system

Abstract

We provide the system. [Solution] A means of obtaining the user's schedule information, Means for collecting user location information, Means of transportation and means for calculating travel time, A means of searching for the availability and location conditions of available facilities, A means for recommending the optimal work location based on the aforementioned schedule information, location information, means of transportation information, and facility information, We need a way to analyze past usage data and incorporate it into future recommendations. Includes system.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern diverse working styles, it is required to secure an efficient working place during movement or during breaks in work. However, it has been difficult for conventional systems to select an appropriate place by comprehensively considering schedules, location information, means of movement, and the availability of facilities. Therefore, in order to maximize the performance of organizations and individuals, a mechanism is required to integrally handle these elements and quickly recommend an appropriate working place based on past usage records.

Means for Solving the Problems

[0005] This invention solves the above problems by providing a system that recommends the optimal work location by comprehensively combining the user's schedule information, location information, means of transportation information, and the availability and location conditions of available facilities. Specifically, it includes means for acquiring the user's schedule, collecting real-time location information, and calculating the means of transportation and required time. Furthermore, it searches for the availability and location conditions of available facilities, analyzes past usage data, and reflects this in future recommendations, thereby realizing the provision of efficient and flexible work locations. The system also includes means for the user to easily reserve the recommended work location and has a function to notify the user of this reservation.

[0006] "Means for obtaining user schedule information" refers to a function that retrieves user schedule data from an external data source and determines the next appointment or time slot.

[0007] "Means for collecting user location information" refers to a function that measures the user's current location in real time and records or provides location data.

[0008] "Means for calculating means of transportation and travel time" refers to a function that identifies the means of transportation from the user's current location to the next planned destination and calculates the optimal route and the time required.

[0009] "Means for searching for the availability and location of available facilities" refers to a function for understanding the availability of facilities such as satellite offices, the availability of seats, and the physical conditions.

[0010] The "means for recommending the optimal workspace" refers to a function that comprehensively analyzes collected schedule, location information, transportation methods, and facility information to present the user with the most suitable workspace.

[0011] "A means of analyzing past usage data and reflecting it in future recommendations" refers to a function that analyzes a user's past behavioral data and usage history and uses that data to provide personalized recommendations.

[0012] "Means that allow users to make reservations" refers to functions that enable users to select recommended facilities or services and secure the necessary resources.

[0013] "Means of notifying users of work location information" refers to a function for electronically communicating recommended work locations and reservation details to users. [Brief explanation of the drawing]

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

Mode for Carrying Out the Invention

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

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

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

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

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

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

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

[0022] [First Embodiment]

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

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

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

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

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

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

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

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

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

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

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

[0035] To implement the present invention, it is necessary to build a system that integrates the user's schedule information, location information, means of transportation information, and the availability of available facilities to recommend the optimal work location. The following describes a specific embodiment of the system of the present invention.

[0036] First, the server retrieves the user's schedule information. It obtains data via API from the user's schedule management system or calendar and analyzes the start and end times, location, and other details of the next appointment. This allows the server to determine the user's travel time for the day.

[0037] Next, the device obtains the user's current location. Using location information systems such as smartphones and tablets, it collects GPS data and transmits it to the server. This location information is a crucial element in planning the user's travel.

[0038] The server calculates the optimal mode of transportation based on the user's current location and next destination. Utilizing a mapping system, it evaluates multiple travel options, including walking, driving, and public transport, and calculates the corresponding travel time. By also considering past travel history and user preferences, it provides an optimized travel plan.

[0039] Furthermore, the server retrieves the availability status of nearby satellite offices and other available facilities from a database. It processes data including the location, accessibility, and equipment provided by each facility, and updates their availability in real time.

[0040] By comprehensively analyzing this information, the server recommends the optimal workspace for the user. Candidate workspaces are prioritized based on factors such as travel efficiency, past usage history, and scheduling constraints.

[0041] Users can view recommended workspaces on their devices and make reservations if they like them. Reservations are reflected in the facility's reservation system in real time via the server, allowing users to secure workspaces smoothly.

[0042] Furthermore, users' past usage history is recorded in a database and analyzed by machine learning algorithms. This makes it possible to further personalize future recommendations and continue to provide users with the best possible choices.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The server uses an API to retrieve schedule information from the user's schedule management system. This information includes the start time, end time, and location of each appointment. The server analyzes this data to calculate the user's free time.

[0046] Step 2:

[0047] The device uses its built-in GPS function to determine the user's current location. This location information is transmitted to the server in real time and used to plan the user's movements.

[0048] Step 3:

[0049] The server uses the current location and information about the next planned destination to calculate the mode of transportation. The server utilizes a map service API to evaluate various transportation options such as walking, driving, and public transport, and calculates the corresponding travel time.

[0050] Step 4:

[0051] The server accesses a database of available satellite offices to retrieve information on availability, location, and facilities. The server then organizes the retrieved data and evaluates the accessibility and usability of each facility.

[0052] Step 5:

[0053] The server integrates all of the above information and recommends the best workspace for the user. The recommendation takes into account schedule, current location, mode of transportation, and facility availability. It analyzes and prioritizes the best options.

[0054] Step 6:

[0055] Users can view a list of recommended workspaces from the server on their device. They can then select their preferred option and reserve a workspace.

[0056] Step 7:

[0057] The server receives the user's reservation request and transmits it in real time to the facility's reservation system to complete the reservation of the selected workspace. The reservation status is then fed back to the terminal.

[0058] Step 8:

[0059] The server stores users' past usage history in a database and analyzes the data using machine learning algorithms. The analysis results are used to improve the accuracy of future recommendations.

[0060] (Example 1)

[0061] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0062] Conventional workspace provision systems were unable to efficiently recommend the optimal workspace by comprehensively considering the user's schedule, current location and means of transportation, as well as information on available facilities. As a result, users struggled to optimize travel time and smoothly book facilities, requiring efficient time management.

[0063] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0064] In this invention, the server includes means for acquiring user schedule information through a communication system, means for collecting the user's current location information using a mobile information terminal, and means for calculating means of transportation and travel time using a geographic information system. This enables the user to travel efficiently and quickly reserve available facilities.

[0065] "Means of obtaining user schedule information through a communication system" refers to technologies that access and obtain schedule information from a user's schedule management system or calendar via a network.

[0066] "Means of collecting user's current location information using mobile information terminals" refers to technologies that use mobile devices such as smartphones and tablets to collect information about the user's current location using GPS functionality.

[0067] "Methods for calculating travel methods and travel time using geographic information systems" refers to technologies that utilize geographic information to calculate routes based on multiple travel methods such as walking, driving, and public transport, and to determine the time required.

[0068] "Means for searching for the availability and location characteristics of available facilities from a database" refers to technologies that search for and obtain information about the availability of facilities and the characteristics of their locations from a database, which is the source of aggregated information.

[0069] "A means of recommending the optimal work location by analyzing schedule information, location information, transportation information, and facility information" refers to a technology that comprehensively analyzes various data to select and present the most efficient work location for the user.

[0070] "Methods for analyzing past usage records and reflecting them in future recommendations" refers to technologies that analyze user history data and use that data to make future location recommendations more personalized.

[0071] "A means of notifying users of their choice of workspace based on recommended results" refers to a technology that notifies users of suggested locations based on the analysis results and encourages them to make a selection.

[0072] This invention is a system that recommends the optimal workspace for the user. To implement this system, various hardware and software are used to collect, analyze, and utilize data.

[0073] First, the server retrieves the user's schedule information. To do this, it uses a technique that leverages the API of the scheduling management system and extracts schedule information through OAuth authentication. This allows the server to obtain detailed data about the user's next appointment, such as the start time, end time, and location.

[0074] Next, the device uses GPS to collect the user's current location. It utilizes the location services of smartphones and tablets to accurately collect latitude and longitude data and transmit it to a server. This establishes a foundation for geographically relevant information.

[0075] The server uses a Geographic Information System (GIS) to calculate the mode of transport and the estimated travel time. Specifically, it utilizes a common map API to calculate the optimal route for walking, driving, and public transport, selecting the mode of transport that best matches the user's history and preferences. This functionality helps to streamline travel and minimize travel time.

[0076] Facility availability information is retrieved by the server through database queries. By extracting detailed information such as the availability of usable locations, facilities provided, and location conditions for satellite offices, cafes, etc., a database is built to provide an effective work environment.

[0077] Based on this data, the server recommends the optimal workspace. A specific algorithm analyzes the acquired data to select an efficient location that meets user needs, and then notifies the user of this information.

[0078] Furthermore, based on past usage history, machine learning algorithms make subsequent recommendations more personalized. This process continuously improves the user experience.

[0079] For example, a user might want to find a workspace available in a city after finishing work. This system can recommend a nearby cafe with available seats, taking into account the user's schedule for the day and current location, as well as traffic conditions. If the user accepts the suggestion, they can make a reservation immediately from their terminal.

[0080] Examples of prompt messages include: "When a user has two hours of free time around Tokyo Station, please recommend the most efficient workspace. Please consider available facilities such as cafes and satellite offices, and make recommendations based on transportation options and past usage history."

[0081] Thus, the present invention flexibly connects diverse data sources, enabling the selection of a work location optimized for the user.

[0082] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0083] Step 1:

[0084] The server retrieves user schedule information via the communication network. Specifically, it integrates with the user's schedule management system via API and retrieves the day's schedule data through OAuth authentication. Inputs include the user ID and authentication information, and the output is a list of appointments for the day. The schedule information includes the start time, end time, and location, and the server uses this information to calculate the time slot for the next appointment.

[0085] Step 2:

[0086] The device collects the user's current location information. It uses the GPS function built into smartphones and tablets to obtain latitude and longitude in real time. In this process, the device uses location services and collects GPS data as input. The output is coordinate information about the user's current location, which is sent to the server to determine the user's geographical location.

[0087] Step 3:

[0088] The server calculates the optimal mode of transportation based on the user's current location and next destination. Using a Geographic Information System (GIS), it incorporates current location and destination information as input and performs route searches considering walking, driving, and public transport. The output is the estimated travel time for each route. Furthermore, it takes into account past travel history and user preferences to present an optimized travel plan.

[0089] Step 4:

[0090] The server retrieves the availability of available facilities from a database. The input information includes a list of facilities near the user's current location, and the server executes database queries to check real-time availability and facilities. This results in output facility data including location and equipment information.

[0091] Step 5:

[0092] The server comprehensively analyzes this information to recommend the optimal work location. It uses schedule information, location information, transportation information, and facility information as input and analyzes them using an algorithm. As output, a prioritized list of work locations best suited to the user's conditions is created.

[0093] Step 6:

[0094] The user checks information about recommended workspaces on their terminal and selects a preferred location. Based on the user's selection, they can proceed with the reservation. The reservation request becomes input, the server sends this information to the facility's reservation system, and receives confirmation of the reservation completion as output.

[0095] Step 7:

[0096] The server records users' past usage history and analyzes it to improve future recommendations. The input is usage history data, which is processed using machine learning algorithms. The output is insights to improve the accuracy of personalized recommendations. Through this process, it is possible to continuously provide users with the most suitable services.

[0097] (Application Example 1)

[0098] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0099] Modern users want to efficiently manage their daily plans and quickly secure the optimal workspace. However, conventional systems require the individual manipulation of planning and location information, and the lack of integration of transportation options and facility availability leads to wasted time and effort. Furthermore, integration with autonomous driving systems is insufficient, limiting the means of selecting the optimal route for travel. Therefore, there is a need for a system that effectively aggregates all this information and instantly presents the most efficient options to users.

[0100] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0101] In this invention, the server includes means for acquiring computerized planning information, means for acquiring positioning information, and means for calculating the method and time of travel. This allows users to plan an optimal travel plan based on their schedule and location information, and to efficiently travel and secure workspace through an automated driving system. Furthermore, personalized recommendations that take into account past usage history and real-time facility availability information allow users to respond immediately to changes in their plans, which is expected to significantly improve convenience.

[0102] "Computerized planning information" refers to data in which users' schedules and plans are electronically recorded and managed.

[0103] "Positioning information" refers to data that represents the user's current geographical coordinates, obtained through GPS or other location measurement technologies.

[0104] "Method of transportation" refers to information about the mode of transport the user will use to reach their next destination, such as walking, driving, or using public transport.

[0105] "Travel time" refers to the estimated time required for a user to travel from their current location to their destination using the planned mode of transport.

[0106] "Availability information for available facilities" refers to data that indicates the availability of a facility based on its location and the space it provides.

[0107] "Location information" refers to information about the specific geographical location where the facility is located.

[0108] An "autonomous driving system" is a technology and system that enables a vehicle to autonomously perform driving operations using sensors and software.

[0109] "Recommending the optimal workspace" is a selection method that presents the workspace that best suits the user's requirements.

[0110] "Past usage history" refers to recorded data about the work locations and conditions used by the user in the past.

[0111] To implement this invention, a server, a terminal, and an autonomous driving system must work together. The server first obtains the user's computerized planning information. This process involves collecting data from the user's calendar and schedule management system using an API. The server then collects positioning information. Using GPS and other positioning technologies installed in the terminal, it determines the user's current location and transmits this information to the server. The server also calculates the optimal method and time of travel through computational processing. This is done by utilizing geographic information systems to evaluate which mode of transport is most efficient.

[0112] Next, the server searches for and retrieves information on the availability and location of available facilities from its database. This process allows the server to continuously update facility availability in real time. Furthermore, the server integrates this information and utilizes a generative AI model to recommend the most suitable workspace to the user. In this process, a proprietary algorithm is applied to improve the accuracy of the recommendations based on past usage history. The recommendation of the best workspace used is designed to allow users to easily reserve a location.

[0113] For example, if a user is currently in Shibuya and their next destination is Tokyo Station, the server will calculate the shortest and most efficient route based on the user's schedule. Furthermore, by using an automated driving system, it becomes possible to instantly arrange for available space near the destination.

[0114] An example of a prompt to input into the generative AI model is: "If the user's current location is 'Shibuya' and their next destination is 'Tokyo Station,' please recommend the optimal route for optimally navigating the autonomous vehicle, as well as available workspaces near Tokyo Station." This prompt is intended to encourage highly accurate optimization by the generative AI model.

[0115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0116] Step 1:

[0117] The server uses an API to retrieve the user's computerized planning information. The input requires authentication credentials from the user's scheduling management system, and the output provides specific planning data such as the next destination, start time, and end time. This information serves as foundational data for optimizing the user's daily travel plans.

