system

Abstract

We provide the system. [Solution] A means of receiving input information from the user, A means for collecting data from multiple external databases and information sources based on the aforementioned input information, A means for analyzing the collected data and generating an activity plan that is optimal for the user's conditions, Means for providing the generated plan to the user, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a 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 chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] How to effectively utilize unexpected free time caused by sudden weather changes or schedule changes is a problem for many people. In the conventional method, it is difficult to obtain an optimal activity plan based on various real - time updated information, so it has been difficult for users to spend their precious free time meaningfully. Also, since the availability and congestion status of facilities are not up - to - date, there is a possibility of causing disappointment on - site. The purpose of this invention is to solve these problems and provide a means for users to select appropriate activities on - site.

Means for Solving the Problems

[0005] This invention includes means for receiving user input information and means for collecting data from multiple external databases and information sources based on this information. This makes it possible to obtain weather, congestion status, social network information, etc., in real time. It also provides means for analyzing the collected data and generating an activity plan that is optimal for the user's conditions. Furthermore, by providing this generated plan to the user, the user can quickly make the best choice. By receiving real-time information from the facility and using that information to generate the plan, it is possible to make even more accurate suggestions. As a result, users can use their free time meaningfully with peace of mind.

[0006] A "user" refers to an individual or group of people who use this system to obtain the information or services they desire.

[0007] "Input information" refers to data that users provide to this system, including their current situation and desired conditions.

[0008] An "external database" refers to third-party information resources, including weather, congestion information, and social network information, that are referenced based on user input.

[0009] "Information sources" refer to digital or online resources that this system can access to obtain the information it needs.

[0010] "Means of collecting data" refers to functions that retrieve necessary information from external databases and information sources based on user input.

[0011] An "activity plan" is a set of specific action suggestions for users to make the most of their free time, based on the information analyzed by this system.

[0012] "Real-time information" refers to dynamic data that reflects the latest situation at the present time.

[0013] A "facility" is a commercial or public place that users can visit or use.

[0014] "Means used for plan generation" refers to the process or function for creating the optimal activity plan for the user based on the collected information. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0018] 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 a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0019] In the following embodiments, 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.

[0020] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

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

[0025] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0032] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0035] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0036] This invention provides a system that generates and provides an optimal activity plan in real time based on information entered by the user. This system is implemented by utilizing the input information provided through the user's terminal and the powerful computing capabilities of the server.

[0037] The user uses a device to input conditions such as their current location, time, preferences, and budget. For example, the user might input, "I want to go to a cafe with someone near Tokyo Station at 3 PM." Once this information is entered, the device sends the data to the server. The server accesses multiple external databases and information sources to collect relevant information based on the user's input.

[0038] The server collects relevant data from the database, such as weather information, congestion levels, and social media trends. Based on this collected data, AI analyzes it and generates an activity plan that is optimal for the user's conditions. This plan generation also includes information sent from facilities in real time (such as availability and discount information).

[0039] The generated activity plan is sent to the user's device and presented in an easy-to-understand format. For example, the user might be given specific information such as, "Cafe A near Tokyo Station is currently open, you can enter from 3 PM, and there's a discount on cake sets from 2 PM." The user can then choose to keep the presented plan or request other options.

[0040] The implementation of this system provides users with a simple and rapid means to make meaningful use of unexpected free time, and also brings the benefit of optimizing customer acquisition for facilities. The embodiment of the present invention is a specific example of a system that combines efficient information provision and processing capabilities utilizing information technology.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The user uses their device to enter conditions such as their current location, desired visit time, number of people, genre, and budget. For example, they might enter information such as, "I want to go to a cafe with two people near Tokyo Station at 3 PM."

[0044] Step 2:

[0045] The terminal sends the entered user information to the server. This transmission includes location and time information.

[0046] Step 3:

[0047] The server receives user information and accesses multiple external databases and APIs (such as weather data, social media trends, and facility congestion information) to collect necessary related information.

[0048] Step 4:

[0049] The AI ​​on the server analyzes the collected data and generates multiple activity plans tailored to the user's conditions. Real-time information from the facility is also taken into consideration during this process.

[0050] Step 5:

[0051] The server generates an activity plan and sends it to the user's device. This plan includes specific facility names, access methods, current congestion levels, and information on available menus within the budget.

[0052] Step 6:

[0053] Users can review the plans presented on their device and select the one they like best, or request another option if the current one doesn't meet their needs.

[0054] Step 7:

[0055] Depending on the selected plan, users can use that information to make reservations at facilities or use links to map apps to get to the location, if necessary.

[0056] This process allows users to efficiently select plans that allow them to spend their free time productively.

[0057] (Example 1)

[0058] 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."

[0059] The information overload of modern society makes it difficult for users to efficiently and quickly plan activities that meet their needs. Furthermore, facility information is frequently updated, making it difficult for users to access timely and accurate information. This results in users having difficulty finding meaningful experiences, and facilities struggling to attract the optimal number of visitors.

[0060] 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.

[0061] In this invention, the server includes means for the user to input conditions using a processing device, means for collecting information from a plurality of data storage locations and information sources based on the conditions, and means for organizing an activity plan via an artificial intelligence model using the collected information. This makes it possible for the user to receive an activity plan that suits their conditions in real time.

[0062] A "user" refers to an entity that uses a system to plan activities based on its own conditions.

[0063] A "processing device" refers to an electronic device used by users to input information or receive suggestions from a system.

[0064] A "data repository" refers to a storage or database where diverse information is accumulated and which has the function of accessing the data that a system needs.

[0065] "Information sources" refer to external data providers or APIs that the system accesses to obtain the data it needs.

[0066] An "artificial intelligence model" refers to an algorithm or system that analyzes vast amounts of data and generates an optimal activity plan for the user.

[0067] An "activity plan" refers to the output from a system that is compiled to suggest the optimal actions and schedule based on the user's conditions.

[0068] "Environmental condition information" refers to information about external environmental factors that affect activity plans, such as weather and temperature.

[0069] "Congestion information" refers to data about the usage status and level of congestion at specific locations or facilities.

[0070] "Social network information" refers to information about current trends and topics obtained from social media and other sources.

[0071] "Real-time information" refers to information provided by the facility in real time, including facility usage status and discount services.

[0072] This invention is a system that provides activity plans tailored to user needs, efficiently handling everything from user input of conditions to optimal suggestions.

[0073] First, the user uses a device to input their desired conditions. These devices include electronic devices such as smartphones and personal computers, and information is entered through application software or a web browser. For example, suppose a user inputs the condition, "I want to go to a cafe with someone near Tokyo Station at 3 PM." This condition is then sent to the server via the device.

[0074] The server collects relevant information from multiple data collection points and sources based on user conditions. This process involves communication over the internet to retrieve data from external sources such as weather APIs, traffic information databases, and social media trend information. The server also receives real-time information from facilities, such as availability and discount information.

[0075] The collected data is input into a generative AI model on the server. The AI ​​model analyzes this data and generates an optimal activity plan for the user in real time. In this process, a massive dataset is rapidly processed by the AI, and optimal suggestions tailored to the user's conditions are created.

[0076] The generated activity plan is sent from the server to the user's terminal. This allows the user to select an activity that suits their needs. The terminal visually presents the received suggestions to the user in an easy-to-understand manner. For example, it might display specific information such as, "Cafe A near Tokyo Station is currently open, you can enter from 3 PM, and a discount on cake sets is available from 2 PM."

[0077] For example, if a user is traveling with a friend and has some free time before moving on to their next destination, this system can be used to quickly obtain information about nearby tourist spots. An example of a prompt sentence to input into the generating AI model would be, "Please tell me about a cafe near Tokyo Station that is open to two people from 3 PM onwards."

[0078] This system provides users with a means to make meaningful use of their free time, while also promoting real-time optimization of customer acquisition for facilities.

[0079] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0080] Step 1:

[0081] The user uses their device to input their current location and desired activity conditions. Specifically, they operate an application or webpage on their device to enter conditions such as, "I want to go to a cafe with someone near Tokyo Station at 3 PM." This input data is then prepared to be sent directly to the server.

[0082] Step 2:

[0083] The terminal sends the user-entered conditions to the server. A communication protocol (e.g., HTTPS) is used for transmission via the internet. The user conditions are sent as input, and the server receives them as input data.

[0084] Step 3:

[0085] Based on the user's requested conditions, the server sends requests to multiple data collection points and sources to gather the necessary information. This includes accessing external sources such as weather APIs, traffic information, and social media trends. The server collects environmental condition information and congestion information related to the conditions and integrates the information.

[0086] Step 4:

[0087] The server inputs the collected information into the generative AI model. The AI ​​model then integrates and preprocesses the data, using it as raw material to generate an optimal activity plan based on the user's conditions. The generative AI model analyzes the large amount of data and compiles the most appropriate plan from multiple options.

[0088] Step 5:

[0089] The generated activity plan is formatted on the server and converted into a user-friendly format. Specifically, the information presentation format is adjusted to suit the user, using text, images, maps, etc. This output is then ready to be sent to the user's device.

[0090] Step 6:

[0091] The server sends the prepared activity plan to the user's terminal. The terminal receives this data and visualizes it on the user interface. Specifically, information such as "Cafe A near Tokyo Station is currently available, you can enter from 3 PM, and a discount on cake sets is available from 2 PM" is presented to the user.

[0092] Through this process, users can quickly receive proposals best suited to their needs and easily implement meaningful activity plans.

[0093] (Application Example 1)

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

[0095] Modern consumers want to shop and use facilities efficiently within limited time, but they face the challenge of making optimal choices due to the overwhelming amount of information available. Furthermore, users want to receive information tailored to their preferences in real time, and there is a need to provide personalized plans that meet this need.

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

[0097] In this invention, the server includes means for receiving input information from a user, means for collecting data from a plurality of external databases and information sources based on the input information, means for analyzing the collected data and generating an activity plan that is optimal for the user's conditions, and means for collecting information on commercial facilities in real time and generating an optimal shopping plan. This makes it possible for the user to receive an optimal activity plan tailored to their individual conditions in real time.

[0098] "Means of receiving user input information" refers to the function that allows a server to acquire information provided by a user through their device.

[0099] "Means for collecting data from external databases and information sources" refers to the function of obtaining necessary data from various information sources via the internet or other networks.

[0100] "Means for analyzing and generating the optimal activity plan for user conditions" refers to algorithms and programs that process acquired data and create the best plan that matches the conditions provided by the user.

[0101] "Means of providing the generated plan to the user" refers to a function for sending and displaying the generated activity plan to the user's available devices.

[0102] "Means of collecting information on commercial facilities and generating optimal shopping plans" refers to a function that utilizes real-time data from shopping malls and stores to provide users with effective shopping routes and promotional information.

[0103] This invention is a system that generates and provides an optimal activity plan in real time based on information input by the user. This system utilizes the user's device as an interface and leverages the computing power of a server. Specifically, the user inputs conditions such as their current location, time, personal preferences, and budget through a device such as a smartphone or smart glasses. This information is transmitted from the device to the server.

[0104] The server utilizes a cloud service platform, such as Google Cloud Platform or Amazon Web Services, to collect relevant information from various external databases. The collected data includes weather information, congestion levels, and real-time information from commercial facilities. Programming languages ​​such as Python are used for data processing, and data analysis is performed using AI frameworks such as Tensorflow. As a result, an optimal activity plan based on the user's conditions is generated.

[0105] The generated plan is sent to the user's device and displayed on it, enabling user-friendly navigation and information provision.

[0106] For example, when a user is shopping at a commercial facility in Shinjuku and requests, "I want to buy trendy clothes in Shinjuku this afternoon for under 20,000 yen," the AI ​​analyzes the current situation at the facility and provides the optimal store route and discount information.

[0107] An example of a prompt message for a generative AI model would be: "Please create a plan to purchase trendy fashion items within a budget at a shopping mall in Shinjuku. Your current location and budget are specified."

