data

[1310] The server retrieves population information from the database and analyzes the age distribution using Python's Pandas. Specifically, it confirms that elderly people account for 30% of the population.

[1311] 5. Analysis of existing bus operator information

[1312] The server uses GIS tools to analyze information such as bus operator routes and evaluate route overlaps and fare trends.

[1313] 6. Calculating the appropriate fee

[1314] The server calculates the appropriate fee based on the analysis results and runs a simulation to set the fee at 200 yen for the elderly and 300 yen for general users.

[1315] 7. Incorporating an Emotional Engine

[1316] The emotion engine collects user emotion data, for example, by using an emotion recognition device to capture the user's emotional state in real time and apply it to pricing and report display.

[1317] 8. Generating and Presenting Pricing Proposals

[1318] The server generates a detailed report on fair fares in Markdown and HTML formats, and finally sends it to the device in PDF format. The report includes demographics, transportation operator information, analysis results, and fare recommendations. The report presentation is adjusted based on sentiment data.

[1319] Specific example explanation

[1320] Specific examples of the present invention will be described below.

[1321] scenario

[1322] Target area: Machida City, Tokyo

[1323] Population: 10,000 (3,000 elderly, 7,000 young)

[1324] Existing bus operators: Company A and Company B

[1325] Operating Procedure

[1326] 1. The user (city hall employee) enters Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information for Company A and Company B into the terminal and presses the send button.

[1327] 2. The device formats the input information and sends it to the server.

[1328] 3. The server saves or updates the received data in the database.

[1329] 4. The server retrieves population information from the database and uses Pandas to analyze the age distribution. For example, it confirms that elderly people account for 30%.

[1330] 5. The server obtains bus operator information, analyzes bus routes using GIS, and analyzes existing fare structures and trends in ridership.

[1331] 6. Based on the analysis results, the server calculates the appropriate fees, which are set at 200 yen for elderly people and 300 yen for general users.

[1332] 7. The server generates a detailed report of the fair charges and sends it to the terminal in PDF format.

[1333] 8. The emotion engine collects user emotion data, and the server adjusts the report content and display method based on that data.

[1334] 9. The terminal notifies the user and displays a report. The user (city hall employee) checks the analysis results and pricing proposal and uses them in making a final decision. Emotional data is also used as a reference for the final decision.

[1335] In this way, the system of the present invention can realize efficient and appropriate pricing based on regional characteristics and user sentiment.

[1336] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1337] Step 1:

[1338] Data collection and input

[1339] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information of existing bus operators. The terminal formats this data and sends it to the server as JSON format data.

[1340] Input: population information of the target area, age distribution, transportation operator information

[1341] Output: Formatted JSON data

[1342] Step 2:

[1343] Sending and Receiving Data

[1344] The device sends the formatted data to the server via an HTTP POST request. The server receives this request and parses the data sent in JSON format. It checks whether the data is properly formatted and performs error handling if necessary.

[1345] Input: JSON format data

[1346] Output: Parsed data, error message (if needed)

[1347] Step 3:

[1348] Database Update

[1349] The server saves or updates the received data in a database. Existing data is updated and new data is inserted. For example, if population information already exists, it is updated, and if it does not exist, a new entry is added. MySQL or similar database management systems are used.

[1350] Input: Parsed data

[1351] Output: Updated or newly inserted database records

[1352] Step 4:

[1353] Analysis of population and age data

[1354] The server retrieves population information from the database and analyzes the age distribution using Python's Pandas. For example, it converts the population data into a data frame, groups it by the age column, and counts the number of people in each age group. This gives statistical information such as the fact that elderly people account for 30% of the total population.

[1355] Input: Population information retrieved from the database

[1356] Output: Age distribution analysis results

[1357] Step 5:

[1358] Analysis of existing bus operator information

[1359] The server retrieves information such as the routes, fare structures, and number of passengers of existing bus operators from the database and analyzes it using a GIS tool (e.g., QGIS). Specifically, it evaluates route overlaps and fare trends, and visualizes the number of passengers for each route using a heat map to identify areas with high demand.

[1360] Input: Transportation operator information obtained from the database

[1361] Output: Route analysis results using GIS, visualization of fare trends

[1362] Step 6:

[1363] Calculating fair fees

[1364] The server calculates the appropriate fare based on the analysis of population and transportation operator data. The pricing algorithm uses historical fare data and local economic indicators as inputs and uses Python's SciPy library to find the optimal fare through simulation. For example, the fare might be set at 200 yen for seniors and 300 yen for general users.

[1365] Input: Age distribution analysis results, transportation operator information analysis results

[1366] Output: Fair pricing results

[1367] Step 7:

[1368] Incorporating an emotion engine

[1369] The server uses an emotion engine to collect user emotion data. If the user is using an emotion recognition device (e.g., a facial recognition camera or biometric sensor), the emotion data is acquired in real time and applied to pricing and report display. For example, if the user is feeling stressed, the fee will be adjusted or the report display method will be changed.

[1370] Input: Emotion data obtained in real time from an emotion recognition device

[1371] Output: Emotion data analysis results

[1372] Step 8:

[1373] Generate and present pricing proposals

[1374] The server generates a detailed report on fair fares, which is then sent to the device in Markdown, HTML, and finally PDF format. The report includes demographics, operator information, analysis results, and fare recommendations. The report content and presentation are adjusted based on sentiment data.

[1375] Input: Results of appropriate pricing, analysis results of emotional data

[1376] Output: Generated report in PDF format

[1377] Step 9:

[1378] User Notification and Feedback

[1379] The device notifies the user of the report received from the server. The user can view the report on the device and check the details. For example, a notification message is displayed on the device, and the report can be opened by clicking the "View details" button. Feedback can also be sent to the server based on emotional data. For example, an interface is provided for rating satisfaction with the report.

[1380] Input: PDF report sent from the server

[1381] Output: User report viewing and feedback data

[1382] By using these detailed processing steps, the system of the present invention can realize efficient and appropriate pricing based on regional characteristics and user sentiment.

[1383] (Application example 2)

[1384] 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."

[1385] When setting fares for autonomous vehicles, it is necessary to realize more appropriate and flexible pricing by not only taking into account regional characteristics (population information and age distribution) but also by appropriately reflecting user emotional data. Furthermore, a method is needed to increase user satisfaction.

[1386] 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.

[1387] In this invention, the server includes means for inputting population information of the target area, means for inputting age distribution of the target area, and means for inputting information about existing transportation operators.

[1388] This will enable detailed analysis and pricing based on various data.

[1389] The system further includes means for collecting emotional data and reflecting the data in pricing and display, and means for adapting pricing using the user's emotional data.

[1390] This will enable flexible and appropriate pricing that takes into account the user's feelings, thereby improving user satisfaction.

[1391] "Population information for the target area" is statistical data on the total number, age, gender, etc. of people living in the area.

[1392] "Age distribution" is statistical data that classifies an unspecified number of people in a particular area by age.

[1393] "Information about transportation operators" refers to data on routes, fare structures, number of users, etc., of companies and organizations that provide transportation services.

[1394] A "database" is a collection of data that stores collected information and can be searched and updated as needed.

[1395] "Analysis results" are analytical results or conclusions obtained through statistical methods or calculations based on collected data.

[1396] A "fair price" is a price that is set based on the analysis results and is considered to be the most fair and reasonable price for each user.