[0118] Step 2:

[0119] The device uses location measurement technologies such as GPS to obtain the user's current location. The input is positioning information obtainable by the device, and the output is geographic coordinates (latitude and longitude). This data is sent to the server and used to select the optimal mode of transportation to the next destination.

[0120] Step 3:

[0121] The server uses a geographic information system to calculate the optimal mode of travel and travel time from the current location to the next destination. It takes the user's current geographic coordinates and information about the next destination as input, and provides recommended modes of travel (e.g., walking, car, public transport) and their estimated travel times as output. This information is key to achieving efficient travel.

[0122] Step 4:

[0123] The server searches the database for available facility availability and location information. The input requires facility type and location criteria, and the output is a list of candidate facilities and their availability. This process provides data to recommend the most suitable workspace to the user.

[0124] Step 5:

[0125] The server integrates the information it has gathered so far and uses a generative AI model to recommend the most suitable workspace for the user. Inputs include schedule data, current location, mode of transportation, and facility information, and the output is a suggestion of the workspace deemed most appropriate. Based on this suggestion, the server provides the user with the opportunity to make a reservation.

[0126] Step 6:

[0127] Users can review recommended workspaces and make reservations immediately if necessary. Selection and confirmation are based on the user's discretion, and the reserved information is sent to the server. This information is used as feedback to improve future recommendations.

[0128] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0129] To implement the present invention, it is necessary to construct a system that integrates the user's schedule information, location information, means of transportation information, and the availability of available facilities, as well as an emotion engine that recognizes the user's emotions. The following describes a specific embodiment of the system of the present invention.

[0130] The server retrieves user schedule information from the schedule management system using an API. Next, it analyzes the user's upcoming appointments and current free time based on this schedule information. This streamlines the management of user travel and work time.

[0131] The terminal acquires location information via the user's smartphone or wearable device. This location data is transmitted to a server in real time and used to select transportation options and facilities.

[0132] Furthermore, the server uses a map service API to calculate the optimal mode of transportation from the current location to the next destination. In doing so, it takes into account travel time, traffic conditions, and past travel history to provide a highly accurate travel plan.

[0133] Next, the server accesses the database to retrieve information on the availability, location, and equipment of available facilities. This information is updated in real time and used to select a suitable workspace for the user.

[0134] A key feature of this invention is the inclusion of an emotion engine that analyzes the user's emotional state. The terminal uses voice input and a camera module to collect the user's voice tone and facial expression data, and transmits it to the emotion engine. Based on the data obtained from the emotion engine, the server analyzes the user's emotional state and adjusts the environment of the suggested workspace accordingly. For example, it recommends a quiet, relaxing environment for a user who is feeling stressed, and a facility with a social space for someone who is in a sociable mood.

[0135] This allows users to utilize workspaces optimized for their emotional state and schedule, maximizing comfort and productivity. The system notifies users of detailed information about recommended locations and allows for easy booking. Booking information is processed on the server and reflected in the booking system of the selected facility.

[0136] Furthermore, the server stores all of this usage data in a database and analyzes and uses it as data to help with future recommendations. In this way, the present invention provides a comprehensive workspace recommendation system that takes into account a variety of factors such as the user's schedule, location, and emotions.

[0137] The following describes the processing flow.

[0138] Step 1:

[0139] The server retrieves appointment information from the user's scheduling application via an API. Here, it analyzes the start time, end time, location, and content of each appointment registered by the user to determine the next location and time to travel.

[0140] Step 2:

[0141] The device uses its built-in GPS function to determine the user's current location in real time. This location information is transmitted to a server and used as input data for planning transportation.

[0142] Step 3:

[0143] The server uses a map service API to calculate the optimal mode of transportation and estimated travel time from the current location to the next destination. It presents multiple transportation options (walking, car, public transport, etc.) and provides details for each (time, distance, cost).

[0144] Step 4:

[0145] The server accesses a database of satellite offices and coworking spaces to retrieve information on availability, location, and amenities (Wi-Fi, power outlets, noise levels, etc.). This information is updated in real time and organized as available options for the user.

[0146] Step 5:

[0147] The device collects the user's voice and facial expressions using input devices (microphone, camera) and sends them to the emotion engine. The emotion engine uses a machine learning model to analyze the data and determine the user's emotional state.

[0148] Step 6:

[0149] The server integrates emotional data obtained from the emotion engine and evaluates it along with the user's schedule, current location, means of transportation, and facility information. This allows it to recommend the optimal workspace based on the user's emotional state. For example, if a relaxed environment is deemed suitable, it will suggest a quiet workspace; if an active social environment is preferred, it will suggest a facility with a social space.

[0150] Step 7:

[0151] Users can review recommended workspaces from the server on their terminal and make a reservation on the spot if they like it. The reservation process is simple and straightforward through the user interface, and the selected location is secured immediately.

[0152] Step 8:

[0153] The server processes the user's reservation information and synchronizes it with the reservation system of the selected facility to complete the reservation process. This allows the user to secure a competitive workspace.

[0154] Step 9:

[0155] The server stores users' past usage data in a database and performs periodic analysis. This analysis improves the accuracy of future location recommendations, enabling a more personalized experience.

[0156] (Example 2)

[0157] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0158] In modern society, users face numerous appointments and diverse modes of transportation on a daily basis, requiring efficient time management and the selection of appropriate work environments. However, conventional systems have struggled to integrate information such as appointments, location, and emotions to recommend the optimal work environment. In particular, they lacked the ability to adjust the environment according to emotional states, making it impossible to instantly provide the relaxing or social environment that users need.

[0159] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0160] In this invention, the server includes means for acquiring user schedule information, means for collecting user location information, means for calculating means of transportation and travel time, and recommending the optimal work location based on the availability and location conditions of available facilities, means for analyzing the user's emotional state and proposing the optimal work environment based on that emotional state, and means for analyzing past usage history and reflecting it in the next recommendation. As a result, the user can efficiently utilize the optimal work environment based on a multifaceted set of factors including schedule, location, and emotional state.

[0161] "User schedule information" refers to detailed data about a user's schedule that can be obtained from the schedule management system.

[0162] "User location information" refers to data indicating the user's current geographical location, and is obtained from smartphones and wearable devices.

[0163] "Means of transportation" refers to the means of transport available to a user when moving from one point to another.

[0164] "Travel time" refers to the time required for a user to travel from their current location to their destination.

[0165] "Facility availability" refers to information indicating the available space and reservation status of facilities.

[0166] "Location conditions" refers to information regarding the geographical location of the facility and its surrounding environment.

[0167] "Recommending a workspace" refers to the process of identifying and presenting the workspace that best suits the user's needs.

[0168] "User emotional state" refers to the user's current psychological or emotional situation, as analyzed from their voice and facial expressions.

[0169] An "optimal work environment" refers to an environment that has been adjusted to maximize the user's work efficiency and comfort.

[0170] "Past usage history" refers to records of facilities and services that a user has used in the past, providing data that can be used as a reference for future use.

[0171] The system for implementing this invention improves comfort and productivity by using advanced information technology to centrally manage the user's schedule information, location information, and emotional state, and recommending the optimal work environment.

[0172] First, the server collects data from the scheduling management system using APIs to obtain user schedule information. Specifically, by using the API of the scheduling software, it can obtain schedule information such as the date, time, location, and participants of the user. For example, it can use the "Calendar API" or the "Scheduler API".

[0173] Next, the device acquires the user's location information in real time. Using the GPS function of smartphones and wearable devices, it determines the user's current location and sends that data to the server. Location information is important as a criterion for selecting transportation methods and searching for facilities.

[0174] Furthermore, the server uses an emotion analysis engine to analyze the user's emotional state. The terminal collects the user's voice tone and facial expression data using voice input and the camera. This data is sent to an AI algorithm for emotion analysis, which determines the user's stress level, relaxation level, etc. Based on this emotional state, the system suggests the optimal work environment for the user by recommending quiet or sociable environments.

[0175] The server uses a map service API to calculate the optimal mode of transportation from the current location to the next destination. For example, by using the "Map API," it compares multiple modes of transport and provides the optimal route considering travel time and traffic conditions.

[0176] Through database access, the server retrieves information on the availability, location, and facilities of available facilities. This allows the server to recommend the most suitable workspace for the user. Detailed information about the recommended facilities is then communicated to the user, enabling easy booking. Booking information is processed on the server and reflected in the booking system.

[0177] For example, if a user has a meeting scheduled for 3 PM, the server will consider traffic conditions, suggest a suitable cafe, and help the user make a reservation immediately. If the system determines that the user's emotional state requires relaxation, it can also prioritize recommending a quiet cafe.

[0178] An example of a prompt to input into a generative AI model might be something like, "Please suggest a suitable workspace based on my schedule, location, and emotional state."

[0179] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0180] Step 1:

[0181] The server retrieves user schedule information from the schedule management system using an API. Specifically, the server uses the "Calendar API" to extract the user's next appointments and free time. The input is the user's authentication information, and the output is the next appointments and free time. Based on this data, initial data is generated to select the optimal work location according to the user's schedule.

[0182] Step 2:

[0183] The terminal utilizes the GPS function of smartphones and wearable devices to obtain the user's current location in real time. Specifically, it uses a location information service API to obtain latitude and longitude information from the terminal's GPS module. The input is the device's location sensor information, and the output is latitude and longitude location information. This location information is sent to a server and used as a criterion for selecting means of transportation and facilities.

[0184] Step 3:

[0185] The server uses a map service API to calculate the optimal mode of transportation from the user's current location to their next destination. The specific operation involves calling the "Map API" to calculate traffic conditions and travel time. The inputs are the location information obtained in step 2 and the location information of the next destination from step 1, and the output is the optimal travel route and travel time. This makes travel more efficient.

[0186] Step 4:

[0187] The server retrieves the availability and location information of available facilities from the database. Its specific operations include collecting facility information in real time using SQL queries and analyzing that data. The input is the facility database, and the output is a list of available facilities suitable for the user. This information serves as a candidate for suggested workspaces.

[0188] Step 5:

[0189] The device collects the user's voice tone and facial expression data through its camera and microphone, and sends it to an emotion analysis engine to determine their emotional state. Specifically, it analyzes the voice and image data using an AI algorithm. The input is the raw voice and facial expression data, and the output is the emotion analysis result. Based on this result, a recommended working environment is adjusted.

[0190] Step 6:

[0191] The server integrates the aforementioned information and recommends a work environment optimized for the user. Specifically, it uses an algorithm to generate optimal suggestions based on schedule information, location information, and sentiment analysis data. The input is all the data obtained in the previous steps, and the output is the recommended work location. This information is notified to the user, who can then book a facility based on the suggestion.

[0192] Step 7:

[0193] The user reserves a suggested workspace, and this is reflected in the facility's reservation system. The specific process involves completing the reservation operation through the application. The input is the user's reservation information, and the output is the information reflected in the facility's reservation system. This ensures that the necessary workspace is efficiently secured.

[0194] (Application Example 2)

[0195] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0196] In modern society, users face numerous scheduling and travel options, and their emotional states also change daily. This presents a challenge in selecting the optimal workspace that takes all of these factors into account. Therefore, there is a need for workspace recommendations that adapt to the user's emotional state and schedule.

[0197] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0198] In this invention, the server includes means for acquiring user schedule information, means for collecting user location information, and means for analyzing user emotional information. This makes it possible to recommend an optimal workspace according to the user's schedule and emotional state.

[0199] "User schedule information" refers to information about activities and events that the user has planned for the future.

[0200] "User location information" refers to information that indicates the user's current geographical location.

[0201] "Transportation" refers to information about the means of transportation used by the user.

[0202] "Travel time" refers to the time required to reach a destination using a means of transportation.

[0203] "Availability of available facilities" refers to information regarding whether a particular facility is available or not.

[0204] "Location conditions" refers to information about the geographical location of the facility.

[0205] "Emotional information" refers to information that indicates the emotional state a user is currently experiencing.

[0206] An "optimal workspace" is an environment suitable for the task, selected considering the user's schedule, location, means of transportation, facility availability, and emotional information.

[0207] "Past usage history" refers to information about the workspaces and related activity history that the user has used in the past.

[0208] This invention realizes a system that integrates a user's schedule information, location information, mode of transportation, facility availability, and emotional information within an autonomous vehicle to recommend the optimal workspace. The server retrieves the user's schedule information from the schedule management system via API and calculates the predicted travel time and mode of transportation. This enables the system to provide the user with efficient routes and schedules.

[0209] The system, installed in the autonomous vehicle as a terminal, collects real-time location information via the user's smartphone or in-vehicle devices. Based on this data, the server uses a map service API to devise the optimal route to the next destination and can suggest music and in-car environments tailored to the user's emotional state.

[0210] The emotion engine analyzes the user's emotional state based on data acquired from the camera module and voice input device. Based on the analysis results, the server recommends environments that are relaxing or suitable for socializing. For example, if the user needs to relax, the in-car music can be softened, or a scenic route can be chosen.

[0211] This system is implemented using programming languages ​​such as Python and JavaScript (registered trademark), and the devices it can use include iOS and Android (registered trademark) smartphones, as well as in-vehicle computer systems. The server stores and analyzes all of this data to improve the accuracy of future suggestions.

[0212] For example, if a busy business person is riding the train between meetings, the emotional engine can detect stress and play relaxing classical music while taking them along a scenic route through nature.

[0213] Example of a prompt:

[0214] "Please explain a system in which autonomous vehicles suggest the optimal route and in-car environment based on the passenger's emotional state and schedule. Please also explain in detail, with specific examples, how the passenger's emotional data is analyzed and what suggestions are made."

[0215] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0216] Step 1:

[0217] The server retrieves user schedule information from the schedule management system via API. Based on this input data, it analyzes the next scheduled appointment time and current free time, and generates the user's schedule as output. This process establishes a foundation for efficient time management.

[0218] Step 2:

[0219] The terminal acquires real-time location information via the user's smartphone or in-vehicle device. The input is location data, which is sent to the server. Based on this, the system calculates the mode of transport and travel time, and uses this information to suggest the optimal route.

[0220] Step 3:

[0221] The server uses a map service API to calculate the optimal travel route to the next destination. It requires location and mode of transport information as input, and outputs the optimal route and its estimated travel time. By taking past travel history into consideration, it provides the most efficient route for the user.

[0222] Step 4:

[0223] The emotion engine collects and analyzes user emotion data from camera modules and voice input devices. The input data includes facial expression data and voice tone, and based on this, it provides an output representing the user's current emotional state. This analysis allows for adjustments to the in-car environment in the next step.