[0108] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0109] Step 1:

[0110] Users use their smartphones or smart glasses to input their requests, such as "I want to buy trendy items in Shinjuku in the afternoon within my budget." This input includes the user's current location, time, preferences, and budget. The entered information is then sent to the server by the device.

[0111] Step 2:

[0112] Based on the received user information, the server accesses external databases and information sources to collect relevant information. At this stage, weather, congestion levels, and real-time information from each commercial facility are obtained. The server then uses data processing languages ​​such as Python to format the data and convert it into an analyzable format.

[0113] Step 3:

[0114] The server uses a generative AI model based on the formatted data to generate an optimal activity plan tailored to the user's conditions. The AI ​​model analyzes the input data to identify the best store routes, recommended items, discount information, and more that match the user's requests. TensorFlow is used for this process.

[0115] Step 4:

[0116] The generated activity plan is sent from the server to the user's device. The device then displays the information based on the received plan in an easy-to-understand format and provides it to the user. For example, it might visually show a map of stores to visit or a list of recommended products.

[0117] Step 5:

[0118] The user can review the presented plan and obtain further details on points of interest. In this process, the device can send additional requests to the server to retrieve more specific information, which can then be presented to the user again.

[0119] 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.

[0120] This invention realizes a system that generates and provides an optimal activity plan by combining user input information and emotional state. By incorporating an emotion engine, it is possible to provide more personalized plan suggestions that take into account the user's emotional elements, rather than just suggestions based on factual data.

[0121] When a user inputs basic information such as location, time, type of activity, and budget through their device, the emotion engine analyzes their current emotions based on their tone of voice and text messages. For example, if a user inputs "tired" or their voice sounds subdued, the emotion engine determines that the user is seeking relaxation.

[0122] The server integrates sentiment data obtained from the user with normal condition data and collects relevant information from multiple external databases and sources. Based on weather information, congestion levels of nearby facilities, social media trends, and real-time information about the facilities, it generates an optimal activity plan that takes the user's emotional state into account.

[0123] For example, if a user's emotional state is determined to be "fatigued," the server might recommend quiet, relaxing places like cafes or spas. On the other hand, if the user is determined to be "active," the server might offer plans for sports facilities or event venues.

[0124] The generated activity plan is sent to the user's device. This includes a list of specific facility suggestions, access information, and recommended activities, all tailored to the user's mood and circumstances. Based on this information, the user can select the plan that best suits their mood and situation.

[0125] As described above, the present invention aims to enrich the user experience by utilizing an emotion engine to propose flexible and individualized activity plans that take into account the user's emotional state.

[0126] The following describes the processing flow.

[0127] Step 1:

[0128] The user uses their device to input the conditions for their desired activity (location, time, number of people, genre, budget). During this process, the emotion engine analyzes the user's emotions from the input voice or text message.

[0129] Step 2:

[0130] The device sends conditional information and emotion data acquired from the user to the server. This transmission also includes the emotional state analyzed by the emotion engine.

[0131] Step 3:

[0132] Based on the information received by the server, relevant information is collected from multiple external databases and APIs (such as weather information, social media trends, and facility congestion status). During this process, the influence of emotional information on the extracted data is also considered.

[0133] Step 4:

[0134] The AI ​​on the server analyzes external data collected from users along with their emotional data to generate activity plans. Taking emotional information into account, it creates suggestions that align with the user's feelings, such as relaxation or exciting activities.

[0135] Step 5:

[0136] The generated plan is then refined by taking real-time information from the facility into consideration. For example, the availability of the target facility and the presence of any special events are taken into account.

[0137] Step 6:

[0138] The server sends the completed activity plan to the user's device. The plan includes emotion-based recommendations for facilities, specific activities, transportation, and an optimal action plan for a particular time period.

[0139] Step 7:

[0140] Users review the customized plans presented on their devices and consider whether to actually select one. If necessary, a function to make facility reservations on the spot is also available.

[0141] This process allows users to quickly and easily select an activity plan that suits their emotional state.

[0142] (Example 2)

[0143] 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".

[0144] Traditional activity plan provision systems use factual data based on user input to make suggestions, but they sometimes fail to adequately provide personalized plans that take into account the user's emotional factors. As a result, they cannot present the optimal options that align with the user's emotions, leading to a decrease in user experience satisfaction.

[0145] 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.

[0146] In this invention, the server includes means for receiving input data from a user, means for analyzing the emotional state of the input data, and means for collecting information from multiple information sources based on the analyzed emotional state and the input data. This makes it possible to integrate the collected information and generate an activity plan optimized for the user's emotional state using a generative AI model.

[0147] "User input data" refers to basic information that users provide to the system, such as location, time, type of activity, budget, as well as tone of voice and text messages that reflect emotions.

[0148] "Analyzing emotional state" refers to the process of analyzing a user's tone of voice and the content of their text messages to identify their emotions or psychological state.

[0149] "Information sources" refer to external databases and information services that provide information such as weather conditions, congestion levels, communication network information, and real-time facility data.

[0150] A "generative AI model" refers to artificial intelligence technology used to create optimal activity plans tailored to a user's emotional state, based on collected information.

[0151] An "activity plan" refers to a suggestion that includes a selection of available services and facilities, provided in a way that is optimized for the user's emotional state and input data.

[0152] To implement this invention, it is necessary to build a system based on cooperation between users, terminals, and servers. A specific example of such a system is described below.

[0153] Users access the system via their device and enter basic information to plan their activities. This includes the activity budget, preferred location and time, and type of activity. Users can also express their emotions through text messages or voice input via their device.

[0154] The device processes input data received from the user and performs sentiment analysis of the voice and text through an emotion engine. This analysis identifies the user's emotional state and classifies it as "fatigue" or "energy level," among other things. The device then sends this sentiment data to a server.

[0155] The server collects relevant data from sources based on the received sentiment data and basic information entered by the user. This includes the process of obtaining information from external databases via the internet, including weather information, congestion levels, communication network trends, and real-time facility data.

[0156] The server integrates the acquired data and uses a generative AI model to generate an activity plan tailored to the user's emotional state. The generative AI model performs complex data calculations and is used to design the optimal plan. Specifically, for example, a user experiencing fatigue might be suggested a quiet cafe or relaxation facility.

[0157] The generated activity plan is provided to the user via their device. This plan includes information on how to access facilities, recommended activities, and personalized information tailored to the user's emotional state.

[0158] As a concrete example, in a situation where "the user wants to relax on the weekend," the prompt input might be something like, "If the user is feeling down, what weekend relaxation plan would you recommend?" Based on this information, the generating AI model creates the optimal plan and provides personalized suggestions that meet the user's needs.

[0159] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0160] Step 1:

[0161] The user uses a device to access the system and enter basic information. This includes the activity budget, preferred location, time, and type of activity. The user also uses text messages or voice input to express emotions. The entered data is received directly by the device and passed on to the next step.

[0162] Step 2:

[0163] The device sends the user's voice tone and text messages to the emotion engine. The emotion engine uses an AI algorithm to analyze this data to determine the user's emotional state. Specifically, it analyzes the intonation of the voice and keywords in the text to classify the user's current emotion as "fatigued" or "energetic," for example. This analysis result serves as input for the next stage.

[0164] Step 3:

[0165] The server obtains basic user information and sentiment data received from the terminal. Using this data, the server obtains information from external sources such as weather conditions, congestion levels of surrounding facilities, the latest social media trends, and facility operating status. By collecting this data and integrating each dataset, the server forms a precise understanding of the user's situation.

[0166] Step 4:

[0167] The server uses a generative AI model to analyze integrated data and generate an activity plan optimized for the user's emotional state. The generative AI model evaluates a large amount of data points and selects the option that best matches each user's needs. For example, for a user experiencing "fatigue," a relaxation-focused plan will be created. This process enables rapid and optimal recommendations without the need for repeated hypothesis testing.

[0168] Step 5:

[0169] The generated activity plan is sent from the server to the user's device. The device displays the received plan to the user, providing detailed information on specific facilities and access methods. The user can then choose the most suitable option from the plans that correspond to their emotional state. In this way, the system completes its support for the user to make the best choice.

[0170] (Application Example 2)

[0171] 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".

[0172] Currently, many plan suggestion systems are based on user input, but they often fail to adequately consider emotional states, resulting in a lack of optimal suggestions for the user's immediate needs. Furthermore, in the food delivery sector, the lack of flexible suggestions that respond to users' moods and emotions leads to a non-personalized user experience.

[0173] 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.

[0174] In this invention, the server includes means for analyzing the user's emotional state, means for collecting data from multiple external databases, and means for generating an optimal plan based on the user's conditions and emotions. This makes it possible to provide an optimal food delivery plan or activity plan that responds to the user's emotions.

[0175] A "user" refers to a person who uses the system to input information and receive suggestions.

[0176] "Input information" refers to data that users provide to the system, such as location, time, type of activity, and budget.

[0177] An "external database" is an external source of information from which the system obtains the information necessary to generate optimal suggestions for the user.

[0178] "Information source" refers to the location and means by which data is obtained, and specifically includes weather information and social network information.

[0179] "Analysis" refers to the process of processing collected data to generate information that is valuable to the user.

[0180] "Emotional state" refers to the psychological state that indicates the user's current emotions and mood.

[0181] "Emotional analysis means" refers to functions and algorithms used to analyze a user's emotional state based on their input information.

[0182] A "plan" is a set of activities and meals suggested based on the user's conditions and emotional state.

[0183] A "suggestion" refers to the options or recommendations that the system presents to the user.

[0184] This invention is a system that provides an optimal plan while taking into account the user's emotional state. This system consists of a user terminal and a server, and includes emotion analysis means and a suggestion generation function. Specifically, it operates in the following procedure.

[0185] Users provide input information such as location, time, type of activity, and budget to the system via devices such as smartphones and computers. This input information is provided using text input or voice input. For voice input, a sentiment analysis tool is used to acquire the user's current emotional state based on the tone of their voice. Software such as a sentiment analysis API is used for sentiment analysis.

[0186] The server receives input information from the user and determines their emotional state using emotion analysis tools. If the emotion is "tired" or "seeking relaxation," it suggests services and locations that promote relaxation. Based on the analyzed emotional state and the user's basic information, the server references multiple external databases and information sources to collect necessary information in real time. This includes weather information, facility congestion levels, and social network trend information.

[0187] This collected information is analyzed, and a customized plan tailored to the user's emotional state is generated on the server. The plan includes recommended spots, ways to get there, and suggested activities. For example, a user seeking relaxation might be suggested a quiet cafe or a spa appointment.

[0188] The generated plan is sent to the user's device and displayed in a user-friendly format. The user can use the plan as a reference to make choices that suit their mood and situation. An example of a prompt might be, "Please suggest the best restaurant based on my emotional state." In this way, users can have an experience that resonates with their emotions.

[0189] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0190] Step 1:

[0191] The user inputs basic information such as location, time, type of activity, and budget through the device. Input can be via text or voice. For voice input, an emotion analysis API analyzes the tone of voice to determine the emotional state. Based on the input information, the device collects the user's basic requests.

[0192] Step 2:

[0193] Data sent from the device is transferred to the server. The server analyzes the user's emotional state and outputs emotional labels such as "tired" or "active." This analysis utilizes a generative AI model to extract emotional tendencies from the input information.

[0194] Step 3:

[0195] The server retrieves relevant information from multiple external databases and sources based on the user's emotional state and basic information. This process involves collecting real-time weather information, facility congestion levels, social network trends, and more. The server aggregates this information to prepare a dataset that is best suited to the user's emotions and circumstances.

[0196] Step 4:

[0197] The server generates a plan tailored to the user's emotional state based on aggregated data. Specifically, if the user is seeking "relaxation," it will create a plan that includes information on quiet cafes and spas. This plan generation utilizes AI to suggest optimized options.