[1397] "Emotion data" is information that indicates the user's current emotional state.

[1398] The "adaptive pricing mechanism" refers to a method or system for dynamically changing pricing in response to user emotional data.

[1399] The present invention is a system that collects and analyzes information on the population and age distribution of a target area, as well as information on existing transportation operators, and also reflects user emotional data in order to set appropriate fares for autonomous vehicles. Specific embodiments of this system are described below.

[1400] Hardware and Software Use

[1401] The system is constructed using smartphones, smart glasses, head-mounted displays, or robots as the server, terminal, and user interfaces. Python's Pandas is used for data analysis, and a geographic information system (GIS) is used for geographic information analysis. An appropriate emotion recognition engine is used to collect and analyze emotion data.

[1402] Data collection and input

[1403] The user, a city hall employee, inputs information about the target area's population, age distribution, and information about existing transportation operators into a terminal that serves as an interface. This data is sent from the terminal to a server and stored in a database. For example, this includes population data for Machida City and operation information for multiple bus operators.

[1404] Database Update

[1405] The server receives the data sent from the terminal and updates the database. After verifying that the data format is correct, new data is inserted or existing data is updated.

[1406] Data analysis

[1407] The server analyzes the population information and age distribution stored in the database using analytical tools such as Pandas. For example, it calculates the population percentage by age group and confirms that elderly people account for 30% of the total. It also analyzes information from transportation operators using a geographic information system (GIS) to evaluate trends in operation routes and user numbers.

[1408] Calculating fair fees

[1409] The server calculates the appropriate fee based on the analysis results. For example, it may set a fee of 200 yen for seniors and 300 yen for general users. Simulations are performed based on past fee data and regional economic indicators to determine the most appropriate fee setting.

[1410] Emotion engine integration

[1411] An emotion recognition device is used to collect real-time emotional data from users and send it to a server. The server analyzes the collected emotional data and reflects it in pricing and report display methods. For example, if the emotion is "happy," the system may adjust the fee slightly.

[1412] Generate and present pricing reports

[1413] The server generates a detailed report on fair pricing in Markdown or HTML format, and finally converts it to PDF format and sends it to the terminal. The user (city hall employee) can check the report on the terminal and use it to make a final decision.

[1414] Specific examples

[1415] For example, consider the following scenario in Machida City, Tokyo.

[1416] Target area: Machida City, Tokyo

[1417] Population: 10,000 (3,000 elderly, 7,000 young)

[1418] Existing bus operators: Multiple companies

[1419] City hall staff collect this information and enter it into a system that analyzes the data and calculates the appropriate fee.

[1420] Prompt Sentence Examples

[1421] Below is an example of an input prompt for a generative AI model.

[1422] Please calculate the appropriate fare for a self-driving bus in Machida City, Tokyo under the following conditions.

[1423] The total population is 10,000, of which 3,000 are elderly and 7,000 others.

[1424] There are multiple existing bus operators, each offering different routes.

[1425] Apply discounts for seniors to fair fares and also reflect emotional data.

[1426] In this way, the system of the present invention realizes efficient and fair pricing while taking into consideration regional characteristics and user sentiment.

[1427] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1428] Step 1:

[1429] The user (city hall employee) inputs population information, age distribution, and operation information of existing transportation operators for the target area into the terminal.

[1430] Input: Population information, age distribution, transportation operator operation data

[1431] Output: Formatted data

[1432] Specific operation: Through the interface, users input information about the population and age distribution of each region, as well as the routes and fares of each transportation company.

[1433] Step 2:

[1434] The device formats the input information and sends it to the server.

[1435] Input: User-entered population information, age distribution, and transportation operator operation data

[1436] Output: Formatted data sent to the server

[1437] Specific operation: The terminal standardizes the input data, converts it into CSV or JSON format, and sends it to the server.

[1438] Step 3:

[1439] The server saves or updates the received data in the database.

[1440] Input: Formatted data

[1441] Output: Information stored in the database

[1442] What happens: The server validates the format of the data and inserts new data or updates existing data in the database.

[1443] Step 4:

[1444] The server retrieves and analyzes demographic information and age distribution from the database.

[1445] Input: Population information and age distribution stored in a database

[1446] Output: Demographic data by age group

[1447] Specific operation: The server uses analytical tools such as Pandas to calculate the population percentage of each age group. For example, it calculates that the elderly make up 30% of the total population.

[1448] Step 5:

[1449] The server analyzes the transportation company's routes and number of users.

[1450] Input: Transport operator operation data stored in a database

[1451] Output: Statistical data on number of users by route

[1452] Specific operation: The server uses a geographic information system (GIS) to analyze trends in each route and the number of passengers.

[1453] Step 6:

[1454] The server calculates the appropriate fee based on the analysis results.

[1455] Input: Demographic data, transportation operator ridership data

[1456] Output: Proposed pricing

[1457] Specific operation: The server performs simulations based on past fee data and local economic indicators to calculate the optimal fee. For example, it may set the fee at 200 yen for seniors and 300 yen for general users.

[1458] Step 7:

[1459] The server collects sentiment data and incorporates it into pricing and reporting.

[1460] Input: Real-time emotion data from emotion recognition device

[1461] Output: Pricing reflecting sentiment data

[1462] Specific operation: Based on the emotional data, if the user is in a "happy" state, the system will adapt, such as reducing the general user fee by 10 yen.

[1463] Step 8:

[1464] The server generates a detailed report of the fair charges and sends it to the terminal.

[1465] Input: Data analysis results, sentiment data, pricing

[1466] Output: Detailed report in PDF format

[1467] Specific operation: The server generates a detailed report in Markdown or HTML format, and finally converts it to PDF format and sends it to the terminal. The user (city hall employee) checks the report on the terminal and uses it for final decision making.

[1468] 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.

[1469] 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.

[1470] 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.

[1471] [Fourth embodiment]

[1472] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1473] 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.

[1474] 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).

[1475] 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.

[1476] 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.

[1477] 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).

[1478] 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. 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.

[1479] 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.

[1480] 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.

[1481] 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.

[1482] 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.

[1483] 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.

[1484] 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."

[1485] This invention relates to a system that collects and analyzes information on the population, age distribution, and existing transportation operators of a target area, and then sets appropriate fares. This system is realized through the interaction of a server, terminals, and users.

[1486] System configuration and operation

[1487] 1. Data collection and input

[1488] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs data for Machida City and presses the send button, sending this information to the server. The terminal then formats the input information and sends it to the server as data.

[1489] 2. Updating the database

[1490] The server validates the data received from the device and stores or updates it in its internal database. After receiving the data, the server validates its format, connects to the database, and updates existing information or inserts new data.

[1491] 3. Demographic and Age Data Analysis

[1492] The server analyzes the population distribution and age structure of the target area. The server retrieves population data from the database and analyzes this data using analytical tools such as Python's Pandas. For example, it performs a statistical analysis to determine that Machida City has a large elderly population and that the elderly make up 30% of the total population.

[1493] 4. Analysis of existing bus operator information

[1494] The server analyzes the routes, fare structures, and ridership numbers of existing transport operators. The server retrieves bus operator information from a database and evaluates trends in routes and ridership numbers using a geographic information system (GIS) and other analytical tools.