[0224] Step 5:

[0225] The server integrates emotional information with previously collected data to recommend the optimal workspace based on the user's emotions and schedule. Inputs include schedule information, location information, and emotional information, and the output suggests the best route and in-car environment. Specifically, this includes selecting music and adjusting the air conditioning.

[0226] Step 6:

[0227] The user reviews the suggested route and settings and makes adjustments if necessary. This step involves final adjustments based on the user's preferences, using the server output as a basis. This ensures user comfort and productive time management.

[0228] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0229] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0230] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0231] [Second Embodiment]

[0232] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0233] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0234] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0235] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0236] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0237] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0238] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0239] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0240] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0241] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0242] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0243] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0244] To implement the present invention, it is necessary to build a system that integrates the user's schedule information, location information, means of transportation information, and the availability of available facilities to recommend the optimal work location. The following describes a specific embodiment of the system of the present invention.

[0245] First, the server retrieves the user's schedule information. It obtains data via API from the user's schedule management system or calendar and analyzes the start and end times, location, and other details of the next appointment. This allows the server to determine the user's travel time for the day.

[0246] Next, the device obtains the user's current location. Using location information systems such as smartphones and tablets, it collects GPS data and transmits it to the server. This location information is a crucial element in planning the user's travel.

[0247] The server calculates the optimal mode of transportation based on the user's current location and next destination. Utilizing a mapping system, it evaluates multiple travel options, including walking, driving, and public transport, and calculates the corresponding travel time. By also considering past travel history and user preferences, it provides an optimized travel plan.

[0248] Furthermore, the server retrieves the availability status of nearby satellite offices and other available facilities from a database. It processes data including the location, accessibility, and equipment provided by each facility, and updates their availability in real time.

[0249] By comprehensively analyzing this information, the server recommends the optimal workspace for the user. Candidate workspaces are prioritized based on factors such as travel efficiency, past usage history, and scheduling constraints.

[0250] Users can view recommended workspaces on their devices and make reservations if they like them. Reservations are reflected in the facility's reservation system in real time via the server, allowing users to secure workspaces smoothly.

[0251] Furthermore, users' past usage history is recorded in a database and analyzed by machine learning algorithms. This makes it possible to further personalize future recommendations and continue to provide users with the best possible choices.

[0252] The following describes the processing flow.

[0253] Step 1:

[0254] The server uses an API to retrieve schedule information from the user's schedule management system. This information includes the start time, end time, and location of each appointment. The server analyzes this data to calculate the user's free time.

[0255] Step 2:

[0256] The device uses its built-in GPS function to determine the user's current location. This location information is transmitted to the server in real time and used to plan the user's movements.

[0257] Step 3:

[0258] The server uses the current location and information about the next planned destination to calculate the mode of transportation. The server utilizes a map service API to evaluate various transportation options such as walking, driving, and public transport, and calculates the corresponding travel time.

[0259] Step 4:

[0260] The server accesses a database of available satellite offices to retrieve information on availability, location, and facilities. The server then organizes the retrieved data and evaluates the accessibility and usability of each facility.

[0261] Step 5:

[0262] The server integrates all of the above information and recommends the best workspace for the user. The recommendation takes into account schedule, current location, mode of transportation, and facility availability. It analyzes and prioritizes the best options.

[0263] Step 6:

[0264] Users can view a list of recommended workspaces from the server on their device. They can then select their preferred option and reserve a workspace.

[0265] Step 7:

[0266] The server receives the user's reservation request and transmits it in real time to the facility's reservation system to complete the reservation of the selected workspace. The reservation status is then fed back to the terminal.

[0267] Step 8:

[0268] The server stores users' past usage history in a database and analyzes the data using machine learning algorithms. The analysis results are used to improve the accuracy of future recommendations.

[0269] (Example 1)

[0270] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0271] Conventional workspace provision systems were unable to efficiently recommend the optimal workspace by comprehensively considering the user's schedule, current location and means of transportation, as well as information on available facilities. As a result, users struggled to optimize travel time and smoothly book facilities, requiring efficient time management.

[0272] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0273] In this invention, the server includes means for acquiring user schedule information through a communication system, means for collecting the user's current location information using a mobile information terminal, and means for calculating means of transportation and travel time using a geographic information system. This enables the user to travel efficiently and quickly reserve available facilities.

[0274] "Means of obtaining user schedule information through a communication system" refers to technologies that access and obtain schedule information from a user's schedule management system or calendar via a network.

[0275] "Means of collecting user's current location information using mobile information terminals" refers to technologies that use mobile devices such as smartphones and tablets to collect information about the user's current location using GPS functionality.

[0276] "Methods for calculating travel methods and travel time using geographic information systems" refers to technologies that utilize geographic information to calculate routes based on multiple travel methods such as walking, driving, and public transport, and to determine the time required.

[0277] "Means for searching for the availability and location characteristics of available facilities from a database" refers to technologies that search for and obtain information about the availability of facilities and the characteristics of their locations from a database, which is the source of aggregated information.

[0278] "A means of recommending the optimal work location by analyzing schedule information, location information, transportation information, and facility information" refers to a technology that comprehensively analyzes various data to select and present the most efficient work location for the user.

[0279] "Methods for analyzing past usage records and reflecting them in future recommendations" refers to technologies that analyze user history data and use that data to make future location recommendations more personalized.

[0280] "A means of notifying users of their choice of workspace based on recommended results" refers to a technology that notifies users of suggested locations based on the analysis results and encourages them to make a selection.

[0281] This invention is a system that recommends the optimal workspace for the user. To implement this system, various hardware and software are used to collect, analyze, and utilize data.

[0282] First, the server obtains the user's schedule information. To do this, it uses the API of the scheduling management system and the technology of extracting schedule information through OAuth authentication. As a result, detailed data about the user's next schedule, such as start time, end time, location, etc., can be obtained.

[0283] Next, the terminal uses GPS to collect the user's current location. By making full use of the location information service of smartphones and tablets, it accurately collects the data of latitude and longitude and sends it to the server. This lays the foundation for geographically relevant information.

[0284] The server uses a Geographic Information System (GIS) to calculate the means of transportation and the required time. As specific software, general map APIs are used to calculate the optimal routes for walking, driving, and public transportation respectively, and select the means of transportation that matches the user's history and preferences. This function helps to optimize the movement and minimize the arrival time.

[0285] The server obtains the availability information of facilities through database queries. By extracting detailed information such as the availability status, provided facilities, and location conditions of available places such as satellite offices and cafes, a database for providing an effective working environment is constructed.

[0286] Based on these data, the server recommends the optimal working location. By analyzing the obtained data with a specific algorithm, it is possible to select a place that is efficient and meets the user's needs and notify the user of the information.

[0287] Also, based on past usage records, a machine learning algorithm makes the next recommendation more personalized. Through this process, the user experience is continuously improved.

[0288] For example, a user might want to find a workspace available in a city after finishing work. This system can recommend a nearby cafe with available seats, taking into account the user's schedule for the day and current location, as well as traffic conditions. If the user accepts the suggestion, they can make a reservation immediately from their terminal.

[0289] Examples of prompt messages include: "When a user has two hours of free time around Tokyo Station, please recommend the most efficient workspace. Please consider available facilities such as cafes and satellite offices, and make recommendations based on transportation options and past usage history."

[0290] Thus, the present invention flexibly connects diverse data sources, enabling the selection of a work location optimized for the user.

[0291] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0292] Step 1:

[0293] The server retrieves user schedule information via the communication network. Specifically, it integrates with the user's schedule management system via API and retrieves the day's schedule data through OAuth authentication. Inputs include the user ID and authentication information, and the output is a list of appointments for the day. The schedule information includes the start time, end time, and location, and the server uses this information to calculate the time slot for the next appointment.

[0294] Step 2:

[0295] The device collects the user's current location information. It uses the GPS function built into smartphones and tablets to obtain latitude and longitude in real time. In this process, the device uses location services and collects GPS data as input. The output is coordinate information about the user's current location, which is sent to the server to determine the user's geographical location.

[0296] Step 3:

[0297] The server calculates the optimal mode of transportation based on the user's current location and next destination. Using a Geographic Information System (GIS), it incorporates current location and destination information as input and performs route searches considering walking, driving, and public transport. The output is the estimated travel time for each route. Furthermore, it takes into account past travel history and user preferences to present an optimized travel plan.

[0298] Step 4:

[0299] The server retrieves the availability of available facilities from a database. The input information includes a list of facilities near the user's current location, and the server executes database queries to check real-time availability and facilities. This results in output facility data including location and equipment information.

[0300] Step 5:

[0301] The server comprehensively analyzes this information to recommend the optimal work location. It uses schedule information, location information, transportation information, and facility information as input and analyzes them using an algorithm. As output, a prioritized list of work locations best suited to the user's conditions is created.

[0302] Step 6:

[0303] The user checks information about recommended workspaces on their terminal and selects a preferred location. Based on the user's selection, they can proceed with the reservation. The reservation request becomes input, the server sends this information to the facility's reservation system, and receives confirmation of the reservation completion as output.

[0304] Step 7:

[0305] The server records the user's past usage history and performs analysis for utilization in next-time recommendations. The input is usage history data, which is processed based on machine learning algorithms. The output is insights for improving personalized recommendation accuracy. Through this process, it is possible to continuously provide the user with the optimal service.

[0306] (Application Example 1)

[0307] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0308] Modern users hope to efficiently manage their daily plans and quickly secure an optimal working space. However, in conventional systems, there is an issue of wasting time and effort because it is necessary to individually operate schedule information and position information, and the integration of means of transportation and the availability of facilities is insufficient, and the means for selecting an optimal route when moving is also limited. For this reason, there is a demand for a system that can effectively aggregate all this information and immediately present the most efficient choice for the user.

[0309] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0310] In this invention, the server includes means for acquiring computerized plan information means, means for acquiring positioning information to be collected, and means for calculating the method of movement and the time of movement to be calculated. Thereby, based on the user's schedule and position information, while formulating an optimal movement plan, it becomes possible to efficiently move and secure a working space through an automatic driving system. Furthermore, with personalized recommendations considering past usage history and real-time availability information of facilities, it is expected that the user can immediately respond to plan changes and the convenience will be greatly improved.

[0311] "Computerized planning information" refers to data in which users' schedules and plans are electronically recorded and managed.

[0312] "Positioning information" refers to data that represents the user's current geographical coordinates, obtained through GPS or other location measurement technologies.

[0313] "Method of transportation" refers to information about the mode of transport the user will use to reach their next destination, such as walking, driving, or using public transport.

[0314] "Travel time" refers to the estimated time required for a user to travel from their current location to their destination using the planned mode of transport.

[0315] "Availability information for available facilities" refers to data that indicates the availability of a facility based on its location and the space it provides.

[0316] "Location information" refers to information about the specific geographical location where the facility is located.

[0317] An "autonomous driving system" is a technology and system that enables a vehicle to autonomously perform driving operations using sensors and software.

[0318] "Recommending the optimal workspace" is a selection method that presents the workspace that best suits the user's requirements.

[0319] "Past usage history" refers to recorded data about the work locations and conditions used by the user in the past.

[0320] To implement this invention, a server, a terminal, and an autonomous driving system must work together. The server first obtains the user's computerized planning information. This process involves collecting data from the user's calendar and schedule management system using an API. The server then collects positioning information. Using GPS and other positioning technologies installed in the terminal, it determines the user's current location and transmits this information to the server. The server also calculates the optimal method and time of travel through computational processing. This is done by utilizing geographic information systems to evaluate which mode of transport is most efficient.

[0321] Next, the server searches for and retrieves information on the availability and location of available facilities from its database. This process allows the server to continuously update facility availability in real time. Furthermore, the server integrates this information and utilizes a generative AI model to recommend the most suitable workspace to the user. In this process, a proprietary algorithm is applied to improve the accuracy of the recommendations based on past usage history. The recommendation of the best workspace used is designed to allow users to easily reserve a location.

[0322] For example, if a user is currently in Shibuya and their next destination is Tokyo Station, the server will calculate the shortest and most efficient route based on the user's schedule. Furthermore, by using an automated driving system, it becomes possible to instantly arrange for available space near the destination.

[0323] An example of a prompt to input into the generative AI model is: "If the user's current location is 'Shibuya' and their next destination is 'Tokyo Station,' please recommend the optimal route for optimally navigating the autonomous vehicle, as well as available workspaces near Tokyo Station." This prompt is intended to encourage highly accurate optimization by the generative AI model.

[0324] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0325] Step 1:

[0326] The server uses an API to retrieve the user's computerized planning information. The input requires authentication credentials from the user's scheduling management system, and the output provides specific planning data such as the next destination, start time, and end time. This information serves as foundational data for optimizing the user's daily travel plans.

[0327] Step 2:

[0328] The device uses location measurement technologies such as GPS to obtain the user's current location. The input is positioning information obtainable by the device, and the output is geographic coordinates (latitude and longitude). This data is sent to the server and used to select the optimal mode of transportation to the next destination.

[0329] Step 3:

[0330] The server uses a geographic information system to calculate the optimal mode of travel and travel time from the current location to the next destination. It takes the user's current geographic coordinates and information about the next destination as input, and provides recommended modes of travel (e.g., walking, car, public transport) and their estimated travel times as output. This information is key to achieving efficient travel.

[0331] Step 4:

[0332] The server searches the database for available facility availability and location information. The input requires facility type and location criteria, and the output is a list of candidate facilities and their availability. This process provides data to recommend the most suitable workspace to the user.

[0333] Step 5:

[0334] The server integrates the information it has gathered so far and uses a generative AI model to recommend the most suitable workspace for the user. Inputs include schedule data, current location, mode of transportation, and facility information, and the output is a suggestion of the workspace deemed most appropriate. Based on this suggestion, the server provides the user with the opportunity to make a reservation.

[0335] Step 6:

[0336] Users can review recommended workspaces and make reservations immediately if necessary. Selection and confirmation are based on the user's discretion, and the reserved information is sent to the server. This information is used as feedback to improve future recommendations.

[0337] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0338] To implement the present invention, it is necessary to construct a system that integrates the user's schedule information, location information, means of transportation information, and the availability of available facilities, as well as an emotion engine that recognizes the user's emotions. The following describes a specific embodiment of the system of the present invention.

[0339] The server retrieves user schedule information from the schedule management system using an API. Next, it analyzes the user's upcoming appointments and current free time based on this schedule information. This streamlines the management of user travel and work time.