[0198] Step 5:

[0199] The generated plan is sent from the server to the terminal and provided to the user. The terminal receives this information and displays it visually in an easy-to-understand format for the user. The user can then choose the plan that best suits their mood and situation from the suggested options.

[0200] 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.

[0201] 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.

[0202] 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.

[0203] [Second Embodiment]

[0204] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0205] 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.

[0206] 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).

[0207] 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.

[0208] 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.

[0209] 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).

[0210] 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.

[0211] 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.

[0212] 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.

[0213] 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.

[0214] 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.

[0215] 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".

[0216] This invention provides a system that generates and provides an optimal activity plan in real time based on information entered by the user. This system is implemented by utilizing the input information provided through the user's terminal and the powerful computing capabilities of the server.

[0217] The user uses a device to input conditions such as their current location, time, preferences, and budget. For example, the user might input, "I want to go to a cafe with someone near Tokyo Station at 3 PM." Once this information is entered, the device sends the data to the server. The server accesses multiple external databases and information sources to collect relevant information based on the user's input.

[0218] The server collects relevant data from the database, such as weather information, congestion levels, and social media trends. Based on this collected data, AI analyzes it and generates an activity plan that is optimal for the user's conditions. This plan generation also includes information sent from facilities in real time (such as availability and discount information).

[0219] The generated activity plan is sent to the user's device and presented in an easy-to-understand format. For example, the user might be given specific information such as, "Cafe A near Tokyo Station is currently open, you can enter from 3 PM, and there's a discount on cake sets from 2 PM." The user can then choose to keep the presented plan or request other options.

[0220] The implementation of this system provides users with a simple and rapid means to make meaningful use of unexpected free time, and also brings the benefit of optimizing customer acquisition for facilities. The embodiment of the present invention is a specific example of a system that combines efficient information provision and processing capabilities utilizing information technology.

[0221] The following describes the processing flow.

[0222] Step 1:

[0223] The user uses their device to enter conditions such as their current location, desired visit time, number of people, genre, and budget. For example, they might enter information such as, "I want to go to a cafe with two people near Tokyo Station at 3 PM."

[0224] Step 2:

[0225] The terminal sends the entered user information to the server. This transmission includes location and time information.

[0226] Step 3:

[0227] The server receives user information and accesses multiple external databases and APIs (such as weather data, social media trends, and facility congestion information) to collect necessary related information.

[0228] Step 4:

[0229] The AI ​​on the server analyzes the collected data and generates multiple activity plans tailored to the user's conditions. Real-time information from the facility is also taken into consideration during this process.

[0230] Step 5:

[0231] The server generates an activity plan and sends it to the user's device. This plan includes specific facility names, access methods, current congestion levels, and information on available menus within the budget.

[0232] Step 6:

[0233] Users can review the plans presented on their device and select the one they like best, or request another option if the current one doesn't meet their needs.

[0234] Step 7:

[0235] Depending on the selected plan, users can use that information to make reservations at facilities or use links to map apps to get to the location, if necessary.

[0236] This process allows users to efficiently select plans that allow them to spend their free time productively.

[0237] (Example 1)

[0238] 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."

[0239] The information overload of modern society makes it difficult for users to efficiently and quickly plan activities that meet their needs. Furthermore, facility information is frequently updated, making it difficult for users to access timely and accurate information. This results in users having difficulty finding meaningful experiences, and facilities struggling to attract the optimal number of visitors.

[0240] 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.

[0241] In this invention, the server includes means for the user to input conditions using a processing device, means for collecting information from a plurality of data storage locations and information sources based on the conditions, and means for organizing an activity plan via an artificial intelligence model using the collected information. This makes it possible for the user to receive an activity plan that suits their conditions in real time.

[0242] A "user" refers to an entity that uses a system to plan activities based on its own conditions.

[0243] A "processing device" refers to an electronic device used by users to input information or receive suggestions from a system.

[0244] A "data repository" refers to a storage or database where diverse information is accumulated and which has the function of accessing the data that a system needs.

[0245] "Information sources" refer to external data providers or APIs that the system accesses to obtain the data it needs.

[0246] An "artificial intelligence model" refers to an algorithm or system that analyzes vast amounts of data and generates an optimal activity plan for the user.

[0247] An "activity plan" refers to the output from a system that is compiled to suggest the optimal actions and schedule based on the user's conditions.

[0248] "Environmental condition information" refers to information about external environmental factors that affect activity plans, such as weather and temperature.

[0249] "Congestion information" refers to data about the usage status and level of congestion at specific locations or facilities.

[0250] "Social network information" refers to information about current trends and topics obtained from social media and other sources.

[0251] "Real-time information" refers to information provided by the facility in real time, including facility usage status and discount services.

[0252] This invention is a system that provides activity plans tailored to user needs, efficiently handling everything from user input of conditions to optimal suggestions.

[0253] First, the user uses a device to input their desired conditions. These devices include electronic devices such as smartphones and personal computers, and information is entered through application software or a web browser. For example, suppose a user inputs the condition, "I want to go to a cafe with someone near Tokyo Station at 3 PM." This condition is then sent to the server via the device.

[0254] The server collects relevant information from multiple data collection points and sources based on user conditions. This process involves communication over the internet to retrieve data from external sources such as weather APIs, traffic information databases, and social media trend information. The server also receives real-time information from facilities, such as availability and discount information.

[0255] The collected data is input into a generative AI model on the server. The AI ​​model analyzes this data and generates an optimal activity plan for the user in real time. In this process, a massive dataset is rapidly processed by the AI, and optimal suggestions tailored to the user's conditions are created.

[0256] The generated activity plan is sent from the server to the user's terminal. This allows the user to select an activity that suits their needs. The terminal visually presents the received suggestions to the user in an easy-to-understand manner. For example, it might display specific information such as, "Cafe A near Tokyo Station is currently open, you can enter from 3 PM, and a discount on cake sets is available from 2 PM."

[0257] For example, if a user is traveling with a friend and has some free time before moving on to their next destination, this system can be used to quickly obtain information about nearby tourist spots. An example of a prompt sentence to input into the generating AI model would be, "Please tell me about a cafe near Tokyo Station that is open to two people from 3 PM onwards."

[0258] This system provides users with a means to make meaningful use of their free time, while also promoting real-time optimization of customer acquisition for facilities.

[0259] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0260] Step 1:

[0261] The user uses their device to input their current location and desired activity conditions. Specifically, they operate an application or webpage on their device to enter conditions such as, "I want to go to a cafe with someone near Tokyo Station at 3 PM." This input data is then prepared to be sent directly to the server.

[0262] Step 2:

[0263] The terminal sends the user-entered conditions to the server. A communication protocol (e.g., HTTPS) is used for transmission via the internet. The user conditions are sent as input, and the server receives them as input data.

[0264] Step 3:

[0265] Based on the user's requested conditions, the server sends requests to multiple data collection points and sources to gather the necessary information. This includes accessing external sources such as weather APIs, traffic information, and social media trends. The server collects environmental condition information and congestion information related to the conditions and integrates the information.

[0266] Step 4:

[0267] The server inputs the collected information into the generative AI model. The AI ​​model then integrates and preprocesses the data, using it as raw material to generate an optimal activity plan based on the user's conditions. The generative AI model analyzes the large amount of data and compiles the most appropriate plan from multiple options.

[0268] Step 5:

[0269] The generated activity plan is formatted on the server and converted into a user-friendly format. Specifically, the information presentation format is adjusted to suit the user, using text, images, maps, etc. This output is then ready to be sent to the user's device.

[0270] Step 6:

[0271] The server sends the prepared activity plan to the user's terminal. The terminal receives this data and visualizes it on the user interface. Specifically, information such as "Cafe A near Tokyo Station is currently available, you can enter from 3 PM, and a discount on cake sets is available from 2 PM" is presented to the user.

[0272] Through this process, users can quickly receive proposals best suited to their needs and easily implement meaningful activity plans.

[0273] (Application Example 1)

[0274] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0275] Modern consumers want to shop and use facilities efficiently within limited time, but they face the challenge of making optimal choices due to the overwhelming amount of information available. Furthermore, users want to receive information tailored to their preferences in real time, and there is a need to provide personalized plans that meet this need.

[0276] 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.

[0277] In this invention, the server includes means for receiving input information from a user, means for collecting data from a plurality of external databases and information sources based on the input information, means for analyzing the collected data and generating an activity plan that is optimal for the user's conditions, and means for collecting information on commercial facilities in real time and generating an optimal shopping plan. This makes it possible for the user to receive an optimal activity plan tailored to their individual conditions in real time.

[0278] "Means of receiving user input information" refers to the function that allows a server to acquire information provided by a user through their device.

[0279] "Means for collecting data from external databases and information sources" refers to the function of obtaining necessary data from various information sources via the internet or other networks.

[0280] The "means for analyzing and generating an activity plan optimized for the user's conditions" refers to algorithms or programs that process the acquired data and create the best plan that matches the conditions provided by the user.

[0281] The "means for providing the generated plan to the user" is a function for transmitting and displaying the generated activity plan to the devices available to the user.

[0282] The "means for collecting information on commercial facilities and generating an optimal shopping plan" refers to a function that utilizes real-time data from shopping malls and stores to provide the user with effective shopping routes and promotion information.

[0283] This invention is a system that generates and provides an optimal activity plan in real time based on the information input by the user. In this system, the user's device functions as an interface and utilizes the computing power of the server. Specifically, the user inputs conditions such as the current location, time, individual preferences, and budget through terminals such as smartphones and smart glasses. This information is transmitted from the device to the server.

[0284] The server uses a cloud service platform, such as Google Cloud Platform or Amazon Web Services, to collect relevant information from various external databases. The collected data includes weather information, congestion status, and real-time information from commercial facilities. Programming languages such as Python are used for data processing, and data analysis is performed using an AI framework such as TensorFlow. As a result, an optimal activity plan based on the user's conditions is generated.

[0285] The generated plan is transmitted to the user's terminal and displayed on the terminal, enabling navigation and information provision in an easy-to-understand form for the user.

[0286] As a specific example, during shopping at a commercial facility in Shinjuku, for a user's request such as "want to purchase trendy clothes within 20,000 yen in the afternoon in Shinjuku", the AI analyzes the current situation of the commercial facility and provides an optimal store route and discount information.

[0287] An example of a prompt sentence for the generative AI model is something like "Please make a plan to purchase trendy fashion items within the budget at a shopping mall in Shinjuku. The current location information and budget are specified."

[0288] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0289] Step 1:

[0290] The user uses a smartphone or smart glasses to input information on their requirements, such as "want to purchase trendy items within the budget in the afternoon in Shinjuku". This input information includes the user's current location, time, preferences, and budget. The input information is sent by the terminal to the server.

[0291] Step 2:

[0292] Based on the received user information, the server accesses external databases and information sources to collect relevant information. At this stage, weather, congestion situation, and real-time information from each commercial facility are obtained. Based on this, the server uses a data processing language such as Python to format the data and convert it into an analyzable form.

[0293]

ID=27

[0294] Based on the formatted data, the server uses the generative AI model to generate an activity plan optimal for the user's conditions. The AI model analyzes the input data to identify an optimal store route, recommended items, discount information, etc. that meet the user's requirements. TensorFlow is used in this process.

[0295] Step 4:

[0296] The generated activity plan is sent from the server to the user's device. The device then displays the information based on the received plan in an easy-to-understand format and provides it to the user. For example, it might visually show a map of stores to visit or a list of recommended products.

[0297] Step 5:

[0298] The user can review the presented plan and obtain further details on points of interest. In this process, the device can send additional requests to the server to retrieve more specific information, which can then be presented to the user again.

[0299] 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.

[0300] This invention realizes a system that generates and provides an optimal activity plan by combining user input information and emotional state. By incorporating an emotion engine, it is possible to provide more personalized plan suggestions that take into account the user's emotional elements, rather than just suggestions based on factual data.