[1495] 5. Calculating the appropriate fee

[1496] The server calculates the appropriate fare based on the analysis results. For example, it might set a fare of 200 yen for seniors and 300 yen for general users. The server uses past fare data and local economic indicators to calculate the most appropriate bus fare through simulation.

[1497] 6. Generating and Presenting Pricing Proposals

[1498] The server generates a detailed report on fair pricing and sends it to the device. The report is generated in Markdown or HTML format, converted to PDF, and securely sent. The device notifies the user that a fair pricing proposal has been generated and displays the report. The user can review the details of the report and make a final pricing decision based on it.

[1499] Specific example explanation

[1500] A specific example is shown below.

[1501] scenario

[1502] Target area: Machida City, Tokyo

[1503] Population: 10,000 (3,000 elderly, 7,000 young)

[1504] Existing bus operators: Company A and Company B

[1505] Operating Procedure

[1506] 1. The user (city hall employee) enters Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information for Company A and Company B into the terminal and presses the send button.

[1507] 2. The device formats the input information and sends it to the server.

[1508] 3. The server saves or updates the received data in the database.

[1509] 4. The server retrieves population information from the database and analyzes it. For example, it uses Pandas to analyze the age distribution and finds that elderly people account for 30%.

[1510] 5. The server obtains bus operator information, analyzes bus routes using GIS, and analyzes existing fare structures and trends in user numbers.

[1511] 6. Based on the analysis results, the server calculates the appropriate fees, which are set at 200 yen for elderly people and 300 yen for general users.

[1512] 7. The server generates a detailed report of the fair charges and sends it to the terminal in PDF format.

[1513] 8. The terminal notifies the user and displays a report. The user (city hall employee) checks the analysis results and fee proposals and uses them in making a final decision.

[1514] In this way, the system of the present invention makes it possible to efficiently set optimal fares for autonomous buses in a target area.

[1515] The processing flow will be explained below.

[1516] Step 1:

[1517] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, they input "population information for Machida City, Tokyo" and "operation routes and fare information for Company A and Company B." Once the input is complete, they press the send button.

[1518] Step 2:

[1519] The device receives the information entered by the user, formats the data in an appropriate format (e.g., JSON), and sends the formatted data to the server using an HTTP POST request.

[1520] Step 3:

[1521] The server then checks the data received and verifies that it is in the correct format. Once the data has been validated, it connects to a database and saves or updates the information in the database. The saved data includes the area's population information, age distribution, and information about existing transport operators.

[1522] Step 4:

[1523] The server retrieves population information and age distribution for the target area from the database. Using the retrieved data, it analyzes the population distribution and age structure using Python's Pandas library, for example. For example, it calculates the proportion of elderly people and identifies the characteristics of age groups specific to that area.

[1524] Step 5:

[1525] The server retrieves information about existing transportation operators from a database. It uses a GIS (geographic information system) API to perform a geographic analysis of the routes. It also performs statistical analysis of fare information and ridership numbers to evaluate trends in existing fare structures and ridership numbers.

[1526] Step 6:

[1527] The server calculates appropriate fees based on the acquired and analyzed data. For example, it calculates different fees for different age groups, such as setting a fee of 200 yen for seniors and 300 yen for general users. It also references past fee data and regional economic indicators to create an optimal fee model.

[1528] Step 7:

[1529] The server generates a detailed report of the calculated fair fares in Markdown and HTML formats, and finally in PDF format, including demographics, transit operator information, analysis results, and recommended fares.

[1530] Step 8:

[1531] The server sends the generated report to the terminal, which notifies the user when the report has been sent.

[1532] Step 9:

[1533] The terminal notifies the user that the report has been received via a pop-up notification or email. The user can view the report on the terminal and check the details. The user (city hall employee) uses the report as reference material to determine the final fee setting.

[1534] In this way, the system of the present invention sets efficient and appropriate fares for autonomous buses based on regional characteristics.

[1535] Example 1

[1536] 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."

[1537] In modern society, changes in demographics and fluctuations in transportation operator operating conditions require the establishment of appropriate fares. However, existing systems often lack reliability and accuracy in fare setting due to insufficient analysis of population distribution and age groups, or the collection and analysis of information on existing transportation operators. Furthermore, the generation and presentation of detailed reports on appropriate fares based on the analysis results is not automated, which can lead to manual errors and time-consuming work. Therefore, there is a need for the development of a system that can efficiently collect and analyze data on population information, age distribution, and existing transportation operators, and automatically calculate appropriate fares.

[1538] 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.

[1539] In this invention, the server includes a means for formatting population data and transportation operator information for the target area and sending it to the server, a means for verifying the format of the received data and saving or updating it in an internal database, and a means for utilizing data analysis tools to analyze the population distribution and age structure of the target area. This enables rapid analysis of population distribution and age structure and accurate evaluation of transportation operator operation information. Furthermore, a detailed report of appropriate fares can be automatically generated and presented, improving the reliability and efficiency of fare setting.

[1540] "Area of ​​Interest" means the specific geographic area that is the subject of an analysis or calculation.

[1541] "Population information" refers to statistical information such as the total number of residents in the target area, their gender, and their age group.

[1542] "Age distribution" refers to data showing the age structure of residents in the target area.

[1543] "Transportation operator" means a company or organization that operates public transportation such as buses and trains.

[1544] "Database" refers to a system for organizing, storing, efficiently retrieving, and updating information.

[1545] "Formatting" refers to the process of unifying the data format and making it consistent.

[1546] "Analysis" refers to the process of evaluating collected data and making sense of it.

[1547] "Data analysis tools" refers to software for analyzing collected data and performing statistical evaluations.

[1548] "Geographic Information System (GIS)" means a system for collecting, managing, analyzing, and visualizing geographic information.

[1549] "Fair rates" refer to rates that are calculated based on the analysis results and are considered fair and reasonable for users.

[1550] "Report" means a document summarizing the results of analysis or calculations.

[1551] This invention relates to a system that collects and analyzes information on the population, age distribution, and existing transportation operators of a target area, and then sets appropriate fares. This system is realized through the interaction of a server, terminals, and users.

[1552] Data collection and input

[1553] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information of Company A and Company B into the terminal, and then presses the send button. This operation completes the data input process.

[1554] Data transmission and preprocessing

[1555] The terminal formats the information entered by the user, converts it to JSON format, and sends it to the server. The HTTPS protocol is used for data transmission, ensuring secure data transmission. The server temporarily stores the received data in memory, checks the format, and performs preprocessing.

[1556] Database Update

[1557] The server validates the pre-processed data and saves or updates it in an internal database. Specifically, the server validates the format of the incoming data, connects to the database (e.g., MySQL or PostgreSQL), and updates existing information or inserts new data. During this process, the server uses transactions to ensure data consistency.

[1558] Population and age data analysis

[1559] The server analyzes the population distribution and age structure of the target area. Specifically, it retrieves population data from the database and performs statistical analysis using Python's Pandas library. For example, it confirms that Machida City has a high elderly population and outputs analysis results such as elderly people making up 30% of the total population.

[1560] Analysis of existing bus operator information

[1561] The server analyzes the routes, fare structures, and number of users of existing transportation operators. Specifically, it retrieves bus operator information from a database and visualizes and analyzes route data using geographic information system (GIS) software (ArcGIS or QGIS). It also graphs and evaluates trends in fare structures and user numbers using Python's Matplotlib and Seaborn.