[0340] The terminal acquires location information via the user's smartphone or wearable device. This location data is transmitted to a server in real time and used to select transportation options and facilities.

[0341] Furthermore, the server uses a map service API to calculate the optimal mode of transportation from the current location to the next destination. In doing so, it takes into account travel time, traffic conditions, and past travel history to provide a highly accurate travel plan.

[0342] Next, the server accesses the database to retrieve information on the availability, location, and equipment of available facilities. This information is updated in real time and used to select a suitable workspace for the user.

[0343] A key feature of this invention is the inclusion of an emotion engine that analyzes the user's emotional state. The terminal uses voice input and a camera module to collect the user's voice tone and facial expression data, and transmits it to the emotion engine. Based on the data obtained from the emotion engine, the server analyzes the user's emotional state and adjusts the environment of the suggested workspace accordingly. For example, it recommends a quiet, relaxing environment for a user who is feeling stressed, and a facility with a social space for someone who is in a sociable mood.

[0344] This allows users to utilize workspaces optimized for their emotional state and schedule, maximizing comfort and productivity. The system notifies users of detailed information about recommended locations and allows for easy booking. Booking information is processed on the server and reflected in the booking system of the selected facility.

[0345] Furthermore, the server stores all of this usage data in a database and analyzes and uses it as data to help with future recommendations. In this way, the present invention provides a comprehensive workspace recommendation system that takes into account a variety of factors such as the user's schedule, location, and emotions.

[0346] The following describes the processing flow.

[0347] Step 1:

[0348] The server retrieves appointment information from the user's scheduling application via an API. Here, it analyzes the start time, end time, location, and content of each appointment registered by the user to determine the next location and time to travel.

[0349] Step 2:

[0350] The device uses its built-in GPS function to determine the user's current location in real time. This location information is transmitted to a server and used as input data for planning transportation.

[0351] Step 3:

[0352] The server uses a map service API to calculate the optimal mode of transportation and estimated travel time from the current location to the next destination. It presents multiple transportation options (walking, car, public transport, etc.) and provides details for each (time, distance, cost).

[0353] Step 4:

[0354] The server accesses a database of satellite offices and coworking spaces to retrieve information on availability, location, and amenities (Wi-Fi, power outlets, noise levels, etc.). This information is updated in real time and organized as available options for the user.

[0355] Step 5:

[0356] The device collects the user's voice and facial expressions using input devices (microphone, camera) and sends them to the emotion engine. The emotion engine uses a machine learning model to analyze the data and determine the user's emotional state.

[0357] Step 6:

[0358] The server integrates emotional data obtained from the emotion engine and evaluates it along with the user's schedule, current location, means of transportation, and facility information. This allows it to recommend the optimal workspace based on the user's emotional state. For example, if a relaxed environment is deemed suitable, it will suggest a quiet workspace; if an active social environment is preferred, it will suggest a facility with a social space.

[0359] Step 7:

[0360] Users can review recommended workspaces from the server on their terminal and make a reservation on the spot if they like it. The reservation process is simple and straightforward through the user interface, and the selected location is secured immediately.

[0361] Step 8:

[0362] The server processes the user's reservation information and synchronizes it with the reservation system of the selected facility to complete the reservation process. This allows the user to secure a competitive workspace.

[0363] Step 9:

[0364] The server stores users' past usage data in a database and performs periodic analysis. This analysis improves the accuracy of future location recommendations, enabling a more personalized experience.

[0365] (Example 2)

[0366] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0367] In modern society, users face numerous appointments and diverse modes of transportation on a daily basis, requiring efficient time management and the selection of appropriate work environments. However, conventional systems have struggled to integrate information such as appointments, location, and emotions to recommend the optimal work environment. In particular, they lacked the ability to adjust the environment according to emotional states, making it impossible to instantly provide the relaxing or social environment that users need.

[0368] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0369] In this invention, the server includes means for acquiring user schedule information, means for collecting user location information, means for calculating means of transportation and travel time, and recommending the optimal work location based on the availability and location conditions of available facilities, means for analyzing the user's emotional state and proposing the optimal work environment based on that emotional state, and means for analyzing past usage history and reflecting it in the next recommendation. As a result, the user can efficiently utilize the optimal work environment based on a multifaceted set of factors including schedule, location, and emotional state.

[0370] "User schedule information" refers to detailed data about a user's schedule that can be obtained from the schedule management system.

[0371] "User location information" refers to data indicating the user's current geographical location, and is obtained from smartphones and wearable devices.

[0372] "Means of transportation" refers to the means of transport available to a user when moving from one point to another.

[0373] "Travel time" refers to the time required for a user to travel from their current location to their destination.

[0374] "Facility availability" refers to information indicating the available space and reservation status of facilities.

[0375] "Location conditions" refers to information regarding the geographical location of the facility and its surrounding environment.

[0376] "Recommending a workspace" refers to the process of identifying and presenting the workspace that best suits the user's needs.

[0377] "User emotional state" refers to the user's current psychological or emotional situation, as analyzed from their voice and facial expressions.

[0378] An "optimal work environment" refers to an environment that has been adjusted to maximize the user's work efficiency and comfort.

[0379] "Past usage history" refers to records of facilities and services that a user has used in the past, providing data that can be used as a reference for future use.

[0380] The system for implementing this invention improves comfort and productivity by using advanced information technology to centrally manage the user's schedule information, location information, and emotional state, and recommending the optimal work environment.

[0381] First, the server collects data from the scheduling management system using APIs to obtain user schedule information. Specifically, by using the API of the scheduling software, it can obtain schedule information such as the date, time, location, and participants of the user. For example, it can use the "Calendar API" or the "Scheduler API".

[0382] Next, the device acquires the user's location information in real time. Using the GPS function of smartphones and wearable devices, it determines the user's current location and sends that data to the server. Location information is important as a criterion for selecting transportation methods and searching for facilities.

[0383] Furthermore, the server uses an emotion analysis engine to analyze the user's emotional state. The terminal collects the user's voice tone and facial expression data using voice input and the camera. This data is sent to an AI algorithm for emotion analysis, which determines the user's stress level, relaxation level, etc. Based on this emotional state, the system suggests the optimal work environment for the user by recommending quiet or sociable environments.

[0384] The server uses a map service API to calculate the optimal mode of transportation from the current location to the next destination. For example, by using the "Map API," it compares multiple modes of transport and provides the optimal route considering travel time and traffic conditions.

[0385] Through database access, the server retrieves information on the availability, location, and facilities of available facilities. This allows the server to recommend the most suitable workspace for the user. Detailed information about the recommended facilities is then communicated to the user, enabling easy booking. Booking information is processed on the server and reflected in the booking system.

[0386] For example, if a user has a meeting scheduled for 3 PM, the server will consider traffic conditions, suggest a suitable cafe, and help the user make a reservation immediately. If the system determines that the user's emotional state requires relaxation, it can also prioritize recommending a quiet cafe.

[0387] An example of a prompt to input into a generative AI model might be something like, "Please suggest a suitable workspace based on my schedule, location, and emotional state."

[0388] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0389] Step 1:

[0390] The server retrieves user schedule information from the schedule management system using an API. Specifically, the server uses the "Calendar API" to extract the user's next appointments and free time. The input is the user's authentication information, and the output is the next appointments and free time. Based on this data, initial data is generated to select the optimal work location according to the user's schedule.

[0391] Step 2:

[0392] The terminal utilizes the GPS function of smartphones and wearable devices to obtain the user's current location in real time. Specifically, it uses a location information service API to obtain latitude and longitude information from the terminal's GPS module. The input is the device's location sensor information, and the output is latitude and longitude location information. This location information is sent to a server and used as a criterion for selecting means of transportation and facilities.

[0393] Step 3:

[0394] The server uses a map service API to calculate the optimal mode of transportation from the user's current location to their next destination. The specific operation involves calling the "Map API" to calculate traffic conditions and travel time. The inputs are the location information obtained in step 2 and the location information of the next destination from step 1, and the output is the optimal travel route and travel time. This makes travel more efficient.

[0395] Step 4:

[0396] The server retrieves the availability and location information of available facilities from the database. Its specific operations include collecting facility information in real time using SQL queries and analyzing that data. The input is the facility database, and the output is a list of available facilities suitable for the user. This information serves as a candidate for suggested workspaces.

[0397] Step 5:

[0398] The device collects the user's voice tone and facial expression data through its camera and microphone, and sends it to an emotion analysis engine to determine their emotional state. Specifically, it analyzes the voice and image data using an AI algorithm. The input is the raw voice and facial expression data, and the output is the emotion analysis result. Based on this result, a recommended working environment is adjusted.

[0399] Step 6:

[0400] The server integrates the aforementioned information and recommends a work environment optimized for the user. Specifically, it uses an algorithm to generate optimal suggestions based on schedule information, location information, and sentiment analysis data. The input is all the data obtained in the previous steps, and the output is the recommended work location. This information is notified to the user, who can then book a facility based on the suggestion.

[0401] Step 7:

[0402] The user reserves a suggested workspace, and this is reflected in the facility's reservation system. The specific process involves completing the reservation operation through the application. The input is the user's reservation information, and the output is the information reflected in the facility's reservation system. This ensures that the necessary workspace is efficiently secured.

[0403] (Application Example 2)

[0404] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0405] In modern society, users face numerous scheduling and travel options, and their emotional states also change daily. This presents a challenge in selecting the optimal workspace that takes all of these factors into account. Therefore, there is a need for workspace recommendations that adapt to the user's emotional state and schedule.

[0406] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0407] In this invention, the server includes means for acquiring user schedule information, means for collecting user location information, and means for analyzing user emotional information. This makes it possible to recommend an optimal workspace according to the user's schedule and emotional state.

[0408] "User schedule information" refers to information about activities and events that the user has planned for the future.

[0409] "User location information" refers to information that indicates the user's current geographical location.

[0410] "Transportation" refers to information about the means of transportation used by the user.

[0411] "Travel time" refers to the time required to reach a destination using a means of transportation.

[0412] "Availability of available facilities" refers to information regarding whether a particular facility is available or not.

[0413] "Location conditions" refers to information about the geographical location of the facility.

[0414] "Emotional information" refers to information that indicates the emotional state a user is currently experiencing.

[0415] An "optimal workspace" is an environment suitable for the task, selected considering the user's schedule, location, means of transportation, facility availability, and emotional information.

[0416] "Past usage history" refers to information about the workspaces and related activity history that the user has used in the past.

[0417] This invention realizes a system that integrates a user's schedule information, location information, mode of transportation, facility availability, and emotional information within an autonomous vehicle to recommend the optimal workspace. The server retrieves the user's schedule information from the schedule management system via API and calculates the predicted travel time and mode of transportation. This enables the system to provide the user with efficient routes and schedules.

[0418] The system, installed in the autonomous vehicle as a terminal, collects real-time location information via the user's smartphone or in-vehicle devices. Based on this data, the server uses a map service API to devise the optimal route to the next destination and can suggest music and in-car environments tailored to the user's emotional state.

[0419] The emotion engine analyzes the user's emotional state based on data acquired from the camera module and voice input device. Based on the analysis results, the server recommends environments that are relaxing or suitable for socializing. For example, if the user needs to relax, the in-car music can be softened, or a scenic route can be chosen.

[0420] This system is implemented using programming languages ​​such as Python and JavaScript, and the devices it can use include iOS and Android smartphones, as well as in-vehicle computer systems. The server stores and analyzes all of this data to improve the accuracy of future suggestions.

[0421] For example, if a busy business person is riding the train between meetings, the emotional engine can detect stress and play relaxing classical music while taking them along a scenic route through nature.

[0422] Example of a prompt:

[0423] "Please explain a system in which autonomous vehicles suggest the optimal route and in-car environment based on the passenger's emotional state and schedule. Please also explain in detail, with specific examples, how the passenger's emotional data is analyzed and what suggestions are made."

[0424] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0425] Step 1:

[0426] The server retrieves user schedule information from the schedule management system via API. Based on this input data, it analyzes the next scheduled appointment time and current free time, and generates the user's schedule as output. This process establishes a foundation for efficient time management.

[0427] Step 2:

[0428] The terminal acquires real-time location information via the user's smartphone or in-vehicle device. The input is location data, which is sent to the server. Based on this, the system calculates the mode of transport and travel time, and uses this information to suggest the optimal route.

[0429] Step 3:

[0430] The server uses a map service API to calculate the optimal travel route to the next destination. It requires location and mode of transport information as input, and outputs the optimal route and its estimated travel time. By taking past travel history into consideration, it provides the most efficient route for the user.

[0431] Step 4:

[0432] The emotion engine collects and analyzes user emotion data from camera modules and voice input devices. The input data includes facial expression data and voice tone, and based on this, it provides an output representing the user's current emotional state. This analysis allows for adjustments to the in-car environment in the next step.

[0433] Step 5:

[0434] The server integrates emotional information with previously collected data to recommend the optimal workspace based on the user's emotions and schedule. Inputs include schedule information, location information, and emotional information, and the output suggests the best route and in-car environment. Specifically, this includes selecting music and adjusting the air conditioning.

[0435] Step 6:

[0436] The user reviews the suggested route and settings and makes adjustments if necessary. This step involves final adjustments based on the user's preferences, using the server output as a basis. This ensures user comfort and productive time management.

[0437] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0438] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0439] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0440] [Third Embodiment]

[0441] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0442] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0443] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0444] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0445] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0446] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0447] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0448] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0449] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0450] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0451] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0452] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0453] To implement the present invention, it is necessary to build a system that integrates the user's schedule information, location information, means of transportation information, and the availability of available facilities to recommend the optimal work location. The following describes a specific embodiment of the system of the present invention.

[0454] First, the server retrieves the user's schedule information. It obtains data via API from the user's schedule management system or calendar and analyzes the start and end times, location, and other details of the next appointment. This allows the server to determine the user's travel time for the day.

[0455] Next, the device obtains the user's current location. Using location information systems such as smartphones and tablets, it collects GPS data and transmits it to the server. This location information is a crucial element in planning the user's travel.

[0456] The server calculates the optimal mode of transportation based on the user's current location and next destination. Utilizing a mapping system, it evaluates multiple travel options, including walking, driving, and public transport, and calculates the corresponding travel time. By also considering past travel history and user preferences, it provides an optimized travel plan.

[0457] Furthermore, the server retrieves the availability status of nearby satellite offices and other available facilities from a database. It processes data including the location, accessibility, and equipment provided by each facility, and updates their availability in real time.