[0301] When a user inputs basic information such as location, time, type of activity, and budget through their device, the emotion engine analyzes their current emotions based on their tone of voice and text messages. For example, if a user inputs "tired" or their voice sounds subdued, the emotion engine determines that the user is seeking relaxation.

[0302] The server integrates sentiment data obtained from the user with normal condition data and collects relevant information from multiple external databases and sources. Based on weather information, congestion levels of nearby facilities, social media trends, and real-time information about the facilities, it generates an optimal activity plan that takes the user's emotional state into account.

[0303] For example, when the user's emotion is determined to be "fatigue", the server may recommend a quiet and relaxing cafe or spa. On the other hand, if it is determined to be "active", it provides plans for sports facilities or event venues.

[0304] The generated activity plan is sent to the user's terminal. This lists specific facility proposals, access methods, recommended activities, etc. including customization information corresponding to the emotion. Based on this information, the user can select the plan most suitable for their mood and situation.

[0305] As described above, the present invention aims to enrich the user's experience by utilizing an emotion engine to propose a flexible and personalized activity plan considering the user's emotional state.

[0306] The processing flow will be described below.

[0307] Step 1:

[0308] The user uses the terminal to input the conditions (location, time, number of people, genre, budget) of the desired activity. At this time, the emotion engine analyzes the user's emotion from the input voice or text message.

[0309] Step 2:

[0310] The terminal sends the condition information and emotion data obtained from the user to the server. The transmission also includes the emotional state analyzed by the emotion engine.

[0311] Step 3:

[0312] Based on the information received by the server, the server collects relevant information from multiple external databases and APIs (such as weather information, SNS trends, and facility congestion status). At this time, how the emotion information affects the extracted data is also considered.

[0313] Step 4:

[0314] The AI ​​on the server analyzes external data collected from users along with their emotional data to generate activity plans. Taking emotional information into account, it creates suggestions that align with the user's feelings, such as relaxation or exciting activities.

[0315] Step 5:

[0316] The generated plan is then refined by taking real-time information from the facility into consideration. For example, the availability of the target facility and the presence of any special events are taken into account.

[0317] Step 6:

[0318] The server sends the completed activity plan to the user's device. The plan includes emotion-based recommendations for facilities, specific activities, transportation, and an optimal action plan for a particular time period.

[0319] Step 7:

[0320] Users review the customized plans presented on their devices and consider whether to actually select one. If necessary, a function to make facility reservations on the spot is also available.

[0321] This process allows users to quickly and easily select an activity plan that suits their emotional state.

[0322] (Example 2)

[0323] 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".

[0324] Traditional activity plan provision systems use factual data based on user input to make suggestions, but they sometimes fail to adequately provide personalized plans that take into account the user's emotional factors. As a result, they cannot present the optimal options that align with the user's emotions, leading to a decrease in user experience satisfaction.

[0325] 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.

[0326] In this invention, the server includes means for receiving input data from a user, means for analyzing the emotional state of the input data, and means for collecting information from multiple information sources based on the analyzed emotional state and the input data. This makes it possible to integrate the collected information and generate an activity plan optimized for the user's emotional state using a generative AI model.

[0327] "User input data" refers to basic information that users provide to the system, such as location, time, type of activity, budget, as well as tone of voice and text messages that reflect emotions.

[0328] "Analyzing emotional state" refers to the process of analyzing a user's tone of voice and the content of their text messages to identify their emotions or psychological state.

[0329] "Information sources" refer to external databases and information services that provide information such as weather conditions, congestion levels, communication network information, and real-time facility data.

[0330] A "generative AI model" refers to artificial intelligence technology used to create optimal activity plans tailored to a user's emotional state, based on collected information.

[0331] An "activity plan" refers to a suggestion that includes a selection of available services and facilities, provided in a way that is optimized for the user's emotional state and input data.

[0332] To implement this invention, it is necessary to build a system based on cooperation between users, terminals, and servers. A specific example of such a system is described below.

[0333] Users access the system via their device and enter basic information to plan their activities. This includes the activity budget, preferred location and time, and type of activity. Users can also express their emotions through text messages or voice input via their device.

[0334] The device processes input data received from the user and performs sentiment analysis of the voice and text through an emotion engine. This analysis identifies the user's emotional state and classifies it as "fatigue" or "energy level," among other things. The device then sends this sentiment data to a server.

[0335] The server collects relevant data from sources based on the received sentiment data and basic information entered by the user. This includes the process of obtaining information from external databases via the internet, including weather information, congestion levels, communication network trends, and real-time facility data.

[0336] The server integrates the acquired data and uses a generative AI model to generate an activity plan tailored to the user's emotional state. The generative AI model performs complex data calculations and is used to design the optimal plan. Specifically, for example, a user experiencing fatigue might be suggested a quiet cafe or relaxation facility.

[0337] The generated activity plan is provided to the user via their device. This plan includes information on how to access facilities, recommended activities, and personalized information tailored to the user's emotional state.

[0338] As a concrete example, in a situation where "the user wants to relax on the weekend," the prompt input might be something like, "If the user is feeling down, what weekend relaxation plan would you recommend?" Based on this information, the generating AI model creates the optimal plan and provides personalized suggestions that meet the user's needs.

[0339] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0340] Step 1:

[0341] The user uses a device to access the system and enter basic information. This includes the activity budget, preferred location, time, and type of activity. The user also uses text messages or voice input to express emotions. The entered data is received directly by the device and passed on to the next step.

[0342] Step 2:

[0343] The device sends the user's voice tone and text messages to the emotion engine. The emotion engine uses an AI algorithm to analyze this data to determine the user's emotional state. Specifically, it analyzes the intonation of the voice and keywords in the text to classify the user's current emotion as "fatigued" or "energetic," for example. This analysis result serves as input for the next stage.

[0344] Step 3:

[0345] The server obtains basic user information and sentiment data received from the terminal. Using this data, the server obtains information from external sources such as weather conditions, congestion levels of surrounding facilities, the latest social media trends, and facility operating status. By collecting this data and integrating each dataset, the server forms a precise understanding of the user's situation.

[0346] Step 4:

[0347] The server uses a generative AI model to analyze integrated data and generate an activity plan optimized for the user's emotional state. The generative AI model evaluates a large amount of data points and selects the option that best matches each user's needs. For example, for a user experiencing "fatigue," a relaxation-focused plan will be created. This process enables rapid and optimal recommendations without the need for repeated hypothesis testing.

[0348] Step 5:

[0349] The generated activity plan is sent from the server to the user's device. The device displays the received plan to the user, providing detailed information on specific facilities and access methods. The user can then choose the most suitable option from the plans that correspond to their emotional state. In this way, the system completes its support for the user to make the best choice.

[0350] (Application Example 2)

[0351] 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."

[0352] Currently, many plan suggestion systems are based on user input, but they often fail to adequately consider emotional states, resulting in a lack of optimal suggestions for the user's immediate needs. Furthermore, in the food delivery sector, the lack of flexible suggestions that respond to users' moods and emotions leads to a non-personalized user experience.

[0353] 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.

[0354] In this invention, the server includes means for analyzing the user's emotional state, means for collecting data from multiple external databases, and means for generating an optimal plan based on the user's conditions and emotions. This makes it possible to provide an optimal food delivery plan or activity plan that responds to the user's emotions.

[0355] A "user" refers to a person who uses the system to input information and receive suggestions.

[0356] "Input information" refers to data that users provide to the system, such as location, time, type of activity, and budget.

[0357] An "external database" is an external source of information from which the system obtains the information necessary to generate optimal suggestions for the user.

[0358] "Information source" refers to the location and means by which data is obtained, and specifically includes weather information and social network information.

[0359] "Analysis" refers to the process of processing collected data to generate information that is valuable to the user.

[0360] "Emotional state" refers to the psychological state that indicates the user's current emotions and mood.

[0361] "Emotional analysis means" refers to functions and algorithms used to analyze a user's emotional state based on their input information.

[0362] A "plan" is a set of activities and meals suggested based on the user's conditions and emotional state.

[0363] A "suggestion" refers to the options or recommendations that the system presents to the user.

[0364] This invention is a system that provides an optimal plan while taking into account the user's emotional state. This system consists of a user terminal and a server, and includes emotion analysis means and a suggestion generation function. Specifically, it operates in the following procedure.

[0365] Users provide input information such as location, time, type of activity, and budget to the system via devices such as smartphones and computers. This input information is provided using text input or voice input. For voice input, a sentiment analysis tool is used to acquire the user's current emotional state based on the tone of their voice. Software such as a sentiment analysis API is used for sentiment analysis.

[0366] The server receives input information from the user and determines their emotional state using emotion analysis tools. If the emotion is "tired" or "seeking relaxation," it suggests services and locations that promote relaxation. Based on the analyzed emotional state and the user's basic information, the server references multiple external databases and information sources to collect necessary information in real time. This includes weather information, facility congestion levels, and social network trend information.

[0367] This collected information is analyzed, and a customized plan tailored to the user's emotional state is generated on the server. The plan includes recommended spots, ways to get there, and suggested activities. For example, a user seeking relaxation might be suggested a quiet cafe or a spa appointment.

[0368] The generated plan is sent to the user's device and displayed in a user-friendly format. The user can use the plan as a reference to make choices that suit their mood and situation. An example of a prompt might be, "Please suggest the best restaurant based on my emotional state." In this way, users can have an experience that resonates with their emotions.

[0369] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0370] Step 1:

[0371] The user inputs basic information such as location, time, type of activity, and budget through the device. Input can be via text or voice. For voice input, an emotion analysis API analyzes the tone of voice to determine the emotional state. Based on the input information, the device collects the user's basic requests.

[0372] Step 2:

[0373] Data sent from the device is transferred to the server. The server analyzes the user's emotional state and outputs emotional labels such as "tired" or "active." This analysis utilizes a generative AI model to extract emotional tendencies from the input information.

[0374] Step 3:

[0375] The server retrieves relevant information from multiple external databases and sources based on the user's emotional state and basic information. This process involves collecting real-time weather information, facility congestion levels, social network trends, and more. The server aggregates this information to prepare a dataset that is best suited to the user's emotions and circumstances.

[0376] Step 4:

[0377] The server generates a plan tailored to the user's emotional state based on aggregated data. Specifically, if the user is seeking "relaxation," it will create a plan that includes information on quiet cafes and spas. This plan generation utilizes AI to suggest optimized options.

[0378] Step 5:

[0379] The generated plan is sent from the server to the terminal and provided to the user. The terminal receives this information and displays it visually in an easy-to-understand format for the user. The user can then choose the plan that best suits their mood and situation from the suggested options.

[0380] 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.

[0381] 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.

[0382] 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.

[0383] [Third Embodiment]

[0384] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0385] 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.

[0386] 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).

[0387] 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.

[0388] 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.

[0389] 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).

[0390] 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.

[0391] 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.

[0392] 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.

[0393] 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.

[0394] 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.

[0395] 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".

[0396] This invention provides a system that generates and provides an optimal activity plan in real time based on information entered by the user. This system is implemented by utilizing the input information provided through the user's terminal and the powerful computing capabilities of the server.

[0397] The user uses a device to input conditions such as their current location, time, preferences, and budget. For example, the user might input, "I want to go to a cafe with someone near Tokyo Station at 3 PM." Once this information is entered, the device sends the data to the server. The server accesses multiple external databases and information sources to collect relevant information based on the user's input.

[0398] The server collects relevant data from the database, such as weather information, congestion levels, and social media trends. Based on this collected data, AI analyzes it and generates an activity plan that is optimal for the user's conditions. This plan generation also includes information sent from facilities in real time (such as availability and discount information).

[0399] The generated activity plan is sent to the user's device and presented in an easy-to-understand format. For example, the user might be given specific information such as, "Cafe A near Tokyo Station is currently open, you can enter from 3 PM, and there's a discount on cake sets from 2 PM." The user can then choose to keep the presented plan or request other options.