[1562] Calculating fair fees

[1563] The server calculates the appropriate fee based on the analysis results. The server references past fee data and local economic indicators and executes algorithms to perform simulations. For example, it uses regression analysis to calculate the appropriate fee of 200 yen for the elderly and 300 yen for general users. These calculations are performed using Python's Scikit-learn library.

[1564] Generate and present reports

[1565] The server generates a detailed report on fair pricing and sends it to the device. Specifically, the report is generated in Markdown or HTML format and then converted to PDF format. The generated PDF is attached to an email or sent to the device via a secure channel. The device notifies the user of the analysis results and pricing proposals and displays the report. The user can then make a final pricing decision based on the report.

[1566] Prompt Sentence Examples

[1567] "Calculate the appropriate fares for the transportation business based on Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information for companies A and B. Then, referencing various statistical data and regional economic indicators, generate a report proposing a fare of 200 yen for elderly people and 300 yen for general users."

[1568] By using the system of the present invention, it is possible to efficiently set fares for autonomous buses that are optimal for the target area, contributing to improving the efficiency and convenience of local transportation.

[1569] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1570] Program processing flow

[1571] Step 1: Data collection and entry

[1572] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs population data for Machida City, such as 3,000 elderly people and 7,000 young people, as well as route and fare information for companies A and B, into the terminal, confirms the input data, and then presses the send button. This sends the information entered by the user to the terminal, where it is formatted and prepared for transmission.

[1573] Input: population information of the target area, age distribution, transportation operator information

[1574] Output: The formatted input data

[1575] Step 2: Data transmission and preprocessing

[1576] The terminal converts the information entered by the user into JSON format and sends it to the server using HTTPS. The server temporarily stores the received data in memory and verifies whether the data format is correct. For example, if the data format is correct, the formatted data is prepared for storage on the server.

[1577] Input: Formatted input data

[1578] Output: Data sent to the server

[1579] Step 3: Update the database

[1580] The server saves or updates the received data in an internal database (for example, MySQL or PostgreSQL). If the same information already exists, the corresponding record is updated, and if not, a new record is inserted. Data consistency is maintained through transaction management.

[1581] Input: Data sent to the server

[1582] Output: Data saved or updated in the database

[1583] Step 4: Population and age data analysis

[1584] The server retrieves population data from the database and performs statistical analysis using Python's Pandas library, such as calculating the ratio of elderly to young people and finding that elderly people account for 30% of the total population in Machida City.

[1585] Input: Population data retrieved from the database

[1586] Output: Statistical analysis results (e.g., elderly people account for 30% of the total)

[1587] Step 5: Analyze existing bus operator information

[1588] The server retrieves bus operator information from the database and uses GIS tools (such as ArcGIS or QGIS) to visualize and analyze routes. It also uses Python's Matplotlib and Seaborn to graph and evaluate trends in fare structures and ridership. For example, it can conclude that Company A has more riders than Company B, but its fares are higher, so it needs to review its pricing.

[1589] Input: Bus operator information retrieved from the database

[1590] Output: Visualization of operation routes using GIS, evaluation of fare structures and trends in number of users

[1591] Step 6: Calculate the fair price

[1592] The server calculates the appropriate fee based on the analysis results. It sets the fee using regression analysis, referencing past fee data and regional economic indicators. For example, it calculates a fee of 200 yen for the elderly and 300 yen for general users through simulation.

[1593] Input: Analysis results, historical pricing data, local economic indicators

[1594] Output: Fair fee calculation result

[1595] Step 7: Generate and present the report

[1596] The server generates a detailed report on fair pricing in Markdown or HTML format, converts it to PDF format, and sends it to the terminal. The terminal notifies the user of the received PDF and displays the report so that the user can review it. The user then determines the final pricing based on the analysis results and pricing proposals.

[1597] Input: Calculation result of fair fee

[1598] Output: Generated report (PDF format), notification to user

[1599] By following the above steps, this system can automate and efficiently set optimal rates for the target area.

[1600] (Application example 1)

[1601] 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."

[1602] Conventional pricing systems for autonomous vehicles do not fully consider the population information and age distribution of the target area, or information on existing transportation operators, making it difficult to calculate appropriate fares. Furthermore, there was no efficient system for collecting and analyzing this information, making operation cumbersome. Furthermore, there was a need to present the analysis results in a user-friendly format.

[1603] 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.

[1604] In this invention, the server includes: means for inputting population information for a target area; means for inputting age distribution for the target area; means for inputting information about existing transportation operators; means for saving or updating the input information in a database; means for analyzing the population information and age distribution saved in the database; means for analyzing information about transportation operators saved in the database; means for calculating an appropriate fare to display on a smartphone, smart glasses, or head-mounted display; means for generating and presenting a detailed report of the appropriate fare; means for using a generative AI model to generate a report of analysis results regarding fare setting for autonomous vehicles; and means for using a generative AI model to generate a prompt message for an appropriate fare based on the analysis results. This enables efficient and accurate fare setting that takes into account the population information, age distribution, and information about existing transportation operators for the target area.

[1605] A "target area" is an area for which specific population information, age distribution, and transportation operator information are analyzed.

[1606] "Population information" is data on the number and distribution of people living in a target area.

[1607] "Age distribution" is information that shows the proportion of the population of various age groups in the target area.

[1608] "Transportation operator information" is data related to transportation such as buses that operate within the target area.

[1609] "Database" means a system for storing or updating collected population information, age distribution, and transportation operator information.

[1610] "Analysis methods" are methods for analyzing population distribution and transportation company routes based on information stored in the database.

[1611] The "fair fare calculation method" is a method for calculating fair fares for autonomous vehicles based on the results of an analysis of population information, age distribution, and transportation operator information.

[1612] The "report generation means" is a method for generating a detailed report of the calculation results of the fair fee and related information, and presenting it to the user.

[1613] A "smartphone" is a mobile device that combines the functions of a mobile phone and a computer.

[1614] "Smart glasses" are eyeglass-shaped wearable devices that have the function of displaying information.

[1615] A "head-mounted display" is a display device worn on the head, and is a device that has the function of displaying digital information in the field of vision.

[1616] A "generative AI model" is a system that uses artificial intelligence (AI) to analyze data and automatically generate effective pricing calculations and reports.

[1617] A "prompt" is an instruction generated by an AI model to present appropriate pricing and related information.

[1618] MODE FOR CARRYING OUT THE INVENTION

[1619] The embodiment of the present invention is a system that collects and analyzes information on the population, age distribution, and existing transportation operators of a target area to set appropriate fares. This system is realized through the interaction of a server, terminals, and users.

[1620] System configuration and operation

[1621] 1. Data collection and input

[1622] Users use a smartphone, smart glasses, or head-mounted display to input information about the target area's population, age distribution, and existing transportation operators. For example, a government official inputs data for a city and presses the send button, which sends the information to the server. The device then formats the input information and sends it to the server as data.

[1623] 2. Updating the database

[1624] The server checks the data received from the device and saves or updates it in its internal database. After receiving the data, the server verifies its format, connects to the database, and updates existing information or inserts new data. This database uses SQLite.

[1625] 3. Demographic and Age Data Analysis

[1626] The server analyzes the population distribution and age structure of the target area. The server retrieves population data from the database and analyzes this data using analytical tools such as Python's Pandas. For example, it performs statistical analysis to determine that there are many elderly people in a particular area and that the elderly make up 30% of the total population.