[0458] By comprehensively analyzing this information, the server recommends the optimal workspace for the user. Candidate workspaces are prioritized based on factors such as travel efficiency, past usage history, and scheduling constraints.

[0459] Users can view recommended workspaces on their devices and make reservations if they like them. Reservations are reflected in the facility's reservation system in real time via the server, allowing users to secure workspaces smoothly.

[0460] Furthermore, users' past usage history is recorded in a database and analyzed by machine learning algorithms. This makes it possible to further personalize future recommendations and continue to provide users with the best possible choices.

[0461] The following describes the processing flow.

[0462] Step 1:

[0463] The server uses an API to retrieve schedule information from the user's schedule management system. This information includes the start time, end time, and location of each appointment. The server analyzes this data to calculate the user's free time.

[0464] Step 2:

[0465] The device uses its built-in GPS function to determine the user's current location. This location information is transmitted to the server in real time and used to plan the user's movements.

[0466] Step 3:

[0467] The server uses the current location and information about the next planned destination to calculate the mode of transportation. The server utilizes a map service API to evaluate various transportation options such as walking, driving, and public transport, and calculates the corresponding travel time.

[0468] Step 4:

[0469] The server accesses a database of available satellite offices to retrieve information on availability, location, and facilities. The server then organizes the retrieved data and evaluates the accessibility and usability of each facility.

[0470] Step 5:

[0471] The server integrates all of the above information and recommends the best workspace for the user. The recommendation takes into account schedule, current location, mode of transportation, and facility availability. It analyzes and prioritizes the best options.

[0472] Step 6:

[0473] Users can view a list of recommended workspaces from the server on their device. They can then select their preferred option and reserve a workspace.

[0474] Step 7:

[0475] The server receives the user's reservation request and transmits it in real time to the facility's reservation system to complete the reservation of the selected workspace. The reservation status is then fed back to the terminal.

[0476] Step 8:

[0477] The server stores users' past usage history in a database and analyzes the data using machine learning algorithms. The analysis results are used to improve the accuracy of future recommendations.

[0478] (Example 1)

[0479] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0480] Conventional workspace provision systems were unable to efficiently recommend the optimal workspace by comprehensively considering the user's schedule, current location and means of transportation, as well as information on available facilities. As a result, users struggled to optimize travel time and smoothly book facilities, requiring efficient time management.

[0481] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0482] In this invention, the server includes means for acquiring user schedule information through a communication system, means for collecting the user's current location information using a mobile information terminal, and means for calculating means of transportation and travel time using a geographic information system. This enables the user to travel efficiently and quickly reserve available facilities.

[0483] "Means of obtaining user schedule information through a communication system" refers to technologies that access and obtain schedule information from a user's schedule management system or calendar via a network.

[0484] "Means of collecting user's current location information using mobile information terminals" refers to technologies that use mobile devices such as smartphones and tablets to collect information about the user's current location using GPS functionality.

[0485] "Methods for calculating travel methods and travel time using geographic information systems" refers to technologies that utilize geographic information to calculate routes based on multiple travel methods such as walking, driving, and public transport, and to determine the time required.

[0486] "Means for searching for the availability and location characteristics of available facilities from a database" refers to technologies that search for and obtain information about the availability of facilities and the characteristics of their locations from a database, which is the source of aggregated information.

[0487] "A means of recommending the optimal work location by analyzing schedule information, location information, transportation information, and facility information" refers to a technology that comprehensively analyzes various data to select and present the most efficient work location for the user.

[0488] "Methods for analyzing past usage records and reflecting them in future recommendations" refers to technologies that analyze user history data and use that data to make future location recommendations more personalized.

[0489] "A means of notifying users of their choice of workspace based on recommended results" refers to a technology that notifies users of suggested locations based on the analysis results and encourages them to make a selection.

[0490] This invention is a system that recommends the optimal workspace for the user. To implement this system, various hardware and software are used to collect, analyze, and utilize data.

[0491] First, the server retrieves the user's schedule information. To do this, it uses a technique that leverages the API of the scheduling management system and extracts schedule information through OAuth authentication. This allows the server to obtain detailed data about the user's next appointment, such as the start time, end time, and location.

[0492] Next, the device uses GPS to collect the user's current location. It utilizes the location services of smartphones and tablets to accurately collect latitude and longitude data and transmit it to a server. This establishes a foundation for geographically relevant information.

[0493] The server uses a Geographic Information System (GIS) to calculate the mode of transport and the estimated travel time. Specifically, it utilizes a common map API to calculate the optimal route for walking, driving, and public transport, selecting the mode of transport that best matches the user's history and preferences. This functionality helps to streamline travel and minimize travel time.

[0494] Facility availability information is retrieved by the server through database queries. By extracting detailed information such as the availability of usable locations, facilities provided, and location conditions for satellite offices, cafes, etc., a database is built to provide an effective work environment.

[0495] Based on this data, the server recommends the optimal workspace. A specific algorithm analyzes the acquired data to select an efficient location that meets user needs, and then notifies the user of this information.

[0496] Furthermore, based on past usage history, machine learning algorithms make subsequent recommendations more personalized. This process continuously improves the user experience.

[0497] For example, a user might want to find a workspace available in a city after finishing work. This system can recommend a nearby cafe with available seats, taking into account the user's schedule for the day and current location, as well as traffic conditions. If the user accepts the suggestion, they can make a reservation immediately from their terminal.

[0498] Examples of prompt messages include: "When a user has two hours of free time around Tokyo Station, please recommend the most efficient workspace. Please consider available facilities such as cafes and satellite offices, and make recommendations based on transportation options and past usage history."

[0499] Thus, the present invention flexibly connects diverse data sources, enabling the selection of a work location optimized for the user.

[0500] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0501] Step 1:

[0502] The server retrieves user schedule information via the communication network. Specifically, it integrates with the user's schedule management system via API and retrieves the day's schedule data through OAuth authentication. Inputs include the user ID and authentication information, and the output is a list of appointments for the day. The schedule information includes the start time, end time, and location, and the server uses this information to calculate the time slot for the next appointment.

[0503] Step 2:

[0504] The device collects the user's current location information. It uses the GPS function built into smartphones and tablets to obtain latitude and longitude in real time. In this process, the device uses location services and collects GPS data as input. The output is coordinate information about the user's current location, which is sent to the server to determine the user's geographical location.

[0505] Step 3:

[0506] The server calculates the optimal mode of transportation based on the user's current location and next destination. Using a Geographic Information System (GIS), it incorporates current location and destination information as input and performs route searches considering walking, driving, and public transport. The output is the estimated travel time for each route. Furthermore, it takes into account past travel history and user preferences to present an optimized travel plan.

[0507] Step 4:

[0508] The server retrieves the availability of available facilities from a database. The input information includes a list of facilities near the user's current location, and the server executes database queries to check real-time availability and facilities. This results in output facility data including location and equipment information.

[0509] Step 5:

[0510] The server comprehensively analyzes this information to recommend the optimal work location. It uses schedule information, location information, transportation information, and facility information as input and analyzes them using an algorithm. As output, a prioritized list of work locations best suited to the user's conditions is created.

[0511] Step 6:

[0512] The user checks information about recommended workspaces on their terminal and selects a preferred location. Based on the user's selection, they can proceed with the reservation. The reservation request becomes input, the server sends this information to the facility's reservation system, and receives confirmation of the reservation completion as output.

[0513] Step 7:

[0514] The server records users' past usage history and analyzes it to improve future recommendations. The input is usage history data, which is processed using machine learning algorithms. The output is insights to improve the accuracy of personalized recommendations. Through this process, it is possible to continuously provide users with the most suitable services.

[0515] (Application Example 1)

[0516] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0517] Modern users want to efficiently manage their daily plans and quickly secure the optimal workspace. However, conventional systems require the individual manipulation of planning and location information, and the lack of integration of transportation options and facility availability leads to wasted time and effort. Furthermore, integration with autonomous driving systems is insufficient, limiting the means of selecting the optimal route for travel. Therefore, there is a need for a system that effectively aggregates all this information and instantly presents the most efficient options to users.

[0518] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0519] In this invention, the server includes means for acquiring computerized planning information, means for acquiring positioning information, and means for calculating the method and time of travel. This allows users to plan an optimal travel plan based on their schedule and location information, and to efficiently travel and secure workspace through an automated driving system. Furthermore, personalized recommendations that take into account past usage history and real-time facility availability information allow users to respond immediately to changes in their plans, which is expected to significantly improve convenience.

[0520] "Computerized planning information" refers to data in which users' schedules and plans are electronically recorded and managed.

[0521] "Positioning information" refers to data that represents the user's current geographical coordinates, obtained through GPS or other location measurement technologies.

[0522] "Method of transportation" refers to information about the mode of transport the user will use to reach their next destination, such as walking, driving, or using public transport.

[0523] "Travel time" refers to the estimated time required for a user to travel from their current location to their destination using the planned mode of transport.

[0524] "Availability information for available facilities" refers to data that indicates the availability of a facility based on its location and the space it provides.

[0525] "Location information" refers to information about the specific geographical location where the facility is located.

[0526] An "autonomous driving system" is a technology and system that enables a vehicle to autonomously perform driving operations using sensors and software.

[0527] "Recommending the optimal workspace" is a selection method that presents the workspace that best suits the user's requirements.

[0528] "Past usage history" refers to recorded data about the work locations and conditions used by the user in the past.

[0529] To implement this invention, a server, a terminal, and an autonomous driving system must work together. The server first obtains the user's computerized planning information. This process involves collecting data from the user's calendar and schedule management system using an API. The server then collects positioning information. Using GPS and other positioning technologies installed in the terminal, it determines the user's current location and transmits this information to the server. The server also calculates the optimal method and time of travel through computational processing. This is done by utilizing geographic information systems to evaluate which mode of transport is most efficient.

[0530] Next, the server searches for and retrieves information on the availability and location of available facilities from its database. This process allows the server to continuously update facility availability in real time. Furthermore, the server integrates this information and utilizes a generative AI model to recommend the most suitable workspace to the user. In this process, a proprietary algorithm is applied to improve the accuracy of the recommendations based on past usage history. The recommendation of the best workspace used is designed to allow users to easily reserve a location.

[0531] For example, if a user is currently in Shibuya and their next destination is Tokyo Station, the server will calculate the shortest and most efficient route based on the user's schedule. Furthermore, by using an automated driving system, it becomes possible to instantly arrange for available space near the destination.

[0532] An example of a prompt to input into the generative AI model is: "If the user's current location is 'Shibuya' and their next destination is 'Tokyo Station,' please recommend the optimal route for optimally navigating the autonomous vehicle, as well as available workspaces near Tokyo Station." This prompt is intended to encourage highly accurate optimization by the generative AI model.

[0533] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0534] Step 1:

[0535] The server uses an API to retrieve the user's computerized planning information. The input requires authentication credentials from the user's scheduling management system, and the output provides specific planning data such as the next destination, start time, and end time. This information serves as foundational data for optimizing the user's daily travel plans.

[0536] Step 2:

[0537] The device uses location measurement technologies such as GPS to obtain the user's current location. The input is positioning information obtainable by the device, and the output is geographic coordinates (latitude and longitude). This data is sent to the server and used to select the optimal mode of transportation to the next destination.

[0538] Step 3:

[0539] The server uses a geographic information system to calculate the optimal mode of travel and travel time from the current location to the next destination. It takes the user's current geographic coordinates and information about the next destination as input, and provides recommended modes of travel (e.g., walking, car, public transport) and their estimated travel times as output. This information is key to achieving efficient travel.

[0540] Step 4:

[0541] The server searches the database for available facility availability and location information. The input requires facility type and location criteria, and the output is a list of candidate facilities and their availability. This process provides data to recommend the most suitable workspace to the user.

[0542] Step 5:

[0543] The server integrates the information it has gathered so far and uses a generative AI model to recommend the most suitable workspace for the user. Inputs include schedule data, current location, mode of transportation, and facility information, and the output is a suggestion of the workspace deemed most appropriate. Based on this suggestion, the server provides the user with the opportunity to make a reservation.

[0544] Step 6:

[0545] Users can review recommended workspaces and make reservations immediately if necessary. Selection and confirmation are based on the user's discretion, and the reserved information is sent to the server. This information is used as feedback to improve future recommendations.

[0546] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0547] To implement the present invention, it is necessary to construct a system that integrates the user's schedule information, location information, means of transportation information, and the availability of available facilities, as well as an emotion engine that recognizes the user's emotions. The following describes a specific embodiment of the system of the present invention.

[0548] The server retrieves user schedule information from the schedule management system using an API. Next, it analyzes the user's upcoming appointments and current free time based on this schedule information. This streamlines the management of user travel and work time.

[0549] The terminal acquires location information via the user's smartphone or wearable device. This location data is transmitted to a server in real time and used to select transportation options and facilities.

[0550] Furthermore, the server uses a map service API to calculate the optimal mode of transportation from the current location to the next destination. In doing so, it takes into account travel time, traffic conditions, and past travel history to provide a highly accurate travel plan.

[0551] Next, the server accesses the database to retrieve information on the availability, location, and equipment of available facilities. This information is updated in real time and used to select a suitable workspace for the user.

[0552] A key feature of this invention is the inclusion of an emotion engine that analyzes the user's emotional state. The terminal uses voice input and a camera module to collect the user's voice tone and facial expression data, and transmits it to the emotion engine. Based on the data obtained from the emotion engine, the server analyzes the user's emotional state and adjusts the environment of the suggested workspace accordingly. For example, it recommends a quiet, relaxing environment for a user who is feeling stressed, and a facility with a social space for someone who is in a sociable mood.

[0553] This allows users to utilize workspaces optimized for their emotional state and schedule, maximizing comfort and productivity. The system notifies users of detailed information about recommended locations and allows for easy booking. Booking information is processed on the server and reflected in the booking system of the selected facility.

[0554] Furthermore, the server stores all of this usage data in a database and analyzes and uses it as data to help with future recommendations. In this way, the present invention provides a comprehensive workspace recommendation system that takes into account a variety of factors such as the user's schedule, location, and emotions.

[0555] The following describes the processing flow.

[0556] Step 1:

[0557] The server retrieves appointment information from the user's scheduling application via an API. Here, it analyzes the start time, end time, location, and content of each appointment registered by the user to determine the next location and time to travel.

[0558] Step 2:

[0559] The device uses its built-in GPS function to determine the user's current location in real time. This location information is transmitted to a server and used as input data for planning transportation.