[0400] The implementation of this system provides users with a simple and rapid means to make meaningful use of unexpected free time, and also brings the benefit of optimizing customer acquisition for facilities. The embodiment of the present invention is a specific example of a system that combines efficient information provision and processing capabilities utilizing information technology.

[0401] The following describes the processing flow.

[0402] Step 1:

[0403] The user uses their device to enter conditions such as their current location, desired visit time, number of people, genre, and budget. For example, they might enter information such as, "I want to go to a cafe with two people near Tokyo Station at 3 PM."

[0404] Step 2:

[0405] The terminal sends the entered user information to the server. This transmission includes location and time information.

[0406] Step 3:

[0407] The server receives user information and accesses multiple external databases and APIs (such as weather data, social media trends, and facility congestion information) to collect necessary related information.

[0408] Step 4:

[0409] The AI ​​on the server analyzes the collected data and generates multiple activity plans tailored to the user's conditions. Real-time information from the facility is also taken into consideration during this process.

[0410] Step 5:

[0411] The server generates an activity plan and sends it to the user's device. This plan includes specific facility names, access methods, current congestion levels, and information on available menus within the budget.

[0412] Step 6:

[0413] Users can review the plans presented on their device and select the one they like best, or request another option if the current one doesn't meet their needs.

[0414] Step 7:

[0415] Depending on the selected plan, users can use that information to make reservations at facilities or use links to map apps to get to the location, if necessary.

[0416] This process allows users to efficiently select plans that allow them to spend their free time productively.

[0417] (Example 1)

[0418] 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."

[0419] The information overload of modern society makes it difficult for users to efficiently and quickly plan activities that meet their needs. Furthermore, facility information is frequently updated, making it difficult for users to access timely and accurate information. This results in users having difficulty finding meaningful experiences, and facilities struggling to attract the optimal number of visitors.

[0420] 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.

[0421] In this invention, the server includes means for the user to input conditions using a processing device, means for collecting information from a plurality of data storage locations and information sources based on the conditions, and means for organizing an activity plan via an artificial intelligence model using the collected information. This makes it possible for the user to receive an activity plan that suits their conditions in real time.

[0422] A "user" refers to an entity that uses a system to plan activities based on its own conditions.

[0423] A "processing device" refers to an electronic device used by users to input information or receive suggestions from a system.

[0424] A "data repository" refers to a storage or database where diverse information is accumulated and which has the function of accessing the data that a system needs.

[0425] "Information sources" refer to external data providers or APIs that the system accesses to obtain the data it needs.

[0426] An "artificial intelligence model" refers to an algorithm or system that analyzes vast amounts of data and generates an optimal activity plan for the user.

[0427] An "activity plan" refers to the output from a system that is compiled to suggest the optimal actions and schedule based on the user's conditions.

[0428] "Environmental condition information" refers to information about external environmental factors that affect activity plans, such as weather and temperature.

[0429] "Congestion information" refers to data about the usage status and level of congestion at specific locations or facilities.

[0430] "Social network information" refers to information about current trends and topics obtained from social media and other sources.

[0431] "Real-time information" refers to information provided by the facility in real time, including facility usage status and discount services.

[0432] This invention is a system that provides activity plans tailored to user needs, efficiently handling everything from user input of conditions to optimal suggestions.

[0433] First, the user uses a device to input their desired conditions. These devices include electronic devices such as smartphones and personal computers, and information is entered through application software or a web browser. For example, suppose a user inputs the condition, "I want to go to a cafe with someone near Tokyo Station at 3 PM." This condition is then sent to the server via the device.

[0434] The server collects relevant information from multiple data collection points and sources based on user conditions. This process involves communication over the internet to retrieve data from external sources such as weather APIs, traffic information databases, and social media trend information. The server also receives real-time information from facilities, such as availability and discount information.

[0435] The collected data is input into a generative AI model on the server. The AI ​​model analyzes this data and generates an optimal activity plan for the user in real time. In this process, a massive dataset is rapidly processed by the AI, and optimal suggestions tailored to the user's conditions are created.

[0436] The generated activity plan is sent from the server to the user's terminal. This allows the user to select an activity that suits their needs. The terminal visually presents the received suggestions to the user in an easy-to-understand manner. For example, it might display specific information such as, "Cafe A near Tokyo Station is currently open, you can enter from 3 PM, and a discount on cake sets is available from 2 PM."

[0437] For example, if a user is traveling with a friend and has some free time before moving on to their next destination, this system can be used to quickly obtain information about nearby tourist spots. An example of a prompt sentence to input into the generating AI model would be, "Please tell me about a cafe near Tokyo Station that is open to two people from 3 PM onwards."

[0438] This system provides users with a means to make meaningful use of their free time, while also promoting real-time optimization of customer acquisition for facilities.

[0439] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0440] Step 1:

[0441] The user uses their device to input their current location and desired activity conditions. Specifically, they operate an application or webpage on their device to enter conditions such as, "I want to go to a cafe with someone near Tokyo Station at 3 PM." This input data is then prepared to be sent directly to the server.

[0442] Step 2:

[0443] The terminal sends the user-entered conditions to the server. A communication protocol (e.g., HTTPS) is used for transmission via the internet. The user conditions are sent as input, and the server receives them as input data.

[0444] Step 3:

[0445] Based on the user's requested conditions, the server sends requests to multiple data collection points and sources to gather the necessary information. This includes accessing external sources such as weather APIs, traffic information, and social media trends. The server collects environmental condition information and congestion information related to the conditions and integrates the information.

[0446] Step 4:

[0447] The server inputs the collected information into the generative AI model. The AI ​​model then integrates and preprocesses the data, using it as raw material to generate an optimal activity plan based on the user's conditions. The generative AI model analyzes the large amount of data and compiles the most appropriate plan from multiple options.

[0448] Step 5:

[0449] The generated activity plan is formatted on the server and converted into a user-friendly format. Specifically, the information presentation format is adjusted to suit the user, using text, images, maps, etc. This output is then ready to be sent to the user's device.

[0450] Step 6:

[0451] The server sends the prepared activity plan to the user's terminal. The terminal receives this data and visualizes it on the user interface. Specifically, information such as "Cafe A near Tokyo Station is currently available, you can enter from 3 PM, and a discount on cake sets is available from 2 PM" is presented to the user.

[0452] Through this process, users can quickly receive proposals best suited to their needs and easily implement meaningful activity plans.

[0453] (Application Example 1)

[0454] 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."

[0455] Modern consumers want to shop and use facilities efficiently within limited time, but they face the challenge of making optimal choices due to the overwhelming amount of information available. Furthermore, users want to receive information tailored to their preferences in real time, and there is a need to provide personalized plans that meet this need.

[0456] 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.

[0457] In this invention, the server includes means for receiving input information from a user, means for collecting data from a plurality of external databases and information sources based on the input information, means for analyzing the collected data and generating an activity plan that is optimal for the user's conditions, and means for collecting information on commercial facilities in real time and generating an optimal shopping plan. This makes it possible for the user to receive an optimal activity plan tailored to their individual conditions in real time.

[0458] "Means of receiving user input information" refers to the function that allows a server to acquire information provided by a user through their device.

[0459] "Means for collecting data from external databases and information sources" refers to the function of obtaining necessary data from various information sources via the internet or other networks.

[0460] "Means for analyzing and generating the optimal activity plan for user conditions" refers to algorithms and programs that process acquired data and create the best plan that matches the conditions provided by the user.

[0461] "Means of providing the generated plan to the user" refers to a function for sending and displaying the generated activity plan to the user's available devices.

[0462] "Means of collecting information on commercial facilities and generating optimal shopping plans" refers to a function that utilizes real-time data from shopping malls and stores to provide users with effective shopping routes and promotional information.

[0463] This invention is a system that generates and provides an optimal activity plan in real time based on information input by the user. This system utilizes the user's device as an interface and leverages the computing power of a server. Specifically, the user inputs conditions such as their current location, time, personal preferences, and budget through a device such as a smartphone or smart glasses. This information is transmitted from the device to the server.

[0464] The server utilizes a cloud service platform, such as Google Cloud Platform or Amazon Web Services, to collect relevant information from various external databases. This collected data includes weather information, congestion levels, and real-time information from commercial facilities. Programming languages ​​such as Python are used for data processing, and AI frameworks like TensorFlow are employed for data analysis. As a result, an optimal activity plan is generated based on the user's specific requirements.

[0465] The generated plan is sent to the user's device and displayed on it, enabling user-friendly navigation and information provision.

[0466] For example, when a user is shopping at a commercial facility in Shinjuku and requests, "I want to buy trendy clothes in Shinjuku this afternoon for under 20,000 yen," the AI ​​analyzes the current situation at the facility and provides the optimal store route and discount information.

[0467] An example of a prompt message for a generative AI model would be: "Please create a plan to purchase trendy fashion items within a budget at a shopping mall in Shinjuku. Your current location and budget are specified."

[0468] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0469] Step 1:

[0470] Users use their smartphones or smart glasses to input their requests, such as "I want to buy trendy items in Shinjuku in the afternoon within my budget." This input includes the user's current location, time, preferences, and budget. The entered information is then sent to the server by the device.

[0471] Step 2:

[0472] Based on the received user information, the server accesses external databases and information sources to collect relevant information. At this stage, weather, congestion levels, and real-time information from each commercial facility are obtained. The server then uses data processing languages ​​such as Python to format the data and convert it into an analyzable format.

[0473] Step 3:

[0474] The server uses a generative AI model based on the formatted data to generate an optimal activity plan tailored to the user's conditions. The AI ​​model analyzes the input data to identify the best store routes, recommended items, discount information, and more that match the user's requests. TensorFlow is used for this process.

[0475] Step 4:

[0476] The generated activity plan is sent from the server to the user's device. The device then displays the information based on the received plan in an easy-to-understand format and provides it to the user. For example, it might visually show a map of stores to visit or a list of recommended products.

[0477] Step 5:

[0478] The user can review the presented plan and obtain further details on points of interest. In this process, the device can send additional requests to the server to retrieve more specific information, which can then be presented to the user again.

[0479] 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.

[0480] This invention realizes a system that generates and provides an optimal activity plan by combining user input information and emotional state. By incorporating an emotion engine, it is possible to provide more personalized plan suggestions that take into account the user's emotional elements, rather than just suggestions based on factual data.

[0481] When a user inputs basic information such as location, time, type of activity, and budget through their device, the emotion engine analyzes their current emotions based on their tone of voice and text messages. For example, if a user inputs "tired" or their voice sounds subdued, the emotion engine determines that the user is seeking relaxation.

[0482] The server integrates sentiment data obtained from the user with normal condition data and collects relevant information from multiple external databases and sources. Based on weather information, congestion levels of nearby facilities, social media trends, and real-time information about the facilities, it generates an optimal activity plan that takes the user's emotional state into account.

[0483] For example, if a user's emotional state is determined to be "fatigued," the server might recommend quiet, relaxing places like cafes or spas. On the other hand, if the user is determined to be "active," the server might offer plans for sports facilities or event venues.

[0484] The generated activity plan is sent to the user's device. This includes a list of specific facility suggestions, access information, and recommended activities, all tailored to the user's mood and circumstances. Based on this information, the user can select the plan that best suits their mood and situation.

[0485] As described above, the present invention aims to enrich the user experience by utilizing an emotion engine to propose flexible and individualized activity plans that take into account the user's emotional state.

[0486] The following describes the processing flow.

[0487] Step 1:

[0488] The user uses their device to input the conditions for their desired activity (location, time, number of people, genre, budget). During this process, the emotion engine analyzes the user's emotions from the input voice or text message.

[0489] Step 2:

[0490] The device sends conditional information and emotion data acquired from the user to the server. This transmission also includes the emotional state analyzed by the emotion engine.

[0491] Step 3:

[0492] Based on the information received by the server, relevant information is collected from multiple external databases and APIs (such as weather information, social media trends, and facility congestion status). During this process, the influence of emotional information on the extracted data is also considered.