[1627] 4. Analysis of existing bus operator information

[1628] The server analyzes the routes, fare structures, and ridership numbers of existing transport operators. The server retrieves information about transport operators from a database and evaluates trends in routes and ridership numbers using a geographic information system (GIS) and other analytical tools.

[1629] 5. Calculating the appropriate fee

[1630] The server calculates the appropriate fee based on the analysis results. For example, it may set the fee at 200 yen for seniors and 300 yen for general users. The server calculates the most appropriate fee through simulations based on past fee data and local economic indicators.

[1631] 6. Generating and Presenting Pricing Proposals

[1632] The server generates a detailed report on fair pricing and sends it to the device. The report is generated in Markdown or HTML format and sent securely. The device notifies the user that fair pricing suggestions have been generated and displays the report. Using a generative AI model, fair pricing prompts are also generated to make the report user-friendly.

[1633] Hardware and software used

[1634] Hardware: Standard servers (e.g. AWS, Google Cloud), smartphones, smart glasses, head-mounted displays

[1635] Software: Python (Pandas, GeoPandas), SQLite, generative AI models

[1636] Specific examples

[1637] scenario:

[1638] Target area: A city

[1639] Population: 50,000 (15,000 elderly, 35,000 young)

[1640] Existing bus operators: Transportation companies A and B

[1641] Operation steps:

[1642] 1. An administrative official enters the city's population data (15,000 elderly people, 35,000 young people) and the route and fare information for companies A and B into the terminal and presses the send button.

[1643] 2. The device formats the input information and sends it to the server.

[1644] 3. The server saves or updates the received data in the database.

[1645] 4. The server retrieves population information from the database, analyzes the age distribution using Pandas, and confirms that elderly people account for 30%.

[1646] 5. The server obtains transportation operator information, analyzes routes using GeoPandas, and analyzes existing fare structures and trends in ridership.

[1647] 6. Based on the analysis results, the server calculates the appropriate fees, which are set at 200 yen for elderly people and 300 yen for general users.

[1648] 7. The server generates a detailed report of the fair charges and sends it to the terminal in PDF format.

[1649] 8. The device notifies the user and displays a report, and also generates prompts regarding fair pricing using a generative AI model.

[1650] Example prompt sentence:

[1651] "Use generative AI to analyze the appropriate fare for a city's autonomous buses. Consider the following data:

[1652] Population data (e.g., 15,000 elderly people, 35,000 young people)

[1653] Route and fare information for existing bus operators

[1654] As a result of the analysis, please calculate the appropriate fees for elderly people and general users and create a detailed report. For example, set the fees at 200 yen for elderly people and 300 yen for general users.

[1655] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1656] Step 1:

[1657] Entering and Submitting Data

[1658] The user uses a smartphone, smart glasses, or head-mounted display to input information about the target area's population, age distribution, and information about existing transportation operators into the terminal and presses the send button. At this time, the input information is formatted in JSON format or similar. The input data (population information, age distribution, transportation operator information) from the terminal is sent to the server.

[1659] Input: population information of the target area, age distribution, transportation operator information

[1660] Output: Send formatted data to the server

[1661] Step 2:

[1662] Save or update to database

[1663] The server checks the data received from the device and stores or updates it in its internal database. The server first verifies the format of the received data, then connects to the SQLite database to update existing information or insert new data.

[1664] Input: Data received from the device (JSON format population information, age distribution, transportation operator information)

[1665] Output: Database update status

[1666] Step 3:

[1667] Analysis of population and age data

[1668] The server retrieves population information and age distributions from the database and analyzes this data using Python's Pandas library, calculating the population percentage for each age group and analyzing, for example, what percentage of the population is elderly.

[1669] Input: Population information and age distribution obtained from the database

[1670] Output: Population percentage by age group (e.g., 30% elderly)

[1671] Step 4:

[1672] Analysis of transportation operator information

[1673] The server retrieves the transportation operator's route, fare structure, and number of users from the database and performs geographic information analysis using libraries such as GeoPandas, thereby analyzing route efficiency and user trends.

[1674] Input: Transport operator information obtained from the database (operation route, fare structure, number of users)

[1675] Output: Route efficiency, ridership trends

[1676] Step 5:

[1677] Calculating fair fees

[1678] The server calculates appropriate fares based on the analysis of population information, age distribution, and transportation company operation information. For example, it simulates and sets fares of 200 yen for seniors and 300 yen for general users. Fares are set more precisely using a generative AI model.

[1679] Input: Analysis results of population information, age distribution, and transportation company operation information

[1680] Output: Reasonable fee (200 yen for seniors, 300 yen for general users)

[1681] Step 6:

[1682] Generate and present pricing proposals

[1683] The server generates a detailed report on fair pricing and sends it to the device. The report is generated in Markdown or HTML format and then converted to PDF. The device notifies the user and displays the report. Additionally, a generative AI model is used to generate prompts based on the analysis results.

[1684] Input: Calculation result of fair fee

[1685] Output: Detailed report (PDF format), prompt statement

[1686] Examples:

[1687] Example prompt sentence:

[1688] "Use generative AI to analyze the appropriate fare for a city's autonomous buses. Consider the following data:

[1689] Population data (e.g., 15,000 elderly people, 35,000 young people)

[1690] Route and fare information for existing bus operators

[1691] As a result of the analysis, please calculate the appropriate fees for elderly people and general users and create a detailed report. For example, set the fees at 200 yen for elderly people and 300 yen for general users.

[1692] 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.

[1693] This invention combines an emotion engine with a system that collects and analyzes information on the population, age distribution, and existing transportation operators in the target area to set appropriate fares. This system is realized through the interaction of servers, terminals, and users.

[1694] System configuration and operation

[1695] 1. Data collection and input

[1696] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs data for Machida City and presses the send button, sending this information to the server. The terminal then formats the input information and sends it to the server as data.

[1697] 2. Updating the database

[1698] The server validates the data received from the device and stores or updates it in its internal database. After receiving the data, the server validates its format, connects to the database, and updates existing information or inserts new data.

[1699] 3. Demographic and Age Data Analysis

[1700] The server analyzes the population distribution and age structure of the target area. The server retrieves population data from the database and analyzes this data using analytical tools such as Python's Pandas. For example, it performs a statistical analysis to determine that Machida City has a large elderly population and that the elderly make up 30% of the total population.

[1701] 4. Analysis of existing bus operator information

[1702] The server analyzes the routes, fare structures, and ridership numbers of existing transport operators. The server retrieves bus operator information from a database and evaluates trends in routes and ridership numbers using a geographic information system (GIS) and other analytical tools.

[1703] 5. Calculating the appropriate fee

[1704] The server calculates the appropriate fare based on the analysis results. For example, it might set a fare of 200 yen for seniors and 300 yen for general users. The server uses past fare data and local economic indicators to calculate the most appropriate bus fare through simulation.

[1705] 6. Incorporating an Emotional Engine

[1706] In the present invention, an emotion engine is used to collect user emotion data and apply the data to pricing and report display, for example, by collecting emotion data in real time when a user is using an emotion recognition device.