[0560] Step 3:

[0561] The server uses a map service API to calculate the optimal mode of transportation and estimated travel time from the current location to the next destination. It presents multiple transportation options (walking, car, public transport, etc.) and provides details for each (time, distance, cost).

[0562] Step 4:

[0563] The server accesses a database of satellite offices and coworking spaces to retrieve information on availability, location, and amenities (Wi-Fi, power outlets, noise levels, etc.). This information is updated in real time and organized as available options for the user.

[0564] Step 5:

[0565] The device collects the user's voice and facial expressions using input devices (microphone, camera) and sends them to the emotion engine. The emotion engine uses a machine learning model to analyze the data and determine the user's emotional state.

[0566] Step 6:

[0567] The server integrates emotional data obtained from the emotion engine and evaluates it along with the user's schedule, current location, means of transportation, and facility information. This allows it to recommend the optimal workspace based on the user's emotional state. For example, if a relaxed environment is deemed suitable, it will suggest a quiet workspace; if an active social environment is preferred, it will suggest a facility with a social space.

[0568] Step 7:

[0569] Users can review recommended workspaces from the server on their terminal and make a reservation on the spot if they like it. The reservation process is simple and straightforward through the user interface, and the selected location is secured immediately.

[0570] Step 8:

[0571] The server processes the user's reservation information and synchronizes it with the reservation system of the selected facility to complete the reservation process. This allows the user to secure a competitive workspace.

[0572] Step 9:

[0573] The server stores users' past usage data in a database and performs periodic analysis. This analysis improves the accuracy of future location recommendations, enabling a more personalized experience.

[0574] (Example 2)

[0575] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0576] In modern society, users face numerous appointments and diverse modes of transportation on a daily basis, requiring efficient time management and the selection of appropriate work environments. However, conventional systems have struggled to integrate information such as appointments, location, and emotions to recommend the optimal work environment. In particular, they lacked the ability to adjust the environment according to emotional states, making it impossible to instantly provide the relaxing or social environment that users need.

[0577] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0578] In this invention, the server includes means for acquiring user schedule information, means for collecting user location information, means for calculating means of transportation and travel time, and recommending the optimal work location based on the availability and location conditions of available facilities, means for analyzing the user's emotional state and proposing the optimal work environment based on that emotional state, and means for analyzing past usage history and reflecting it in the next recommendation. As a result, the user can efficiently utilize the optimal work environment based on a multifaceted set of factors including schedule, location, and emotional state.

[0579] "User schedule information" refers to detailed data about a user's schedule that can be obtained from the schedule management system.

[0580] "User location information" refers to data indicating the user's current geographical location, and is obtained from smartphones and wearable devices.

[0581] "Means of transportation" refers to the means of transport available to a user when moving from one point to another.

[0582] "Travel time" refers to the time required for a user to travel from their current location to their destination.

[0583] "Facility availability" refers to information indicating the available space and reservation status of facilities.

[0584] "Location conditions" refers to information regarding the geographical location of the facility and its surrounding environment.

[0585] "Recommending a workspace" refers to the process of identifying and presenting the workspace that best suits the user's needs.

[0586] "User emotional state" refers to the user's current psychological or emotional situation, as analyzed from their voice and facial expressions.

[0587] An "optimal work environment" refers to an environment that has been adjusted to maximize the user's work efficiency and comfort.

[0588] "Past usage history" refers to records of facilities and services that a user has used in the past, providing data that can be used as a reference for future use.

[0589] The system for implementing this invention improves comfort and productivity by using advanced information technology to centrally manage the user's schedule information, location information, and emotional state, and recommending the optimal work environment.

[0590] First, the server collects data from the scheduling management system using APIs to obtain user schedule information. Specifically, by using the API of the scheduling software, it can obtain schedule information such as the date, time, location, and participants of the user. For example, it can use the "Calendar API" or the "Scheduler API".

[0591] Next, the device acquires the user's location information in real time. Using the GPS function of smartphones and wearable devices, it determines the user's current location and sends that data to the server. Location information is important as a criterion for selecting transportation methods and searching for facilities.

[0592] Furthermore, the server uses an emotion analysis engine to analyze the user's emotional state. The terminal collects the user's voice tone and facial expression data using voice input and the camera. This data is sent to an AI algorithm for emotion analysis, which determines the user's stress level, relaxation level, etc. Based on this emotional state, the system suggests the optimal work environment for the user by recommending quiet or sociable environments.

[0593] The server uses a map service API to calculate the optimal mode of transportation from the current location to the next destination. For example, by using the "Map API," it compares multiple modes of transport and provides the optimal route considering travel time and traffic conditions.

[0594] Through database access, the server retrieves information on the availability, location, and facilities of available facilities. This allows the server to recommend the most suitable workspace for the user. Detailed information about the recommended facilities is then communicated to the user, enabling easy booking. Booking information is processed on the server and reflected in the booking system.

[0595] For example, if a user has a meeting scheduled for 3 PM, the server will consider traffic conditions, suggest a suitable cafe, and help the user make a reservation immediately. If the system determines that the user's emotional state requires relaxation, it can also prioritize recommending a quiet cafe.

[0596] An example of a prompt to input into a generative AI model might be something like, "Please suggest a suitable workspace based on my schedule, location, and emotional state."

[0597] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0598] Step 1:

[0599] The server retrieves user schedule information from the schedule management system using an API. Specifically, the server uses the "Calendar API" to extract the user's next appointments and free time. The input is the user's authentication information, and the output is the next appointments and free time. Based on this data, initial data is generated to select the optimal work location according to the user's schedule.

[0600] Step 2:

[0601] The terminal utilizes the GPS function of smartphones and wearable devices to obtain the user's current location in real time. Specifically, it uses a location information service API to obtain latitude and longitude information from the terminal's GPS module. The input is the device's location sensor information, and the output is latitude and longitude location information. This location information is sent to a server and used as a criterion for selecting means of transportation and facilities.

[0602] Step 3:

[0603] The server uses a map service API to calculate the optimal mode of transportation from the user's current location to their next destination. The specific operation involves calling the "Map API" to calculate traffic conditions and travel time. The inputs are the location information obtained in step 2 and the location information of the next destination from step 1, and the output is the optimal travel route and travel time. This makes travel more efficient.

[0604] Step 4:

[0605] The server retrieves the availability and location information of available facilities from the database. Its specific operations include collecting facility information in real time using SQL queries and analyzing that data. The input is the facility database, and the output is a list of available facilities suitable for the user. This information serves as a candidate for suggested workspaces.

[0606] Step 5:

[0607] The device collects the user's voice tone and facial expression data through its camera and microphone, and sends it to an emotion analysis engine to determine their emotional state. Specifically, it analyzes the voice and image data using an AI algorithm. The input is the raw voice and facial expression data, and the output is the emotion analysis result. Based on this result, a recommended working environment is adjusted.

[0608] Step 6:

[0609] The server integrates the aforementioned information and recommends a work environment optimized for the user. Specifically, it uses an algorithm to generate optimal suggestions based on schedule information, location information, and sentiment analysis data. The input is all the data obtained in the previous steps, and the output is the recommended work location. This information is notified to the user, who can then book a facility based on the suggestion.

[0610] Step 7:

[0611] The user reserves a suggested workspace, and this is reflected in the facility's reservation system. The specific process involves completing the reservation operation through the application. The input is the user's reservation information, and the output is the information reflected in the facility's reservation system. This ensures that the necessary workspace is efficiently secured.

[0612] (Application Example 2)

[0613] Next, we will explain Application Example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0614] In modern society, users face numerous scheduling and travel options, and their emotional states also change daily. This presents a challenge in selecting the optimal workspace that takes all of these factors into account. Therefore, there is a need for workspace recommendations that adapt to the user's emotional state and schedule.

[0615] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0616] In this invention, the server includes means for acquiring user schedule information, means for collecting user location information, and means for analyzing user emotional information. This makes it possible to recommend an optimal workspace according to the user's schedule and emotional state.

[0617] "User schedule information" refers to information about activities and events that the user has planned for the future.

[0618] "User location information" refers to information that indicates the user's current geographical location.

[0619] "Transportation" refers to information about the means of transportation used by the user.

[0620] "Travel time" refers to the time required to reach a destination using a means of transportation.

[0621] "Availability of available facilities" refers to information regarding whether a particular facility is available or not.

[0622] "Location conditions" refers to information about the geographical location of the facility.

[0623] "Emotional information" refers to information that indicates the emotional state a user is currently experiencing.

[0624] An "optimal workspace" is an environment suitable for the task, selected considering the user's schedule, location, means of transportation, facility availability, and emotional information.

[0625] "Past usage history" refers to information about the workspaces and related activity history that the user has used in the past.

[0626] This invention realizes a system that integrates a user's schedule information, location information, mode of transportation, facility availability, and emotional information within an autonomous vehicle to recommend the optimal workspace. The server retrieves the user's schedule information from the schedule management system via API and calculates the predicted travel time and mode of transportation. This enables the system to provide the user with efficient routes and schedules.

[0627] The system, installed in the autonomous vehicle as a terminal, collects real-time location information via the user's smartphone or in-vehicle devices. Based on this data, the server uses a map service API to devise the optimal route to the next destination and can suggest music and in-car environments tailored to the user's emotional state.

[0628] The emotion engine analyzes the user's emotional state based on data acquired from the camera module and voice input device. Based on the analysis results, the server recommends environments that are relaxing or suitable for socializing. For example, if the user needs to relax, the in-car music can be softened, or a scenic route can be chosen.

[0629] This system is implemented using programming languages ​​such as Python and JavaScript, and the devices it can use include iOS and Android smartphones, as well as in-vehicle computer systems. The server stores and analyzes all of this data to improve the accuracy of future suggestions.

[0630] For example, if a busy business person is riding the train between meetings, the emotional engine can detect stress and play relaxing classical music while taking them along a scenic route through nature.

[0631] Example of a prompt:

[0632] "Please explain a system in which autonomous vehicles suggest the optimal route and in-car environment based on the passenger's emotional state and schedule. Please also explain in detail, with specific examples, how the passenger's emotional data is analyzed and what suggestions are made."

[0633] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0634] Step 1:

[0635] The server retrieves user schedule information from the schedule management system via API. Based on this input data, it analyzes the next scheduled appointment time and current free time, and generates the user's schedule as output. This process establishes a foundation for efficient time management.

[0636] Step 2:

[0637] The terminal acquires real-time location information via the user's smartphone or in-vehicle device. The input is location data, which is sent to the server. Based on this, the system calculates the mode of transport and travel time, and uses this information to suggest the optimal route.

[0638] Step 3:

[0639] The server uses a map service API to calculate the optimal travel route to the next destination. It requires location and mode of transport information as input, and outputs the optimal route and its estimated travel time. By taking past travel history into consideration, it provides the most efficient route for the user.

[0640] Step 4:

[0641] The emotion engine collects and analyzes user emotion data from camera modules and voice input devices. The input data includes facial expression data and voice tone, and based on this, it provides an output representing the user's current emotional state. This analysis allows for adjustments to the in-car environment in the next step.

[0642] Step 5:

[0643] The server integrates emotional information with previously collected data to recommend the optimal workspace based on the user's emotions and schedule. Inputs include schedule information, location information, and emotional information, and the output suggests the best route and in-car environment. Specifically, this includes selecting music and adjusting the air conditioning.

[0644] Step 6:

[0645] The user reviews the suggested route and settings and makes adjustments if necessary. This step involves final adjustments based on the user's preferences, using the server output as a basis. This ensures user comfort and productive time management.

[0646] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0647] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0648] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0649] [Fourth Embodiment]

[0650] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0651] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0652] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0653] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0654] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0655] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0656] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0657] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0658] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0659] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0660] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0661] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0662] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0663] To implement the present invention, it is necessary to build a system that integrates the user's schedule information, location information, means of transportation information, and the availability of available facilities to recommend the optimal work location. The following describes a specific embodiment of the system of the present invention.

[0664] First, the server retrieves the user's schedule information. It obtains data via API from the user's schedule management system or calendar and analyzes the start and end times, location, and other details of the next appointment. This allows the server to determine the user's travel time for the day.

[0665] Next, the device obtains the user's current location. Using location information systems such as smartphones and tablets, it collects GPS data and transmits it to the server. This location information is a crucial element in planning the user's travel.

[0666] The server calculates the optimal mode of transportation based on the user's current location and next destination. Utilizing a mapping system, it evaluates multiple travel options, including walking, driving, and public transport, and calculates the corresponding travel time. By also considering past travel history and user preferences, it provides an optimized travel plan.

[0667] Furthermore, the server retrieves the availability status of nearby satellite offices and other available facilities from a database. It processes data including the location, accessibility, and equipment provided by each facility, and updates their availability in real time.

[0668] By comprehensively analyzing this information, the server recommends the optimal workspace for the user. Candidate workspaces are prioritized based on factors such as travel efficiency, past usage history, and scheduling constraints.

[0669] Users can view recommended workspaces on their devices and make reservations if they like them. Reservations are reflected in the facility's reservation system in real time via the server, allowing users to secure workspaces smoothly.

[0670] Furthermore, users' past usage history is recorded in a database and analyzed by machine learning algorithms. This makes it possible to further personalize future recommendations and continue to provide users with the best possible choices.

[0671] The following describes the processing flow.

[0672] Step 1:

[0673] The server uses an API to retrieve schedule information from the user's schedule management system. This information includes the start time, end time, and location of each appointment. The server analyzes this data to calculate the user's free time.

[0674] Step 2:

[0675] The device uses its built-in GPS function to determine the user's current location. This location information is transmitted to the server in real time and used to plan the user's movements.

[0676] Step 3:

[0677] The server uses the current location and information about the next planned destination to calculate the mode of transportation. The server utilizes a map service API to evaluate various transportation options such as walking, driving, and public transport, and calculates the corresponding travel time.

[0678] Step 4:

[0679] The server accesses a database of available satellite offices to retrieve information on availability, location, and facilities. The server then organizes the retrieved data and evaluates the accessibility and usability of each facility.

[0680] Step 5:

[0681] The server integrates all of the above information and recommends the best workspace for the user. The recommendation takes into account schedule, current location, mode of transportation, and facility availability. It analyzes and prioritizes the best options.

[0682] Step 6:

[0683] Users can view a list of recommended workspaces from the server on their device. They can then select their preferred option and reserve a workspace.