[0493] Step 4:

[0494] The AI ​​on the server analyzes external data collected from users along with their emotional data to generate activity plans. Taking emotional information into account, it creates suggestions that align with the user's feelings, such as relaxation or exciting activities.

[0495] Step 5:

[0496] The generated plan is then refined by taking real-time information from the facility into consideration. For example, the availability of the target facility and the presence of any special events are taken into account.

[0497] Step 6:

[0498] The server sends the completed activity plan to the user's device. The plan includes emotion-based recommendations for facilities, specific activities, transportation, and an optimal action plan for a particular time period.

[0499] Step 7:

[0500] Users review the customized plans presented on their devices and consider whether to actually select one. If necessary, a function to make facility reservations on the spot is also available.

[0501] This process allows users to quickly and easily select an activity plan that suits their emotional state.

[0502] (Example 2)

[0503] 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."

[0504] Traditional activity plan provision systems use factual data based on user input to make suggestions, but they sometimes fail to adequately provide personalized plans that take into account the user's emotional factors. As a result, they cannot present the optimal options that align with the user's emotions, leading to a decrease in user experience satisfaction.

[0505] 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.

[0506] In this invention, the server includes means for receiving input data from a user, means for analyzing the emotional state of the input data, and means for collecting information from multiple information sources based on the analyzed emotional state and the input data. This makes it possible to integrate the collected information and generate an activity plan optimized for the user's emotional state using a generative AI model.

[0507] "User input data" refers to basic information that users provide to the system, such as location, time, type of activity, budget, as well as tone of voice and text messages that reflect emotions.

[0508] "Analyzing emotional state" refers to the process of analyzing a user's tone of voice and the content of their text messages to identify their emotions or psychological state.

[0509] "Information sources" refer to external databases and information services that provide information such as weather conditions, congestion levels, communication network information, and real-time facility data.

[0510] A "generative AI model" refers to artificial intelligence technology used to create optimal activity plans tailored to a user's emotional state, based on collected information.

[0511] An "activity plan" refers to a suggestion that includes a selection of available services and facilities, provided in a way that is optimized for the user's emotional state and input data.

[0512] To implement this invention, it is necessary to build a system based on cooperation between users, terminals, and servers. A specific example of such a system is described below.

[0513] Users access the system via their device and enter basic information to plan their activities. This includes the activity budget, preferred location and time, and type of activity. Users can also express their emotions through text messages or voice input via their device.

[0514] The device processes input data received from the user and performs sentiment analysis of the voice and text through an emotion engine. This analysis identifies the user's emotional state and classifies it as "fatigue" or "energy level," among other things. The device then sends this sentiment data to a server.

[0515] The server collects relevant data from sources based on the received sentiment data and basic information entered by the user. This includes the process of obtaining information from external databases via the internet, including weather information, congestion levels, communication network trends, and real-time facility data.

[0516] The server integrates the acquired data and uses a generative AI model to generate an activity plan tailored to the user's emotional state. The generative AI model performs complex data calculations and is used to design the optimal plan. Specifically, for example, a user experiencing fatigue might be suggested a quiet cafe or relaxation facility.

[0517] The generated activity plan is provided to the user via their device. This plan includes information on how to access facilities, recommended activities, and personalized information tailored to the user's emotional state.

[0518] As a concrete example, in a situation where "the user wants to relax on the weekend," the prompt input might be something like, "If the user is feeling down, what weekend relaxation plan would you recommend?" Based on this information, the generating AI model creates the optimal plan and provides personalized suggestions that meet the user's needs.

[0519] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0520] Step 1:

[0521] The user uses a device to access the system and enter basic information. This includes the activity budget, preferred location, time, and type of activity. The user also uses text messages or voice input to express emotions. The entered data is received directly by the device and passed on to the next step.

[0522] Step 2:

[0523] The device sends the user's voice tone and text messages to the emotion engine. The emotion engine uses an AI algorithm to analyze this data to determine the user's emotional state. Specifically, it analyzes the intonation of the voice and keywords in the text to classify the user's current emotion as "fatigued" or "energetic," for example. This analysis result serves as input for the next stage.

[0524] Step 3:

[0525] The server obtains basic user information and sentiment data received from the terminal. Using this data, the server obtains information from external sources such as weather conditions, congestion levels of surrounding facilities, the latest social media trends, and facility operating status. By collecting this data and integrating each dataset, the server forms a precise understanding of the user's situation.

[0526] Step 4:

[0527] The server uses a generative AI model to analyze integrated data and generate an activity plan optimized for the user's emotional state. The generative AI model evaluates a large amount of data points and selects the option that best matches each user's needs. For example, for a user experiencing "fatigue," a relaxation-focused plan will be created. This process enables rapid and optimal recommendations without the need for repeated hypothesis testing.

[0528] Step 5:

[0529] The generated activity plan is sent from the server to the user's device. The device displays the received plan to the user, providing detailed information on specific facilities and access methods. The user can then choose the most suitable option from the plans that correspond to their emotional state. In this way, the system completes its support for the user to make the best choice.

[0530] (Application Example 2)

[0531] 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."

[0532] Currently, many plan suggestion systems are based on user input, but they often fail to adequately consider emotional states, resulting in a lack of optimal suggestions for the user's immediate needs. Furthermore, in the food delivery sector, the lack of flexible suggestions that respond to users' moods and emotions leads to a non-personalized user experience.

[0533] 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.

[0534] In this invention, the server includes means for analyzing the user's emotional state, means for collecting data from multiple external databases, and means for generating an optimal plan based on the user's conditions and emotions. This makes it possible to provide an optimal food delivery plan or activity plan that responds to the user's emotions.

[0535] A "user" refers to a person who uses the system to input information and receive suggestions.

[0536] "Input information" refers to data that users provide to the system, such as location, time, type of activity, and budget.

[0537] An "external database" is an external source of information from which the system obtains the information necessary to generate optimal suggestions for the user.

[0538] "Information source" refers to the location and means by which data is obtained, and specifically includes weather information and social network information.

[0539] "Analysis" refers to the process of processing collected data to generate information that is valuable to the user.

[0540] "Emotional state" refers to the psychological state that indicates the user's current emotions and mood.

[0541] "Emotional analysis means" refers to functions and algorithms used to analyze a user's emotional state based on their input information.

[0542] A "plan" is a set of activities and meals suggested based on the user's conditions and emotional state.

[0543] A "suggestion" refers to the options or recommendations that the system presents to the user.

[0544] This invention is a system that provides an optimal plan while taking into account the user's emotional state. This system consists of a user terminal and a server, and includes emotion analysis means and a suggestion generation function. Specifically, it operates in the following procedure.

[0545] Users provide input information such as location, time, type of activity, and budget to the system via devices such as smartphones and computers. This input information is provided using text input or voice input. For voice input, a sentiment analysis tool is used to acquire the user's current emotional state based on the tone of their voice. Software such as a sentiment analysis API is used for sentiment analysis.

[0546] The server receives input information from the user and determines their emotional state using emotion analysis tools. If the emotion is "tired" or "seeking relaxation," it suggests services and locations that promote relaxation. Based on the analyzed emotional state and the user's basic information, the server references multiple external databases and information sources to collect necessary information in real time. This includes weather information, facility congestion levels, and social network trend information.

[0547] This collected information is analyzed, and a customized plan tailored to the user's emotional state is generated on the server. The plan includes recommended spots, ways to get there, and suggested activities. For example, a user seeking relaxation might be suggested a quiet cafe or a spa appointment.

[0548] The generated plan is sent to the user's device and displayed in a user-friendly format. The user can use the plan as a reference to make choices that suit their mood and situation. An example of a prompt might be, "Please suggest the best restaurant based on my emotional state." In this way, users can have an experience that resonates with their emotions.

[0549] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0550] Step 1:

[0551] The user inputs basic information such as location, time, type of activity, and budget through the device. Input can be via text or voice. For voice input, an emotion analysis API analyzes the tone of voice to determine the emotional state. Based on the input information, the device collects the user's basic requests.

[0552] Step 2:

[0553] Data sent from the device is transferred to the server. The server analyzes the user's emotional state and outputs emotional labels such as "tired" or "active." This analysis utilizes a generative AI model to extract emotional tendencies from the input information.

[0554] Step 3:

[0555] The server retrieves relevant information from multiple external databases and sources based on the user's emotional state and basic information. This process involves collecting real-time weather information, facility congestion levels, social network trends, and more. The server aggregates this information to prepare a dataset that is best suited to the user's emotions and circumstances.

[0556] Step 4:

[0557] The server generates a plan tailored to the user's emotional state based on aggregated data. Specifically, if the user is seeking "relaxation," it will create a plan that includes information on quiet cafes and spas. This plan generation utilizes AI to suggest optimized options.

[0558] Step 5:

[0559] The generated plan is sent from the server to the terminal and provided to the user. The terminal receives this information and displays it visually in an easy-to-understand format for the user. The user can then choose the plan that best suits their mood and situation from the suggested options.

[0560] 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.

[0561] 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.

[0562] 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.

[0563] [Fourth Embodiment]

[0564] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0565] 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.

[0566] 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).

[0567] 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.

[0568] 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.

[0569] 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).

[0570] 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.

[0571] 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.

[0572] 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.

[0573] 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.

[0574] 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.

[0575] 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.

[0576] 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".

[0577] This invention provides a system that generates and provides an optimal activity plan in real time based on information entered by the user. This system is implemented by utilizing the input information provided through the user's terminal and the powerful computing capabilities of the server.

[0578] The user uses a device to input conditions such as their current location, time, preferences, and budget. For example, the user might input, "I want to go to a cafe with someone near Tokyo Station at 3 PM." Once this information is entered, the device sends the data to the server. The server accesses multiple external databases and information sources to collect relevant information based on the user's input.

[0579] The server collects relevant data from the database, such as weather information, congestion levels, and social media trends. Based on this collected data, AI analyzes it and generates an activity plan that is optimal for the user's conditions. This plan generation also includes information sent from facilities in real time (such as availability and discount information).

[0580] The generated activity plan is sent to the user's device and presented in an easy-to-understand format. For example, the user might be given specific information such as, "Cafe A near Tokyo Station is currently open, you can enter from 3 PM, and there's a discount on cake sets from 2 PM." The user can then choose to keep the presented plan or request other options.

[0581] The implementation of this system provides users with a simple and rapid means to make meaningful use of unexpected free time, and also brings the benefit of optimizing customer acquisition for facilities. The embodiment of the present invention is a specific example of a system that combines efficient information provision and processing capabilities utilizing information technology.

[0582] The following describes the processing flow.

[0583] Step 1:

[0584] The user uses their device to enter conditions such as their current location, desired visit time, number of people, genre, and budget. For example, they might enter information such as, "I want to go to a cafe with two people near Tokyo Station at 3 PM."

[0585] Step 2:

[0586] The terminal sends the entered user information to the server. This transmission includes location and time information.

[0587] Step 3:

[0588] The server receives user information and accesses multiple external databases and APIs (such as weather data, social media trends, and facility congestion information) to collect necessary related information.

[0589] Step 4:

[0590] The AI ​​on the server analyzes the collected data and generates multiple activity plans tailored to the user's conditions. Real-time information from the facility is also taken into consideration during this process.

[0591] Step 5:

[0592] The server generates an activity plan and sends it to the user's device. This plan includes specific facility names, access methods, current congestion levels, and information on available menus within the budget.

[0593] Step 6:

[0594] Users can review the plans presented on their device and select the one they like best, or request another option if the current one doesn't meet their needs.

[0595] Step 7:

[0596] Depending on the selected plan, users can use that information to make reservations at facilities or use links to map apps to get to the location, if necessary.

[0597] This process allows users to efficiently select plans that allow them to spend their free time productively.

[0598] (Example 1)

[0599] 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".