[1707] 7. Generating and Presenting Pricing Proposals

[1708] The server generates a detailed report on fair fares in Markdown and HTML formats, and finally in PDF format. The report includes demographics, operator information, analysis results, and fare recommendations. The report's content and presentation can be tailored based on data from the sentiment engine.

[1709] 8. User Notification and Feedback

[1710] The server sends the generated report to the device. Once the report has been sent, the device notifies the user. The user can view the report on the device and check the details. If emotion data has been collected, it can also be used as user feedback.

[1711] Specific example explanation

[1712] A specific example is shown below.

[1713] scenario

[1714] Target area: Machida City, Tokyo

[1715] Population: 10,000 (3,000 elderly, 7,000 young)

[1716] Existing bus operators: Company A and Company B

[1717] Operating Procedure

[1718] 1. The user (city hall employee) enters Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information for Company A and Company B into the terminal and presses the send button.

[1719] 2. The device formats the input information and sends it to the server.

[1720] 3. The server saves or updates the received data in the database.

[1721] 4. The server retrieves population information from the database and analyzes it. For example, it uses Pandas to analyze the age distribution and finds that elderly people account for 30% of the population.

[1722] 5. The server obtains bus operator information, analyzes bus routes using GIS, and analyzes existing fare structures and trends in user numbers.

[1723] 6. Based on the analysis results, the server calculates the appropriate fees, which are set at 200 yen for elderly people and 300 yen for general users.

[1724] 7. The server generates a detailed report of the fair charges and sends it to the terminal in PDF format.

[1725] 8. The emotion engine collects user emotion data, and the server uses that data to adjust the content and presentation of the report.

[1726] 9. The terminal notifies the user and displays a report. The user (city hall employee) checks the analysis results and pricing proposal and uses them in making a final decision. Emotional data is also used as a reference for the final decision.

[1727] In this way, the system of the present invention sets efficient and appropriate fares for autonomous buses based on regional characteristics, and by taking user emotions into consideration, it becomes possible to set fares more adaptively.

[1728] The processing flow will be explained below.

[1729] Step 1:

[1730] Users input information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee might input "Machida City's population data" (3,000 elderly people, 7,000 young people) and "operation routes and fare information for Company A and Company B," then press the send button.

[1731] Step 2:

[1732] The device receives the information entered by the user, formats the data in an appropriate format (e.g., JSON), and sends the formatted data to the server using an HTTP POST request.

[1733] Step 3:

[1734] The server checks the received data and verifies that it is in the correct format. Once the data is verified, it connects to a database and saves or updates the information in the database. For example, the database records the population information, age distribution, and information about existing transport operators in the target area.

[1735] Step 4:

[1736] The server retrieves population information and age distribution for the target area from the database. Using Python's Pandas library, the server analyzes the population distribution and age structure. For example, it calculates that the proportion of elderly people is 30%.

[1737] Step 5:

[1738] The server retrieves information about existing transport operators from a database, uses a GIS (geographic information system) API to perform a geographic analysis of the routes, and performs statistical analysis of fare information and user numbers.

[1739] Step 6:

[1740] The server calculates the appropriate fee based on the acquired and analyzed data. For example, the fee for seniors may be set at 200 yen, and the fee for general users at 300 yen. This allows different fees to be calculated for each age group.

[1741] Step 7:

[1742] The server generates a detailed report of the generated fair fares in Markdown and HTML format, which is then converted to PDF format, and includes demographics, operator information, analysis results, and recommended fares.

[1743] Step 8:

[1744] The server collects user emotion data using an emotion engine. For example, if the user uses an emotion recognition device, the server acquires the user's emotional state (satisfied, dissatisfied, excited, etc.) in real time.

[1745] Step 9:

[1746] The server adjusts the content and presentation of the report based on the emotion data. For example, if the user is frustrated, it adjusts the tone of the report to provide a more understandable explanation.

[1747] Step 10:

[1748] The server sends the generated report to the terminal, which notifies the user when the report has been sent.

[1749] Step 11:

[1750] The device will notify the user via a pop-up notification or email that the report has been received. The user can view the report on the device and check the details. Emotional data will also be referenced and used as user feedback. The user (city hall employee) will use the report as reference material to determine the final pricing.

[1751] In this way, the system of the present invention sets efficient and appropriate fares for autonomous buses based on regional characteristics, and by taking user emotions into consideration, it becomes possible to set fares more adaptively.

[1752] Example 2

[1753] 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."

[1754] The current transportation fare system does not effectively utilize information on the local population structure, age distribution, or existing transportation operators, making it difficult to set fair and appropriate fares.Furthermore, the system does not take into account user emotions when setting fares or displaying reports, resulting in low user satisfaction.

[1755] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1756] In this invention, the server includes means for inputting population information for a target area, means for inputting the age distribution of the target area, means for inputting information about existing transportation operators, means for saving or updating the input information in a database, means for analyzing the population information and age distribution saved in the database, means for analyzing the information about transportation operators saved in the database, means for calculating an appropriate fare based on the analysis results, means for generating and presenting a detailed report of the appropriate fare, means for using an emotion engine to collect user emotion data, and means for applying the emotion data to fare setting and report display. This enables the transportation fare system to set appropriate fares and provide reports that take into account regional characteristics and user emotions.

[1757] "Target area" means a specific geographic area established for the purpose of collecting and analyzing population information, age distribution, and transportation operator information.

[1758] "Population information" refers to data that indicates the total number of people living in a particular area and their characteristics.

[1759] "Age distribution" refers to data that shows the proportion and composition of the population by age group living in a particular area.

[1760] A "transportation operator" is a company or organization that operates public transportation such as buses and trains.

[1761] A "database" is a system for organizing, efficiently storing, and managing information.

[1762] "Analysis" refers to the techniques used to examine collected data in detail and extract meaningful information.

[1763] "Fair fare" means a fair and reasonable fare that users can accept for the transportation services provided.

[1764] A "report" is a document that clearly presents the results of the analysis and recommendations.

[1765] "Emotion data" refers to information that quantifies the user's emotions and psychological state.

[1766] An "emotion engine" is a piece of software or hardware dedicated to collecting and analyzing users' emotional data.

[1767] "Pricing" refers to the process of determining prices for transportation services.

[1768] "Report display" refers to the visual presentation of a generated report to a user.

[1769] This invention combines an emotion engine with a system that collects and analyzes information on the population, age distribution, and existing transportation operators in the target area to set appropriate fares. This system is realized through the interaction of a server, terminals, and users.

[1770] Hardware and software used

[1771] server

[1772] The server handles all major processing, from data storage, analysis, billing, and report generation. The software that runs on the server includes:

[1773] Database management system (e.g. MySQL)

[1774] Data analysis tools (e.g., Python, Pandas, SciPy)

[1775] Geographic Information Systems (e.g. QGIS)

[1776] Emotion Recognition Software

[1777] Report generation tools (e.g., Markdown, HTML, PDF export)

[1778] Terminal

[1779] The terminal provides the interface for users to enter data and view and manipulate reports. Software running on the terminal includes:

[1780] A front-end framework that provides a form input screen (e.g., React, Angular)

[1781] API client to send and receive data

[1782] A viewer for displaying reports in the interface (e.g., a PDF viewer)

[1783] User

[1784] Users input the target area's population information, age distribution, and existing transport operators' information into the terminal, and then check the generated report. The devices used by users include regular PCs, tablets, and smartphones.