[0684] Step 7:

[0685] The server receives the user's reservation request and transmits it in real time to the facility's reservation system to complete the reservation of the selected workspace. The reservation status is then fed back to the terminal.

[0686] Step 8:

[0687] The server stores users' past usage history in a database and analyzes the data using machine learning algorithms. The analysis results are used to improve the accuracy of future recommendations.

[0688] (Example 1)

[0689] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0690] Conventional workspace provision systems were unable to efficiently recommend the optimal workspace by comprehensively considering the user's schedule, current location and means of transportation, as well as information on available facilities. As a result, users struggled to optimize travel time and smoothly book facilities, requiring efficient time management.

[0691] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0692] In this invention, the server includes means for acquiring user schedule information through a communication system, means for collecting the user's current location information using a mobile information terminal, and means for calculating means of transportation and travel time using a geographic information system. This enables the user to travel efficiently and quickly reserve available facilities.

[0693] "Means of obtaining user schedule information through a communication system" refers to technologies that access and obtain schedule information from a user's schedule management system or calendar via a network.

[0694] "Means of collecting user's current location information using mobile information terminals" refers to technologies that use mobile devices such as smartphones and tablets to collect information about the user's current location using GPS functionality.

[0695] "Methods for calculating travel methods and travel time using geographic information systems" refers to technologies that utilize geographic information to calculate routes based on multiple travel methods such as walking, driving, and public transport, and to determine the time required.

[0696] "Means for searching for the availability and location characteristics of available facilities from a database" refers to technologies that search for and obtain information about the availability of facilities and the characteristics of their locations from a database, which is the source of aggregated information.

[0697] "A means of recommending the optimal work location by analyzing schedule information, location information, transportation information, and facility information" refers to a technology that comprehensively analyzes various data to select and present the most efficient work location for the user.

[0698] "Methods for analyzing past usage records and reflecting them in future recommendations" refers to technologies that analyze user history data and use that data to make future location recommendations more personalized.

[0699] "A means of notifying users of their choice of workspace based on recommended results" refers to a technology that notifies users of suggested locations based on the analysis results and encourages them to make a selection.

[0700] This invention is a system that recommends the optimal workspace for the user. To implement this system, various hardware and software are used to collect, analyze, and utilize data.

[0701] First, the server retrieves the user's schedule information. To do this, it uses a technique that leverages the API of the scheduling management system and extracts schedule information through OAuth authentication. This allows the server to obtain detailed data about the user's next appointment, such as the start time, end time, and location.

[0702] Next, the device uses GPS to collect the user's current location. It utilizes the location services of smartphones and tablets to accurately collect latitude and longitude data and transmit it to a server. This establishes a foundation for geographically relevant information.

[0703] The server uses a Geographic Information System (GIS) to calculate the mode of transport and the estimated travel time. Specifically, it utilizes a common map API to calculate the optimal route for walking, driving, and public transport, selecting the mode of transport that best matches the user's history and preferences. This functionality helps to streamline travel and minimize travel time.

[0704] Facility availability information is retrieved by the server through database queries. By extracting detailed information such as the availability of usable locations, facilities provided, and location conditions for satellite offices, cafes, etc., a database is built to provide an effective work environment.

[0705] Based on this data, the server recommends the optimal workspace. A specific algorithm analyzes the acquired data to select an efficient location that meets user needs, and then notifies the user of this information.

[0706] Furthermore, based on past usage history, machine learning algorithms make subsequent recommendations more personalized. This process continuously improves the user experience.

[0707] For example, a user might want to find a workspace available in a city after finishing work. This system can recommend a nearby cafe with available seats, taking into account the user's schedule for the day and current location, as well as traffic conditions. If the user accepts the suggestion, they can make a reservation immediately from their terminal.

[0708] Examples of prompt messages include: "When a user has two hours of free time around Tokyo Station, please recommend the most efficient workspace. Please consider available facilities such as cafes and satellite offices, and make recommendations based on transportation options and past usage history."

[0709] Thus, the present invention flexibly connects diverse data sources, enabling the selection of a work location optimized for the user.

[0710] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0711] Step 1:

[0712] The server retrieves user schedule information via the communication network. Specifically, it integrates with the user's schedule management system via API and retrieves the day's schedule data through OAuth authentication. Inputs include the user ID and authentication information, and the output is a list of appointments for the day. The schedule information includes the start time, end time, and location, and the server uses this information to calculate the time slot for the next appointment.

[0713] Step 2:

[0714] The device collects the user's current location information. It uses the GPS function built into smartphones and tablets to obtain latitude and longitude in real time. In this process, the device uses location services and collects GPS data as input. The output is coordinate information about the user's current location, which is sent to the server to determine the user's geographical location.

[0715] Step 3:

[0716] The server calculates the optimal mode of transportation based on the user's current location and next destination. Using a Geographic Information System (GIS), it incorporates current location and destination information as input and performs route searches considering walking, driving, and public transport. The output is the estimated travel time for each route. Furthermore, it takes into account past travel history and user preferences to present an optimized travel plan.

[0717] Step 4:

[0718] The server retrieves the availability of available facilities from a database. The input information includes a list of facilities near the user's current location, and the server executes database queries to check real-time availability and facilities. This results in output facility data including location and equipment information.

[0719] Step 5:

[0720] The server comprehensively analyzes this information to recommend the optimal work location. It uses schedule information, location information, transportation information, and facility information as input and analyzes them using an algorithm. As output, a prioritized list of work locations best suited to the user's conditions is created.

[0721] Step 6:

[0722] The user checks information about recommended workspaces on their terminal and selects a preferred location. Based on the user's selection, they can proceed with the reservation. The reservation request becomes input, the server sends this information to the facility's reservation system, and receives confirmation of the reservation completion as output.

[0723] Step 7:

[0724] The server records users' past usage history and analyzes it to improve future recommendations. The input is usage history data, which is processed using machine learning algorithms. The output is insights to improve the accuracy of personalized recommendations. Through this process, it is possible to continuously provide users with the most suitable services.

[0725] (Application Example 1)

[0726] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0727] Modern users want to efficiently manage their daily plans and quickly secure the optimal workspace. However, conventional systems require the individual manipulation of planning and location information, and the lack of integration of transportation options and facility availability leads to wasted time and effort. Furthermore, integration with autonomous driving systems is insufficient, limiting the means of selecting the optimal route for travel. Therefore, there is a need for a system that effectively aggregates all this information and instantly presents the most efficient options to users.

[0728] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0729] In this invention, the server includes means for acquiring computerized planning information, means for acquiring positioning information, and means for calculating the method and time of travel. This allows users to plan an optimal travel plan based on their schedule and location information, and to efficiently travel and secure workspace through an automated driving system. Furthermore, personalized recommendations that take into account past usage history and real-time facility availability information allow users to respond immediately to changes in their plans, which is expected to significantly improve convenience.

[0730] "Computerized planning information" refers to data in which users' schedules and plans are electronically recorded and managed.

[0731] "Positioning information" refers to data that represents the user's current geographical coordinates, obtained through GPS or other location measurement technologies.

[0732] "Method of transportation" refers to information about the mode of transport the user will use to reach their next destination, such as walking, driving, or using public transport.

[0733] "Travel time" refers to the estimated time required for a user to travel from their current location to their destination using the planned mode of transport.

[0734] "Availability information for available facilities" refers to data that indicates the availability of a facility based on its location and the space it provides.

[0735] "Location information" refers to information about the specific geographical location where the facility is located.

[0736] An "autonomous driving system" is a technology and system that enables a vehicle to autonomously perform driving operations using sensors and software.

[0737] "Recommending the optimal workspace" is a selection method that presents the workspace that best suits the user's requirements.

[0738] "Past usage history" refers to recorded data about the work locations and conditions used by the user in the past.

[0739] To implement this invention, a server, a terminal, and an autonomous driving system must work together. The server first obtains the user's computerized planning information. This process involves collecting data from the user's calendar and schedule management system using an API. The server then collects positioning information. Using GPS and other positioning technologies installed in the terminal, it determines the user's current location and transmits this information to the server. The server also calculates the optimal method and time of travel through computational processing. This is done by utilizing geographic information systems to evaluate which mode of transport is most efficient.

[0740] Next, the server searches for and retrieves information on the availability and location of available facilities from its database. This process allows the server to continuously update facility availability in real time. Furthermore, the server integrates this information and utilizes a generative AI model to recommend the most suitable workspace to the user. In this process, a proprietary algorithm is applied to improve the accuracy of the recommendations based on past usage history. The recommendation of the best workspace used is designed to allow users to easily reserve a location.

[0741] For example, if a user is currently in Shibuya and their next destination is Tokyo Station, the server will calculate the shortest and most efficient route based on the user's schedule. Furthermore, by using an automated driving system, it becomes possible to instantly arrange for available space near the destination.

[0742] An example of a prompt to input into the generative AI model is: "If the user's current location is 'Shibuya' and their next destination is 'Tokyo Station,' please recommend the optimal route for optimally navigating the autonomous vehicle, as well as available workspaces near Tokyo Station." This prompt is intended to encourage highly accurate optimization by the generative AI model.

[0743] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0744] Step 1:

[0745] The server uses an API to retrieve the user's computerized planning information. The input requires authentication credentials from the user's scheduling management system, and the output provides specific planning data such as the next destination, start time, and end time. This information serves as foundational data for optimizing the user's daily travel plans.

[0746] Step 2:

[0747] The device uses location measurement technologies such as GPS to obtain the user's current location. The input is positioning information obtainable by the device, and the output is geographic coordinates (latitude and longitude). This data is sent to the server and used to select the optimal mode of transportation to the next destination.

[0748] Step 3:

[0749] The server uses a geographic information system to calculate the optimal mode of travel and travel time from the current location to the next destination. It takes the user's current geographic coordinates and information about the next destination as input, and provides recommended modes of travel (e.g., walking, car, public transport) and their estimated travel times as output. This information is key to achieving efficient travel.

[0750] Step 4:

[0751] The server searches the database for available facility availability and location information. The input requires facility type and location criteria, and the output is a list of candidate facilities and their availability. This process provides data to recommend the most suitable workspace to the user.

[0752] Step 5:

[0753] The server integrates the information it has gathered so far and uses a generative AI model to recommend the most suitable workspace for the user. Inputs include schedule data, current location, mode of transportation, and facility information, and the output is a suggestion of the workspace deemed most appropriate. Based on this suggestion, the server provides the user with the opportunity to make a reservation.

[0754] Step 6:

[0755] Users can review recommended workspaces and make reservations immediately if necessary. Selection and confirmation are based on the user's discretion, and the reserved information is sent to the server. This information is used as feedback to improve future recommendations.

[0756] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0757] To implement the present invention, it is necessary to construct a system that integrates the user's schedule information, location information, means of transportation information, and the availability of available facilities, as well as an emotion engine that recognizes the user's emotions. The following describes a specific embodiment of the system of the present invention.

[0758] The server retrieves user schedule information from the schedule management system using an API. Next, it analyzes the user's upcoming appointments and current free time based on this schedule information. This streamlines the management of user travel and work time.

[0759] The terminal acquires location information via the user's smartphone or wearable device. This location data is transmitted to a server in real time and used to select transportation options and facilities.

[0760] Furthermore, the server uses a map service API to calculate the optimal mode of transportation from the current location to the next destination. In doing so, it takes into account travel time, traffic conditions, and past travel history to provide a highly accurate travel plan.

[0761] Next, the server accesses the database to retrieve information on the availability, location, and equipment of available facilities. This information is updated in real time and used to select a suitable workspace for the user.

[0762] A key feature of this invention is the inclusion of an emotion engine that analyzes the user's emotional state. The terminal uses voice input and a camera module to collect the user's voice tone and facial expression data, and transmits it to the emotion engine. Based on the data obtained from the emotion engine, the server analyzes the user's emotional state and adjusts the environment of the suggested workspace accordingly. For example, it recommends a quiet, relaxing environment for a user who is feeling stressed, and a facility with a social space for someone who is in a sociable mood.

[0763] This allows users to utilize workspaces optimized for their emotional state and schedule, maximizing comfort and productivity. The system notifies users of detailed information about recommended locations and allows for easy booking. Booking information is processed on the server and reflected in the booking system of the selected facility.

[0764] Furthermore, the server stores all of this usage data in a database and analyzes and uses it as data to help with future recommendations. In this way, the present invention provides a comprehensive workspace recommendation system that takes into account a variety of factors such as the user's schedule, location, and emotions.

[0765] The following describes the processing flow.

[0766] Step 1:

[0767] The server retrieves appointment information from the user's scheduling application via an API. Here, it analyzes the start time, end time, location, and content of each appointment registered by the user to determine the next location and time to travel.

[0768] Step 2:

[0769] The device uses its built-in GPS function to determine the user's current location in real time. This location information is transmitted to a server and used as input data for planning transportation.

[0770] Step 3:

[0771] The server uses a map service API to calculate the optimal mode of transportation and estimated travel time from the current location to the next destination. It presents multiple transportation options (walking, car, public transport, etc.) and provides details for each (time, distance, cost).

[0772] Step 4:

[0773] The server accesses a database of satellite offices and coworking spaces to retrieve information on availability, location, and amenities (Wi-Fi, power outlets, noise levels, etc.). This information is updated in real time and organized as available options for the user.

[0774] Step 5:

[0775] The device collects the user's voice and facial expressions using input devices (microphone, camera) and sends them to the emotion engine. The emotion engine uses a machine learning model to analyze the data and determine the user's emotional state.

[0776] Step 6:

[0777] The server integrates emotional data obtained from the emotion engine and evaluates it along with the user's schedule, current location, means of transportation, and facility information. This allows it to recommend the optimal workspace based on the user's emotional state. For example, if a relaxed environment is deemed suitable, it will suggest a quiet workspace; if an active social environment is preferred, it will suggest a facility with a social space.

[0778] Step 7:

[0779] Users can review recommended workspaces from the server on their terminal and make a reservation on the spot if they like it. The reservation process is simple and straightforward through the user interface, and the selected location is secured immediately.

[0780] Step 8:

[0781] The server processes the user's reservation information and synchronizes it with the reservation system of the selected facility to complete the reservation process. This allows the user to secure a competitive workspace.

[0782] Step 9:

[0783] The server stores users' past usage data in a database and performs periodic analysis. This analysis improves the accuracy of future location recommendations, enabling a more personalized experience.