[0600] The information overload of modern society makes it difficult for users to efficiently and quickly plan activities that meet their needs. Furthermore, facility information is frequently updated, making it difficult for users to access timely and accurate information. This results in users having difficulty finding meaningful experiences, and facilities struggling to attract the optimal number of visitors.

[0601] 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.

[0602] In this invention, the server includes means for the user to input conditions using a processing device, means for collecting information from a plurality of data storage locations and information sources based on the conditions, and means for organizing an activity plan via an artificial intelligence model using the collected information. This makes it possible for the user to receive an activity plan that suits their conditions in real time.

[0603] A "user" refers to an entity that uses a system to plan activities based on its own conditions.

[0604] A "processing device" refers to an electronic device used by users to input information or receive suggestions from a system.

[0605] A "data repository" refers to a storage or database where diverse information is accumulated and which has the function of accessing the data that a system needs.

[0606] "Information sources" refer to external data providers or APIs that the system accesses to obtain the data it needs.

[0607] An "artificial intelligence model" refers to an algorithm or system that analyzes vast amounts of data and generates an optimal activity plan for the user.

[0608] An "activity plan" refers to the output from a system that is compiled to suggest the optimal actions and schedule based on the user's conditions.

[0609] "Environmental condition information" refers to information about external environmental factors that affect activity plans, such as weather and temperature.

[0610] "Congestion information" refers to data about the usage status and level of congestion at specific locations or facilities.

[0611] "Social network information" refers to information about current trends and topics obtained from social media and other sources.

[0612] "Real-time information" refers to information provided by the facility in real time, including facility usage status and discount services.

[0613] This invention is a system that provides activity plans tailored to user needs, efficiently handling everything from user input of conditions to optimal suggestions.

[0614] First, the user uses a device to input their desired conditions. These devices include electronic devices such as smartphones and personal computers, and information is entered through application software or a web browser. For example, suppose a user inputs the condition, "I want to go to a cafe with someone near Tokyo Station at 3 PM." This condition is then sent to the server via the device.

[0615] The server collects relevant information from multiple data collection points and sources based on user conditions. This process involves communication over the internet to retrieve data from external sources such as weather APIs, traffic information databases, and social media trend information. The server also receives real-time information from facilities, such as availability and discount information.

[0616] The collected data is input into a generative AI model on the server. The AI ​​model analyzes this data and generates an optimal activity plan for the user in real time. In this process, a massive dataset is rapidly processed by the AI, and optimal suggestions tailored to the user's conditions are created.

[0617] The generated activity plan is sent from the server to the user's terminal. This allows the user to select an activity that suits their needs. The terminal visually presents the received suggestions to the user in an easy-to-understand manner. For example, it might display specific information such as, "Cafe A near Tokyo Station is currently open, you can enter from 3 PM, and a discount on cake sets is available from 2 PM."

[0618] For example, if a user is traveling with a friend and has some free time before moving on to their next destination, this system can be used to quickly obtain information about nearby tourist spots. An example of a prompt sentence to input into the generating AI model would be, "Please tell me about a cafe near Tokyo Station that is open to two people from 3 PM onwards."

[0619] This system provides users with a means to make meaningful use of their free time, while also promoting real-time optimization of customer acquisition for facilities.

[0620] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0621] Step 1:

[0622] The user uses their device to input their current location and desired activity conditions. Specifically, they operate an application or webpage on their device to enter conditions such as, "I want to go to a cafe with someone near Tokyo Station at 3 PM." This input data is then prepared to be sent directly to the server.

[0623] Step 2:

[0624] The terminal sends the user-entered conditions to the server. A communication protocol (e.g., HTTPS) is used for transmission via the internet. The user conditions are sent as input, and the server receives them as input data.

[0625] Step 3:

[0626] Based on the user's requested conditions, the server sends requests to multiple data collection points and sources to gather the necessary information. This includes accessing external sources such as weather APIs, traffic information, and social media trends. The server collects environmental condition information and congestion information related to the conditions and integrates the information.

[0627] Step 4:

[0628] The server inputs the collected information into the generative AI model. The AI ​​model then integrates and preprocesses the data, using it as raw material to generate an optimal activity plan based on the user's conditions. The generative AI model analyzes the large amount of data and compiles the most appropriate plan from multiple options.

[0629] Step 5:

[0630] The generated activity plan is formatted on the server and converted into a user-friendly format. Specifically, the information presentation format is adjusted to suit the user, using text, images, maps, etc. This output is then ready to be sent to the user's device.

[0631] Step 6:

[0632] The server sends the prepared activity plan to the user's terminal. The terminal receives this data and visualizes it on the user interface. Specifically, information such as "Cafe A near Tokyo Station is currently available, you can enter from 3 PM, and a discount on cake sets is available from 2 PM" is presented to the user.

[0633] Through this process, users can quickly receive proposals best suited to their needs and easily implement meaningful activity plans.

[0634] (Application Example 1)

[0635] 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".

[0636] Modern consumers want to shop and use facilities efficiently within limited time, but they face the challenge of making optimal choices due to the overwhelming amount of information available. Furthermore, users want to receive information tailored to their preferences in real time, and there is a need to provide personalized plans that meet this need.

[0637] 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.

[0638] In this invention, the server includes means for receiving input information from a user, means for collecting data from a plurality of external databases and information sources based on the input information, means for analyzing the collected data and generating an activity plan that is optimal for the user's conditions, and means for collecting information on commercial facilities in real time and generating an optimal shopping plan. This makes it possible for the user to receive an optimal activity plan tailored to their individual conditions in real time.

[0639] "Means of receiving user input information" refers to the function that allows a server to acquire information provided by a user through their device.

[0640] "Means for collecting data from external databases and information sources" refers to the function of obtaining necessary data from various information sources via the internet or other networks.

[0641] "Means for analyzing and generating the optimal activity plan for user conditions" refers to algorithms and programs that process acquired data and create the best plan that matches the conditions provided by the user.

[0642] "Means of providing the generated plan to the user" refers to a function for sending and displaying the generated activity plan to the user's available devices.

[0643] "Means of collecting information on commercial facilities and generating optimal shopping plans" refers to a function that utilizes real-time data from shopping malls and stores to provide users with effective shopping routes and promotional information.

[0644] This invention is a system that generates and provides an optimal activity plan in real time based on information input by the user. This system utilizes the user's device as an interface and leverages the computing power of a server. Specifically, the user inputs conditions such as their current location, time, personal preferences, and budget through a device such as a smartphone or smart glasses. This information is transmitted from the device to the server.

[0645] The server utilizes a cloud service platform, such as Google Cloud Platform or Amazon Web Services, to collect relevant information from various external databases. This collected data includes weather information, congestion levels, and real-time information from commercial facilities. Programming languages ​​such as Python are used for data processing, and AI frameworks like TensorFlow are employed for data analysis. As a result, an optimal activity plan is generated based on the user's specific requirements.

[0646] The generated plan is sent to the user's device and displayed on it, enabling user-friendly navigation and information provision.

[0647] For example, when a user is shopping at a commercial facility in Shinjuku and requests, "I want to buy trendy clothes in Shinjuku this afternoon for under 20,000 yen," the AI ​​analyzes the current situation at the facility and provides the optimal store route and discount information.

[0648] An example of a prompt message for a generative AI model would be: "Please create a plan to purchase trendy fashion items within a budget at a shopping mall in Shinjuku. Your current location and budget are specified."

[0649] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0650] Step 1:

[0651] Users use their smartphones or smart glasses to input their requests, such as "I want to buy trendy items in Shinjuku in the afternoon within my budget." This input includes the user's current location, time, preferences, and budget. The entered information is then sent to the server by the device.

[0652] Step 2:

[0653] Based on the received user information, the server accesses external databases and information sources to collect relevant information. At this stage, weather, congestion levels, and real-time information from each commercial facility are obtained. The server then uses data processing languages ​​such as Python to format the data and convert it into an analyzable format.

[0654] Step 3:

[0655] The server uses a generative AI model based on the formatted data to generate an optimal activity plan tailored to the user's conditions. The AI ​​model analyzes the input data to identify the best store routes, recommended items, discount information, and more that match the user's requests. TensorFlow is used for this process.

[0656] Step 4:

[0657] The generated activity plan is sent from the server to the user's device. The device then displays the information based on the received plan in an easy-to-understand format and provides it to the user. For example, it might visually show a map of stores to visit or a list of recommended products.

[0658] Step 5:

[0659] The user can review the presented plan and obtain further details on points of interest. In this process, the device can send additional requests to the server to retrieve more specific information, which can then be presented to the user again.

[0660] 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.

[0661] This invention realizes a system that generates and provides an optimal activity plan by combining user input information and emotional state. By incorporating an emotion engine, it is possible to provide more personalized plan suggestions that take into account the user's emotional elements, rather than just suggestions based on factual data.

[0662] When a user inputs basic information such as location, time, type of activity, and budget through their device, the emotion engine analyzes their current emotions based on their tone of voice and text messages. For example, if a user inputs "tired" or their voice sounds subdued, the emotion engine determines that the user is seeking relaxation.

[0663] The server integrates sentiment data obtained from the user with normal condition data and collects relevant information from multiple external databases and sources. Based on weather information, congestion levels of nearby facilities, social media trends, and real-time information about the facilities, it generates an optimal activity plan that takes the user's emotional state into account.

[0664] For example, if a user's emotional state is determined to be "fatigued," the server might recommend quiet, relaxing places like cafes or spas. On the other hand, if the user is determined to be "active," the server might offer plans for sports facilities or event venues.

[0665] The generated activity plan is sent to the user's device. This includes a list of specific facility suggestions, access information, and recommended activities, all tailored to the user's mood and circumstances. Based on this information, the user can select the plan that best suits their mood and situation.

[0666] As described above, the present invention aims to enrich the user experience by utilizing an emotion engine to propose flexible and individualized activity plans that take into account the user's emotional state.

[0667] The following describes the processing flow.

[0668] Step 1:

[0669] The user uses their device to input the conditions for their desired activity (location, time, number of people, genre, budget). During this process, the emotion engine analyzes the user's emotions from the input voice or text message.

[0670] Step 2:

[0671] The device sends conditional information and emotion data acquired from the user to the server. This transmission also includes the emotional state analyzed by the emotion engine.

[0672] Step 3:

[0673] Based on the information received by the server, relevant information is collected from multiple external databases and APIs (such as weather information, social media trends, and facility congestion status). During this process, the influence of emotional information on the extracted data is also considered.

[0674] Step 4:

[0675] The AI ​​on the server analyzes external data collected from users along with their emotional data to generate activity plans. Taking emotional information into account, it creates suggestions that align with the user's feelings, such as relaxation or exciting activities.

[0676] Step 5:

[0677] The generated plan is then refined by taking real-time information from the facility into consideration. For example, the availability of the target facility and the presence of any special events are taken into account.

[0678] Step 6:

[0679] The server sends the completed activity plan to the user's device. The plan includes emotion-based recommendations for facilities, specific activities, transportation, and an optimal action plan for a particular time period.

[0680] Step 7:

[0681] Users review the customized plans presented on their devices and consider whether to actually select one. If necessary, a function to make facility reservations on the spot is also available.

[0682] This process allows users to quickly and easily select an activity plan that suits their emotional state.

[0683] (Example 2)

[0684] 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".

[0685] Traditional activity plan provision systems use factual data based on user input to make suggestions, but they sometimes fail to adequately provide personalized plans that take into account the user's emotional factors. As a result, they cannot present the optimal options that align with the user's emotions, leading to a decrease in user experience satisfaction.

[0686] 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.

[0687] In this invention, the server includes means for receiving input data from a user, means for analyzing the emotional state of the input data, and means for collecting information from multiple information sources based on the analyzed emotional state and the input data. This makes it possible to integrate the collected information and generate an activity plan optimized for the user's emotional state using a generative AI model.