[1785] Data processing and calculation

[1786] 1. Data collection and input

[1787] The user inputs information about the target area into the terminal. For example, a city hall employee inputs the population data for Machida City (3,000 elderly people, 7,000 young people) and the route and fare information for existing bus operators A and B, and sends the data to the server.

[1788] 2. Sending and Receiving Data

[1789] The device formats the input information and sends it to the server, which receives the data and verifies that it is in the proper format.

[1790] 3. Updating the database

[1791] The server stores or updates the received data in the database: existing data is updated and new data is inserted.

[1792] 4. Analysis of Demographic and Age Data

[1793] The server retrieves population information from the database and analyzes the age distribution using Python's Pandas. Specifically, it confirms that elderly people account for 30% of the population.

[1794] 5. Analysis of existing bus operator information

[1795] The server uses GIS tools to analyze information such as bus operator routes and evaluate route overlaps and fare trends.

[1796] 6. Calculating the appropriate fee

[1797] The server calculates the appropriate fee based on the analysis results and runs a simulation to set the fee at 200 yen for the elderly and 300 yen for general users.

[1798] 7. Incorporating an Emotional Engine

[1799] The emotion engine collects user emotion data, for example, by using an emotion recognition device to capture the user's emotional state in real time and apply it to pricing and report display.

[1800] 8. Generating and Presenting Pricing Proposals

[1801] The server generates a detailed report on fair fares in Markdown and HTML formats, and finally sends it to the device in PDF format. The report includes demographics, transportation operator information, analysis results, and fare recommendations. The report presentation is adjusted based on sentiment data.

[1802] Specific example explanation

[1803] Specific examples of the present invention will be described below.

[1804] scenario

[1805] Target area: Machida City, Tokyo

[1806] Population: 10,000 (3,000 elderly, 7,000 young)

[1807] Existing bus operators: Company A and Company B

[1808] Operating Procedure

[1809] 1. The user (city hall employee) enters Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information for Company A and Company B into the terminal and presses the send button.

[1810] 2. The device formats the input information and sends it to the server.

[1811] 3. The server saves or updates the received data in the database.

[1812] 4. The server retrieves population information from the database and uses Pandas to analyze the age distribution. For example, it confirms that elderly people account for 30%.

[1813] 5. The server obtains bus operator information, analyzes bus routes using GIS, and analyzes existing fare structures and trends in ridership.

[1814] 6. Based on the analysis results, the server calculates the appropriate fees, which are set at 200 yen for elderly people and 300 yen for general users.

[1815] 7. The server generates a detailed report of the fair charges and sends it to the terminal in PDF format.

[1816] 8. The emotion engine collects user emotion data, and the server adjusts the report content and display method based on that data.

[1817] 9. The terminal notifies the user and displays a report. The user (city hall employee) checks the analysis results and pricing proposal and uses them in making a final decision. Emotional data is also used as a reference for the final decision.

[1818] In this way, the system of the present invention can realize efficient and appropriate pricing based on regional characteristics and user sentiment.

[1819] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1820] Step 1:

[1821] Data collection and input

[1822] The user inputs information about the target area's population, age distribution, and information about existing transportation operators into the terminal. For example, a city hall employee inputs Machida City's population data (3,000 elderly people, 7,000 young people) and the route and fare information of existing bus operators. The terminal formats this data and sends it to the server as JSON format data.

[1823] Input: population information of the target area, age distribution, transportation operator information

[1824] Output: Formatted JSON data

[1825] Step 2:

[1826] Sending and Receiving Data

[1827] The device sends the formatted data to the server via an HTTP POST request. The server receives this request and parses the data sent in JSON format. It checks whether the data is properly formatted and performs error handling if necessary.

[1828] Input: JSON format data

[1829] Output: Parsed data, error message (if needed)

[1830] Step 3:

[1831] Database Update

[1832] The server saves or updates the received data in a database. Existing data is updated and new data is inserted. For example, if population information already exists, it is updated, and if it does not exist, a new entry is added. MySQL or similar database management systems are used.

[1833] Input: Parsed data

[1834] Output: Updated or newly inserted database records

[1835] Step 4:

[1836] Analysis of population and age data

[1837] The server retrieves population information from the database and analyzes the age distribution using Python's Pandas. For example, it converts the population data into a data frame, groups it by the age column, and counts the number of people in each age group. This gives statistical information such as the fact that elderly people account for 30% of the total population.

[1838] Input: Population information retrieved from the database

[1839] Output: Age distribution analysis results

[1840] Step 5:

[1841] Analysis of existing bus operator information

[1842] The server retrieves information such as the routes, fare structures, and number of passengers of existing bus operators from the database and analyzes it using a GIS tool (e.g., QGIS). Specifically, it evaluates route overlaps and fare trends, and visualizes the number of passengers for each route using a heat map to identify areas with high demand.

[1843] Input: Transportation operator information obtained from the database

[1844] Output: Route analysis results using GIS, visualization of fare trends

[1845] Step 6:

[1846] Calculating fair fees

[1847] The server calculates the appropriate fare based on the analysis of population and transportation operator data. The pricing algorithm uses historical fare data and local economic indicators as inputs and uses Python's SciPy library to find the optimal fare through simulation. For example, the fare might be set at 200 yen for seniors and 300 yen for general users.

[1848] Input: Age distribution analysis results, transportation operator information analysis results

[1849] Output: Fair pricing results

[1850] Step 7:

[1851] Incorporating an emotion engine

[1852] The server uses an emotion engine to collect user emotion data. If the user is using an emotion recognition device (e.g., a facial recognition camera or biometric sensor), the emotion data is acquired in real time and applied to pricing and report display. For example, if the user is feeling stressed, the fee will be adjusted or the report display method will be changed.

[1853] Input: Emotion data obtained in real time from an emotion recognition device

[1854] Output: Emotion data analysis results

[1855] Step 8:

[1856] Generate and present pricing proposals

[1857] The server generates a detailed report on fair fares, which is then sent to the device in Markdown, HTML, and finally PDF format. The report includes demographics, operator information, analysis results, and fare recommendations. The report content and presentation are adjusted based on sentiment data.

[1858] Input: Results of appropriate pricing, analysis results of emotional data

[1859] Output: Generated report in PDF format

[1860] Step 9:

[1861] User Notification and Feedback

[1862] The device notifies the user of the report received from the server. The user can view the report on the device and check the details. For example, a notification message is displayed on the device, and the report can be opened by clicking the "View details" button. Feedback can also be sent to the server based on emotional data. For example, an interface is provided for rating satisfaction with the report.

[1863] Input: PDF report sent from the server

[1864] Output: User report viewing and feedback data

[1865] By using these detailed processing steps, the system of the present invention can realize efficient and appropriate pricing based on regional characteristics and user sentiment.

[1866] (Application example 2)

[1867] 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."

[1868] When setting fares for autonomous vehicles, it is necessary to realize more appropriate and flexible pricing by not only taking into account regional characteristics (population information and age distribution) but also by appropriately reflecting user emotional data. Furthermore, a method is needed to increase user satisfaction.

[1869] 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.

[1870] In this invention, the server includes means for inputting population information of the target area, means for inputting age distribution of the target area, and means for inputting information about existing transportation operators.

[1871] This will enable detailed analysis and pricing based on various data.

[1872] The system further includes means for collecting emotional data and reflecting the data in pricing and display, and means for adapting pricing using the user's emotional data.