[0784] (Example 2)

[0785] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0786] In modern society, users face numerous appointments and diverse modes of transportation on a daily basis, requiring efficient time management and the selection of appropriate work environments. However, conventional systems have struggled to integrate information such as appointments, location, and emotions to recommend the optimal work environment. In particular, they lacked the ability to adjust the environment according to emotional states, making it impossible to instantly provide the relaxing or social environment that users need.

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

[0788] In this invention, the server includes means for acquiring user schedule information, means for collecting user location information, means for calculating means of transportation and travel time, and recommending the optimal work location based on the availability and location conditions of available facilities, means for analyzing the user's emotional state and proposing the optimal work environment based on that emotional state, and means for analyzing past usage history and reflecting it in the next recommendation. As a result, the user can efficiently utilize the optimal work environment based on a multifaceted set of factors including schedule, location, and emotional state.

[0789] "User schedule information" refers to detailed data about a user's schedule that can be obtained from the schedule management system.

[0790] "User location information" refers to data indicating the user's current geographical location, and is obtained from smartphones and wearable devices.

[0791] "Means of transportation" refers to the means of transport available to a user when moving from one point to another.

[0792] "Travel time" refers to the time required for a user to travel from their current location to their destination.

[0793] "Facility availability" refers to information indicating the available space and reservation status of facilities.

[0794] "Location conditions" refers to information regarding the geographical location of the facility and its surrounding environment.

[0795] "Recommending a workspace" refers to the process of identifying and presenting the workspace that best suits the user's needs.

[0796] "User emotional state" refers to the user's current psychological or emotional situation, as analyzed from their voice and facial expressions.

[0797] An "optimal work environment" refers to an environment that has been adjusted to maximize the user's work efficiency and comfort.

[0798] "Past usage history" refers to records of facilities and services that a user has used in the past, providing data that can be used as a reference for future use.

[0799] The system for implementing this invention improves comfort and productivity by using advanced information technology to centrally manage the user's schedule information, location information, and emotional state, and recommending the optimal work environment.

[0800] First, the server collects data from the scheduling management system using APIs to obtain user schedule information. Specifically, by using the API of the scheduling software, it can obtain schedule information such as the date, time, location, and participants of the user. For example, it can use the "Calendar API" or the "Scheduler API".

[0801] Next, the device acquires the user's location information in real time. Using the GPS function of smartphones and wearable devices, it determines the user's current location and sends that data to the server. Location information is important as a criterion for selecting transportation methods and searching for facilities.

[0802] Furthermore, the server uses an emotion analysis engine to analyze the user's emotional state. The terminal collects the user's voice tone and facial expression data using voice input and the camera. This data is sent to an AI algorithm for emotion analysis, which determines the user's stress level, relaxation level, etc. Based on this emotional state, the system suggests the optimal work environment for the user by recommending quiet or sociable environments.

[0803] The server uses a map service API to calculate the optimal mode of transportation from the current location to the next destination. For example, by using the "Map API," it compares multiple modes of transport and provides the optimal route considering travel time and traffic conditions.

[0804] Through database access, the server retrieves information on the availability, location, and facilities of available facilities. This allows the server to recommend the most suitable workspace for the user. Detailed information about the recommended facilities is then communicated to the user, enabling easy booking. Booking information is processed on the server and reflected in the booking system.

[0805] For example, if a user has a meeting scheduled for 3 PM, the server will consider traffic conditions, suggest a suitable cafe, and help the user make a reservation immediately. If the system determines that the user's emotional state requires relaxation, it can also prioritize recommending a quiet cafe.

[0806] An example of a prompt to input into a generative AI model might be something like, "Please suggest a suitable workspace based on my schedule, location, and emotional state."

[0807] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0808] Step 1:

[0809] The server retrieves user schedule information from the schedule management system using an API. Specifically, the server uses the "Calendar API" to extract the user's next appointments and free time. The input is the user's authentication information, and the output is the next appointments and free time. Based on this data, initial data is generated to select the optimal work location according to the user's schedule.

[0810] Step 2:

[0811] The terminal utilizes the GPS function of smartphones and wearable devices to obtain the user's current location in real time. Specifically, it uses a location information service API to obtain latitude and longitude information from the terminal's GPS module. The input is the device's location sensor information, and the output is latitude and longitude location information. This location information is sent to a server and used as a criterion for selecting means of transportation and facilities.

[0812] Step 3:

[0813] The server uses a map service API to calculate the optimal mode of transportation from the user's current location to their next destination. The specific operation involves calling the "Map API" to calculate traffic conditions and travel time. The inputs are the location information obtained in step 2 and the location information of the next destination from step 1, and the output is the optimal travel route and travel time. This makes travel more efficient.

[0814] Step 4:

[0815] The server retrieves the availability and location information of available facilities from the database. Its specific operations include collecting facility information in real time using SQL queries and analyzing that data. The input is the facility database, and the output is a list of available facilities suitable for the user. This information serves as a candidate for suggested workspaces.

[0816] Step 5:

[0817] The device collects the user's voice tone and facial expression data through its camera and microphone, and sends it to an emotion analysis engine to determine their emotional state. Specifically, it analyzes the voice and image data using an AI algorithm. The input is the raw voice and facial expression data, and the output is the emotion analysis result. Based on this result, a recommended working environment is adjusted.

[0818] Step 6:

[0819] The server integrates the aforementioned information and recommends a work environment optimized for the user. Specifically, it uses an algorithm to generate optimal suggestions based on schedule information, location information, and sentiment analysis data. The input is all the data obtained in the previous steps, and the output is the recommended work location. This information is notified to the user, who can then book a facility based on the suggestion.

[0820] Step 7:

[0821] The user reserves a suggested workspace, and this is reflected in the facility's reservation system. The specific process involves completing the reservation operation through the application. The input is the user's reservation information, and the output is the information reflected in the facility's reservation system. This ensures that the necessary workspace is efficiently secured.

[0822] (Application Example 2)

[0823] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0824] In modern society, users face numerous scheduling and travel options, and their emotional states also change daily. This presents a challenge in selecting the optimal workspace that takes all of these factors into account. Therefore, there is a need for workspace recommendations that adapt to the user's emotional state and schedule.

[0825] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0826] In this invention, the server includes means for acquiring user schedule information, means for collecting user location information, and means for analyzing user emotional information. This makes it possible to recommend an optimal workspace according to the user's schedule and emotional state.

[0827] "User schedule information" refers to information about activities and events that the user has planned for the future.

[0828] "User location information" refers to information that indicates the user's current geographical location.

[0829] "Transportation" refers to information about the means of transportation used by the user.

[0830] "Travel time" refers to the time required to reach a destination using a means of transportation.

[0831] "Availability of available facilities" refers to information regarding whether a particular facility is available or not.

[0832] "Location conditions" refers to information about the geographical location of the facility.

[0833] "Emotional information" refers to information that indicates the emotional state a user is currently experiencing.

[0834] An "optimal workspace" is an environment suitable for the task, selected considering the user's schedule, location, means of transportation, facility availability, and emotional information.

[0835] "Past usage history" refers to information about the workspaces and related activity history that the user has used in the past.

[0836] This invention realizes a system that integrates a user's schedule information, location information, mode of transportation, facility availability, and emotional information within an autonomous vehicle to recommend the optimal workspace. The server retrieves the user's schedule information from the schedule management system via API and calculates the predicted travel time and mode of transportation. This enables the system to provide the user with efficient routes and schedules.

[0837] The system, installed in the autonomous vehicle as a terminal, collects real-time location information via the user's smartphone or in-vehicle devices. Based on this data, the server uses a map service API to devise the optimal route to the next destination and can suggest music and in-car environments tailored to the user's emotional state.

[0838] The emotion engine analyzes the user's emotional state based on data acquired from the camera module and voice input device. Based on the analysis results, the server recommends environments that are relaxing or suitable for socializing. For example, if the user needs to relax, the in-car music can be softened, or a scenic route can be chosen.

[0839] This system is implemented using programming languages ​​such as Python and JavaScript, and the devices it can use include iOS and Android smartphones, as well as in-vehicle computer systems. The server stores and analyzes all of this data to improve the accuracy of future suggestions.

[0840] For example, if a busy business person is riding the train between meetings, the emotional engine can detect stress and play relaxing classical music while taking them along a scenic route through nature.

[0841] Example of a prompt:

[0842] "Please explain a system in which autonomous vehicles suggest the optimal route and in-car environment based on the passenger's emotional state and schedule. Please also explain in detail, with specific examples, how the passenger's emotional data is analyzed and what suggestions are made."

[0843] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0844] Step 1:

[0845] The server retrieves user schedule information from the schedule management system via API. Based on this input data, it analyzes the next scheduled appointment time and current free time, and generates the user's schedule as output. This process establishes a foundation for efficient time management.

[0846] Step 2:

[0847] The terminal acquires real-time location information via the user's smartphone or in-vehicle device. The input is location data, which is sent to the server. Based on this, the system calculates the mode of transport and travel time, and uses this information to suggest the optimal route.

[0848] Step 3:

[0849] The server uses a map service API to calculate the optimal travel route to the next destination. It requires location and mode of transport information as input, and outputs the optimal route and its estimated travel time. By taking past travel history into consideration, it provides the most efficient route for the user.

[0850] Step 4:

[0851] The emotion engine collects and analyzes user emotion data from camera modules and voice input devices. The input data includes facial expression data and voice tone, and based on this, it provides an output representing the user's current emotional state. This analysis allows for adjustments to the in-car environment in the next step.

[0852] Step 5:

[0853] The server integrates emotional information with previously collected data to recommend the optimal workspace based on the user's emotions and schedule. Inputs include schedule information, location information, and emotional information, and the output suggests the best route and in-car environment. Specifically, this includes selecting music and adjusting the air conditioning.

[0854] Step 6:

[0855] The user reviews the suggested route and settings and makes adjustments if necessary. This step involves final adjustments based on the user's preferences, using the server output as a basis. This ensures user comfort and productive time management.

[0856] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0857] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0858] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0859] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0860] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0861] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0862] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0863] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0864] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0865] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0866] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0867] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0868] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0869] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0870] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0871] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0872] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0873] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0874] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0875] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0876] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0877] The following is further disclosed regarding the embodiments described above.

[0878] (Claim 1)

[0879] A means of obtaining the user's schedule information,

[0880] Means for collecting user location information,

[0881] Means of transportation and means for calculating travel time,

[0882] A means of searching for the availability and location conditions of available facilities,

[0883] A means for recommending the optimal work location based on the aforementioned schedule information, location information, means of transportation information, and facility information,

[0884] We need a way to analyze past usage data and incorporate it into future recommendations.

[0885] Includes system.

[0886] (Claim 2)

[0887] The system according to claim 1, which allows a user to make a reservation based on the recommendation of the most suitable work location.

[0888] (Claim 3)

[0889] The system according to claim 1, which notifies the user of information about a recommended work location.

[0890] "Example 1"

[0891] (Claim 1)

[0892] A means of obtaining user schedule information through a communication system,

[0893] A means of collecting the user's current location information using a mobile device,

[0894] A means of calculating the means of travel and the time required for travel using a geographic information system,

[0895] A means for searching for the availability and location characteristics of available facilities from a database,

[0896] A means of recommending the optimal work location by analyzing schedule information, location information, means of transportation information, and facility information,

[0897] A means to analyze past usage records and reflect them in future recommendations,

[0898] A means of notifying users of their work location selection based on the recommended results,

[0899] Includes system.

[0900] (Claim 2)

[0901] The system according to claim 1, which allows a user to make a reservation based on information about a recommended work location.

[0902] (Claim 3)

[0903] The system according to claim 1, which transmits reservation information to the facility's reservation system in real time.

[0904] "Application Example 1"

[0905] (Claim 1)

[0906] The computerized planning information means to be acquired,

[0907] Means for acquiring the positioning information to be collected,

[0908] A means for calculating the method of movement to be performed and the time of movement,

[0909] A means of obtaining information on the availability and location of searchable facilities,

[0910] A means for recommending the optimal workspace based on the generated planning information, positioning information, movement method information, and facility information,

[0911] A means to reflect the analysis of past usage history in future recommendations,

[0912] A means for integrating an autonomous driving system that can suggest the optimal route,

[0913] A system that includes this.

[0914] (Claim 2)

[0915] The system according to claim 1, which allows a user to reserve a workspace based on the recommendation of the optimal workspace.

[0916] (Claim 3)

[0917] The system according to claim 1, which transmits information about recommended workspaces to the user.

[0918] "Example 2 of combining an emotion engine"

[0919] (Claim 1)

[0920] A means of obtaining the user's schedule information,

[0921] Means for collecting user location information,

[0922] Means of transportation and means for calculating travel time,

[0923] A means of searching for the availability and location conditions of available facilities,

[0924] A means to analyze the user's emotional state and propose the optimal work environment based on that emotional state,

[0925] A means for recommending the optimal work location based on the aforementioned schedule information, location information, means of transportation information, facility information, and emotional information,

[0926] We need a way to analyze past usage data and incorporate it into future recommendations.

[0927] Includes system.

[0928] (Claim 2)

[0929] The system according to claim 1, which allows a user to make a reservation based on the recommendation of the most suitable work location.

[0930] (Claim 3)

[0931] The system according to claim 1, which notifies the user of information about a recommended work location.

[0932] "Application example 2 when combining with an emotional engine"

[0933] (Claim 1)

[0934] A means of obtaining the user's schedule information,

[0935] Means for collecting user location information,

[0936] Means of transportation and means for calculating travel time,

[0937] A means of searching for the availability and location conditions of available facilities,

[0938] A means of analyzing user sentiment information,

[0939] A means for recommending the optimal workspace based on the aforementioned schedule information, location information, means of transportation information, facility information, and emotional information,

[0940] We need a way to analyze past usage data and incorporate it into future recommendations.

[0941] Includes system.

[0942] (Claim 2)

[0943] The system according to claim 1, which allows a user to make a reservation based on the recommendation of the optimal workspace.

[0944] (Claim 3)

[0945] The system according to claim 1, which notifies the user of information about the recommended workspace. [Explanation of Symbols]

[0946] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of obtaining the user's schedule information, Means for collecting user location information, Means of transportation and means for calculating travel time, A means of searching for the availability and location conditions of available facilities, A means for recommending the optimal work location based on the aforementioned schedule information, location information, means of transportation information, and facility information, We need a way to analyze past usage data and incorporate it into future recommendations. Includes system.

2. The system according to claim 1, which allows a user to make a reservation based on the recommendation of the most suitable work location.

3. The system according to claim 1, which notifies the user of information about a recommended work location.

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