[0688] "User input data" refers to basic information that users provide to the system, such as location, time, type of activity, budget, as well as tone of voice and text messages that reflect emotions.

[0689] "Analyzing emotional state" refers to the process of analyzing a user's tone of voice and the content of their text messages to identify their emotions or psychological state.

[0690] "Information sources" refer to external databases and information services that provide information such as weather conditions, congestion levels, communication network information, and real-time facility data.

[0691] A "generative AI model" refers to artificial intelligence technology used to create optimal activity plans tailored to a user's emotional state, based on collected information.

[0692] An "activity plan" refers to a suggestion that includes a selection of available services and facilities, provided in a way that is optimized for the user's emotional state and input data.

[0693] To implement this invention, it is necessary to build a system based on cooperation between users, terminals, and servers. A specific example of such a system is described below.

[0694] Users access the system via their device and enter basic information to plan their activities. This includes the activity budget, preferred location and time, and type of activity. Users can also express their emotions through text messages or voice input via their device.

[0695] The device processes input data received from the user and performs sentiment analysis of the voice and text through an emotion engine. This analysis identifies the user's emotional state and classifies it as "fatigue" or "energy level," among other things. The device then sends this sentiment data to a server.

[0696] The server collects relevant data from sources based on the received sentiment data and basic information entered by the user. This includes the process of obtaining information from external databases via the internet, including weather information, congestion levels, communication network trends, and real-time facility data.

[0697] The server integrates the acquired data and uses a generative AI model to generate an activity plan tailored to the user's emotional state. The generative AI model performs complex data calculations and is used to design the optimal plan. Specifically, for example, a user experiencing fatigue might be suggested a quiet cafe or relaxation facility.

[0698] The generated activity plan is provided to the user via their device. This plan includes information on how to access facilities, recommended activities, and personalized information tailored to the user's emotional state.

[0699] As a concrete example, in a situation where "the user wants to relax on the weekend," the prompt input might be something like, "If the user is feeling down, what weekend relaxation plan would you recommend?" Based on this information, the generating AI model creates the optimal plan and provides personalized suggestions that meet the user's needs.

[0700] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0701] Step 1:

[0702] The user uses a device to access the system and enter basic information. This includes the activity budget, preferred location, time, and type of activity. The user also uses text messages or voice input to express emotions. The entered data is received directly by the device and passed on to the next step.

[0703] Step 2:

[0704] The device sends the user's voice tone and text messages to the emotion engine. The emotion engine uses an AI algorithm to analyze this data to determine the user's emotional state. Specifically, it analyzes the intonation of the voice and keywords in the text to classify the user's current emotion as "fatigued" or "energetic," for example. This analysis result serves as input for the next stage.

[0705] Step 3:

[0706] The server obtains basic user information and sentiment data received from the terminal. Using this data, the server obtains information from external sources such as weather conditions, congestion levels of surrounding facilities, the latest social media trends, and facility operating status. By collecting this data and integrating each dataset, the server forms a precise understanding of the user's situation.

[0707] Step 4:

[0708] The server uses a generative AI model to analyze integrated data and generate an activity plan optimized for the user's emotional state. The generative AI model evaluates a large amount of data points and selects the option that best matches each user's needs. For example, for a user experiencing "fatigue," a relaxation-focused plan will be created. This process enables rapid and optimal recommendations without the need for repeated hypothesis testing.

[0709] Step 5:

[0710] The generated activity plan is sent from the server to the user's device. The device displays the received plan to the user, providing detailed information on specific facilities and access methods. The user can then choose the most suitable option from the plans that correspond to their emotional state. In this way, the system completes its support for the user to make the best choice.

[0711] (Application Example 2)

[0712] 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".

[0713] Currently, many plan suggestion systems are based on user input, but they often fail to adequately consider emotional states, resulting in a lack of optimal suggestions for the user's immediate needs. Furthermore, in the food delivery sector, the lack of flexible suggestions that respond to users' moods and emotions leads to a non-personalized user experience.

[0714] 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.

[0715] In this invention, the server includes means for analyzing the user's emotional state, means for collecting data from multiple external databases, and means for generating an optimal plan based on the user's conditions and emotions. This makes it possible to provide an optimal food delivery plan or activity plan that responds to the user's emotions.

[0716] A "user" refers to a person who uses the system to input information and receive suggestions.

[0717] "Input information" refers to data that users provide to the system, such as location, time, type of activity, and budget.

[0718] An "external database" is an external source of information from which the system obtains the information necessary to generate optimal suggestions for the user.

[0719] "Information source" refers to the location and means by which data is obtained, and specifically includes weather information and social network information.

[0720] "Analysis" refers to the process of processing collected data to generate information that is valuable to the user.

[0721] "Emotional state" refers to the psychological state that indicates the user's current emotions and mood.

[0722] "Emotional analysis means" refers to functions and algorithms used to analyze a user's emotional state based on their input information.

[0723] A "plan" is a set of activities and meals suggested based on the user's conditions and emotional state.

[0724] A "suggestion" refers to the options or recommendations that the system presents to the user.

[0725] This invention is a system that provides an optimal plan while taking into account the user's emotional state. This system consists of a user terminal and a server, and includes emotion analysis means and a suggestion generation function. Specifically, it operates in the following procedure.

[0726] Users provide input information such as location, time, type of activity, and budget to the system via devices such as smartphones and computers. This input information is provided using text input or voice input. For voice input, a sentiment analysis tool is used to acquire the user's current emotional state based on the tone of their voice. Software such as a sentiment analysis API is used for sentiment analysis.

[0727] The server receives input information from the user and determines their emotional state using emotion analysis tools. If the emotion is "tired" or "seeking relaxation," it suggests services and locations that promote relaxation. Based on the analyzed emotional state and the user's basic information, the server references multiple external databases and information sources to collect necessary information in real time. This includes weather information, facility congestion levels, and social network trend information.

[0728] This collected information is analyzed, and a customized plan tailored to the user's emotional state is generated on the server. The plan includes recommended spots, ways to get there, and suggested activities. For example, a user seeking relaxation might be suggested a quiet cafe or a spa appointment.

[0729] The generated plan is sent to the user's device and displayed in a user-friendly format. The user can use the plan as a reference to make choices that suit their mood and situation. An example of a prompt might be, "Please suggest the best restaurant based on my emotional state." In this way, users can have an experience that resonates with their emotions.

[0730] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0731] Step 1:

[0732] The user inputs basic information such as location, time, type of activity, and budget through the device. Input can be via text or voice. For voice input, an emotion analysis API analyzes the tone of voice to determine the emotional state. Based on the input information, the device collects the user's basic requests.

[0733] Step 2:

[0734] Data sent from the device is transferred to the server. The server analyzes the user's emotional state and outputs emotional labels such as "tired" or "active." This analysis utilizes a generative AI model to extract emotional tendencies from the input information.

[0735] Step 3:

[0736] The server retrieves relevant information from multiple external databases and sources based on the user's emotional state and basic information. This process involves collecting real-time weather information, facility congestion levels, social network trends, and more. The server aggregates this information to prepare a dataset that is best suited to the user's emotions and circumstances.

[0737] Step 4:

[0738] The server generates a plan tailored to the user's emotional state based on aggregated data. Specifically, if the user is seeking "relaxation," it will create a plan that includes information on quiet cafes and spas. This plan generation utilizes AI to suggest optimized options.

[0739] Step 5:

[0740] The generated plan is sent from the server to the terminal and provided to the user. The terminal receives this information and displays it visually in an easy-to-understand format for the user. The user can then choose the plan that best suits their mood and situation from the suggested options.

[0741] 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.

[0742] 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.

[0743] 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.

[0744] 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.

[0745] 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.

[0746] 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.

[0747] 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.

[0748] 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.

[0749] 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."

[0750] 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.

[0751] 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.

[0752] 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.

[0753] 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.

[0754] 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.

[0755] 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.

[0756] 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.

[0757] 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.

[0758] 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.

[0759] 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.

[0760] 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.

[0761] 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.

[0762] The following is further disclosed regarding the embodiments described above.

[0763] (Claim 1)

[0764] A means of receiving input information from the user,

[0765] A means for collecting data from multiple external databases and information sources based on the aforementioned input information,

[0766] A means for analyzing the collected data and generating an activity plan that is optimal for the user's conditions,

[0767] Means for providing the generated plan to the user,

[0768] A system that includes this.

[0769] (Claim 2)

[0770] The system according to claim 1, characterized in that the external database and information sources include weather information, congestion information, and social network information.

[0771] (Claim 3)

[0772] The system according to claim 1, further comprising means for receiving real-time information from the facility and using it for generating the plan.

[0773] "Example 1"

[0774] (Claim 1)

[0775] A means by which the user inputs conditions using a processing device,

[0776] A means for collecting information from multiple data collection points and information sources based on the aforementioned conditions,

[0777] A means for formulating an activity plan via an artificial intelligence model using the information collected above,

[0778] Means for presenting the aforementioned organized activity plan to the user's processing device,

[0779] A system that includes this.

[0780] (Claim 2)

[0781] The system according to claim 1, characterized in that the data collection point and information source include environmental condition information, congestion level information, and social network information.

[0782] (Claim 3)

[0783] The system according to claim 1, further comprising means for receiving real-time information from a facility and using it in formulating the activity plan.

[0784] "Application Example 1"

[0785] (Claim 1)

[0786] A means of receiving input information from the user,

[0787] A means for collecting data from multiple external databases and information sources based on the aforementioned input information,

[0788] A means for analyzing the collected data and generating an activity plan that is optimal for the user's conditions,

[0789] Means for providing the generated plan to the user,

[0790] A means of collecting information on commercial facilities in real time and generating the optimal shopping plan,

[0791] A system that includes this.

[0792] (Claim 2)

[0793] The system according to claim 1, characterized in that the external database and information source include weather information, congestion information, and communication network information.

[0794] (Claim 3)

[0795] The system according to claim 1, further comprising means for receiving real-time information from the facility and using it for generating the plan.

[0796] "Example 2 of combining an emotion engine"

[0797] (Claim 1)

[0798] A means of receiving input data from the user,

[0799] A means for analyzing the emotional state of the input data,

[0800] A means for collecting information from multiple information sources based on the analyzed emotional state and input data,

[0801] A means for integrating the collected information and generating an activity plan optimized for the user's emotional state using a generative AI model,

[0802] Means for providing the generated activity plan to the user,

[0803] A system that includes this.

[0804] (Claim 2)

[0805] The system according to claim 1, characterized in that the information source includes weather conditions, congestion status, and communication network information.

[0806] (Claim 3)

[0807] The system according to claim 1, further comprising means for receiving real-time information from a facility and using it to generate the activity plan.

[0808] "Application example 2 when combining with an emotional engine"

[0809] (Claim 1)

[0810] A means of receiving input information from the user,

[0811] A means for collecting data from multiple external databases and information sources based on the aforementioned input information,

[0812] A means for analyzing the collected data and generating an activity plan that is optimal for the user's conditions and emotional state,

[0813] Means for providing the generated plan to the user,

[0814] A means of analyzing the emotional state of a user,

[0815] A means of suggesting the optimal meal plan or facility based on emotional state,

[0816] A system that includes this.

[0817] (Claim 2)

[0818] The system according to claim 1, characterized in that the external database and information sources include weather information, congestion information, social network information, and facility information.

[0819] (Claim 3)

[0820] The system according to claim 1, further comprising means for receiving real-time information from the facility and using it for generating the plan. [Explanation of Symbols]

[0821] 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 receiving input information from the user, A means for collecting data from multiple external databases and information sources based on the aforementioned input information, A means for analyzing the collected data and generating an activity plan that is optimal for the user's conditions, Means for providing the generated plan to the user, A system that includes this.

2. The system according to claim 1, characterized in that the external database and information source include weather information, congestion information, and social network information.

3. The system according to claim 1, further comprising means for receiving real-time information from the facility and using it for generating the plan.

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