[1873] This will enable flexible and appropriate pricing that takes into account the user's feelings, thereby improving user satisfaction.

[1874] "Population information for the target area" is statistical data on the total number, age, gender, etc. of people living in the area.

[1875] "Age distribution" is statistical data that classifies an unspecified number of people in a particular area by age.

[1876] "Information about transportation operators" refers to data on routes, fare structures, number of users, etc., of companies and organizations that provide transportation services.

[1877] A "database" is a collection of data that stores collected information and can be searched and updated as needed.

[1878] "Analysis results" are analytical results or conclusions obtained through statistical methods or calculations based on collected data.

[1879] A "fair price" is a price that is set based on the analysis results and is considered to be the most fair and reasonable price for each user.

[1880] "Emotion data" is information that indicates the user's current emotional state.

[1881] The "adaptive pricing mechanism" refers to a method or system for dynamically changing pricing in response to user emotional data.

[1882] The present invention is a system that collects and analyzes information on the population and age distribution of a target area, as well as information on existing transportation operators, and also reflects user emotional data in order to set appropriate fares for autonomous vehicles. Specific embodiments of this system are described below.

[1883] Hardware and Software Use

[1884] The system is constructed using smartphones, smart glasses, head-mounted displays, or robots as the server, terminal, and user interfaces. Python's Pandas is used for data analysis, and a geographic information system (GIS) is used for geographic information analysis. An appropriate emotion recognition engine is used to collect and analyze emotion data.

[1885] Data collection and input

[1886] The user, a city hall employee, inputs information about the target area's population, age distribution, and information about existing transportation operators into a terminal that serves as an interface. This data is sent from the terminal to a server and stored in a database. For example, this includes population data for Machida City and operation information for multiple bus operators.

[1887] Database Update

[1888] The server receives the data sent from the terminal and updates the database. After verifying that the data format is correct, new data is inserted or existing data is updated.

[1889] Data analysis

[1890] The server analyzes the population information and age distribution stored in the database using analytical tools such as Pandas. For example, it calculates the population percentage by age group and confirms that elderly people account for 30% of the total. It also analyzes information from transportation operators using a geographic information system (GIS) to evaluate trends in operation routes and user numbers.

[1891] Calculating fair fees

[1892] The server calculates the appropriate fee based on the analysis results. For example, it may set a fee of 200 yen for seniors and 300 yen for general users. Simulations are performed based on past fee data and regional economic indicators to determine the most appropriate fee setting.

[1893] Emotion engine integration

[1894] An emotion recognition device is used to collect real-time emotional data from users and send it to a server. The server analyzes the collected emotional data and reflects it in pricing and report display methods. For example, if the emotion is "happy," the system may adjust the fee slightly.

[1895] Generate and present pricing reports

[1896] The server generates a detailed report on fair pricing in Markdown or HTML format, and finally converts it to PDF format and sends it to the terminal. The user (city hall employee) can check the report on the terminal and use it to make a final decision.

[1897] Specific examples

[1898] For example, consider the following scenario in Machida City, Tokyo.

[1899] Target area: Machida City, Tokyo

[1900] Population: 10,000 (3,000 elderly, 7,000 young)

[1901] Existing bus operators: Multiple companies

[1902] City hall staff collect this information and enter it into a system that analyzes the data and calculates the appropriate fee.

[1903] Prompt Sentence Examples

[1904] Below is an example of an input prompt for a generative AI model.

[1905] Please calculate the appropriate fare for a self-driving bus in Machida City, Tokyo under the following conditions.

[1906] The total population is 10,000, of which 3,000 are elderly and 7,000 others.

[1907] There are multiple existing bus operators, each offering different routes.

[1908] Apply discounts for seniors to fair fares and also reflect emotional data.

[1909] In this way, the system of the present invention realizes efficient and fair pricing while taking into consideration regional characteristics and user sentiment.

[1910] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1911] Step 1:

[1912] The user (city hall employee) inputs population information, age distribution, and operation information of existing transportation operators for the target area into the terminal.

[1913] Input: Population information, age distribution, transportation operator operation data

[1914] Output: Formatted data

[1915] Specific operation: Through the interface, users input information about the population and age distribution of each region, as well as the routes and fares of each transportation company.

[1916] Step 2:

[1917] The device formats the input information and sends it to the server.

[1918] Input: User-entered population information, age distribution, and transportation operator operation data

[1919] Output: Formatted data sent to the server

[1920] Specific operation: The terminal standardizes the input data, converts it into CSV or JSON format, and sends it to the server.

[1921] Step 3:

[1922] The server saves or updates the received data in the database.

[1923] Input: Formatted data

[1924] Output: Information stored in the database

[1925] What happens: The server validates the format of the data and inserts new data or updates existing data in the database.

[1926] Step 4:

[1927] The server retrieves and analyzes demographic information and age distribution from the database.

[1928] Input: Population information and age distribution stored in a database

[1929] Output: Demographic data by age group

[1930] Specific operation: The server uses analytical tools such as Pandas to calculate the population percentage of each age group. For example, it calculates that the elderly make up 30% of the total population.

[1931] Step 5:

[1932] The server analyzes the transportation company's routes and number of users.

[1933] Input: Transport operator operation data stored in a database

[1934] Output: Statistical data on number of users by route

[1935] Specific operation: The server uses a geographic information system (GIS) to analyze trends in each route and the number of passengers.

[1936] Step 6:

[1937] The server calculates the appropriate fee based on the analysis results.

[1938] Input: Demographic data, transportation operator ridership data

[1939] Output: Proposed pricing

[1940] Specific operation: The server performs simulations based on past fee data and local economic indicators to calculate the optimal fee. For example, it may set the fee at 200 yen for seniors and 300 yen for general users.

[1941] Step 7:

[1942] The server collects sentiment data and incorporates it into pricing and reporting.

[1943] Input: Real-time emotion data from emotion recognition device

[1944] Output: Pricing reflecting sentiment data

[1945] Specific operation: Based on the emotional data, if the user is in a "happy" state, the system will adapt, such as reducing the general user fee by 10 yen.

[1946] Step 8:

[1947] The server generates a detailed report of the fair charges and sends it to the terminal.

[1948] Input: Data analysis results, sentiment data, pricing

[1949] Output: Detailed report in PDF format

[1950] Specific operation: The server generates a detailed report in Markdown or HTML format, and finally converts it to PDF format and sends it to the terminal. The user (city hall employee) checks the report on the terminal and uses it for final decision making.

[1951] 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.

[1952] 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.

[1953] 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.

[1954] 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.

[1955] 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.

[1956] 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.

[1957] 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).

[1958] 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 Unive...

Claims

1. a means for inputting population information for the target area; A means of inputting the age distribution of the target area; a means for inputting information about existing transportation operators; means for storing or updating the input information in a database; means for analyzing the demographic information and age distribution stored in said database; means for analyzing information about transportation operators stored in the database; A means for calculating an appropriate fee based on the analysis result; means for generating and presenting a detailed report of said fair rates; A system including:

2. 2. The system of claim 1, further comprising means for setting differentiated rates for specific age groups based on said demographic information and age distribution.

3. 2. The system of claim 1, further comprising means for utilizing a geographic information system (GIS) of travel routes in analyzing the information relating to the transportation operators.

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