system

Abstract

We provide the system. [Solution] A means of searching for relevant tourist destinations based on the user's current location and preferences, A means of evaluating searched tourist destinations and generating rankings, A means for automatically generating short videos based on the aforementioned ranking, A means of distributing the generated video to the user's terminal, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, people need to make quick decisions based on a lot of information within limited time. However, the conventional tourism information providing system has a huge amount of information and has a problem that it cannot quickly provide information suitable for the user's current location and preferences. For this reason, users spend a lot of time when choosing the optimal destination to visit, and there is a problem that the use is complicated.

Means for Solving the Problems

[0005] This invention provides a system that identifies tourist destinations based on the user's current location and preferences, and then evaluates and ranks them. Furthermore, it automatically generates short, easy-to-understand videos based on this information and delivers them to the user's device, thereby supporting rapid decision-making. This system allows users to instantly receive suggestions for the most suitable tourist destinations, enabling them to make decisions efficiently.

[0006] "User's current location" refers to the geographical location where the user is actually located at a specific point in time.

[0007] "Preferences" refer to the individual user's interests, concerns, and tastes.

[0008] A "tourist spot" refers to a geographical or architectural location that users are interested in visiting or sightseeing.

[0009] "Means of searching" refers to the processes and techniques used to find information based on specific criteria.

[0010] "Methods for evaluation and ranking generation" refers to the process of analyzing the relative value and popularity of tourist destinations, prioritizing them, and creating a list.

[0011] "Methods for automatically generating short videos" refer to technologies that dynamically and quickly create visual content based on given information.

[0012] "Means of distribution to user terminals" refers to the process of transmitting generated digital content to the user's device via the internet or other means of communication. [Brief explanation of the drawing]

[0013] [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]It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an 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 an emotion engine is combined.

MODE FOR CARRYING OUT THE INVENTION

[0014] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the labeled 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.

[0019] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), and the like.

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] This invention is a system for quickly recommending tourist destinations suitable for users, and mainly consists of a server, terminals, and a user interface. This system utilizes the user's current location information and preferences to identify relevant tourist spots, ranks them, and automatically generates short videos that convey their appeal.

[0035] When the server receives a request from a user, it first searches a pre-prepared database of tourist spots using the user's location and preferences. This extracts potential tourist spots accessible from the user's current location. The extracted tourist spots are then evaluated by the server based on criteria such as ease of access, user reviews, and popularity. Based on this evaluation, a ranking is generated, which identifies the most suitable spots based on the user's interests.

[0036] Next, the server retrieves visual materials and related information for each tourist spot and automatically generates a short video based on them. This video condenses the characteristics and appeal of the tourist spot and is designed to be easily understood by the user. The video created in this way is sent to the user's device and displayed in real time.

[0037] For example, if a user is planning a sightseeing trip during limited free time on a weekday, they might enter a request via their device such as "a quiet cafe I can get to in under an hour." The server analyzes this information and provides a ranking of recommended spots that reflect the user's current location and cafe preferences. Based on this information, the server generates a concise and engaging short video, which is displayed on the device, allowing the user to quickly decide where to go.

[0038] This system eliminates the need for users to process vast amounts of information, allowing them to select their destination in a relaxed manner.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] The user uses their device to enter their current location along with a request for "a good Japanese restaurant I can get to within the next hour." The device retrieves this information and sends it to an available server.

[0042] Step 2:

[0043] The server analyzes the received data and searches a tourist destination database based on the user's current location and preferences. As a result, it extracts candidate restaurants that meet the specified criteria.

[0044] Step 3:

[0045] The server evaluates the extracted restaurant candidates based on multiple criteria, including how well they match preferences, ease of access, and user reviews. Based on this evaluation, it generates a ranking that prioritizes the candidate restaurants.

[0046] Step 4:

[0047] The server uses information from ranked restaurants to automatically generate engaging short videos by incorporating visual materials and descriptions for each restaurant.

[0048] Step 5:

[0049] The server sends the generated short videos to the user's device. The videos are sorted by ranking, making it easy for users to compare them.

[0050] Step 6:

[0051] The user reviews short videos received on their device and selects restaurants that interest them. Based on the selected information, the next action is determined.

[0052] (Example 1)

[0053] 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."

[0054] Conventional tourist destination recommendation systems struggled to select the most suitable tourist facilities based on the user's current location and preferences, requiring users to manually sift through a large amount of information. Furthermore, the lack of effective means for intuitively understanding the appeal of tourist facilities made it difficult to quickly decide on the best destination.

[0055] 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.

[0056] In this invention, the server includes means for searching for relevant tourist facilities based on the user's current location and preferences, means for evaluating the searched tourist facilities and generating rankings based on location and popularity, and means for generating short videos that convey the characteristics of the tourist facilities based on the rankings. This makes it possible for users to quickly find tourist facilities that are easily accessible from their current location and that interest them. Furthermore, through the generated short videos, users can intuitively grasp the appeal of the facilities and efficiently decide where to visit.

[0057] "Users" refer to individuals who use this system to search for tourist facilities and select their destinations through the interface.

[0058] "Current location information" refers to data indicating the geographical location obtained from the user's device.

[0059] "Preferences" refers to information about the user's preferences, including past preferences, interests, or pre-entered conditions.

[0060] "Tourist facilities" refer to tourist destinations and leisure facilities that users visit for their own purposes, and the database includes information about their location, characteristics, and popularity.

[0061] "Searching method" refers to the method or process used to identify tourist facilities that meet the specified criteria from a database.

[0062] "Means of evaluation" refers to the process of judging the value of search results for tourist facilities based on criteria such as ease of access, reviews, and popularity.

[0063] "Means for generating rankings" refers to the methods and processes for ranking and displaying tourist facilities based on evaluation results.

[0064] "Methods for generating short videos" refers to the process of editing images and videos to create short, viewable video formats in order to visually convey the characteristics of tourist facilities.

[0065] "Means for transmitting to a display device" refers to communication means or protocols for transmitting the generated short video to the user's device and making it viewable.

[0066] The system of this invention mainly consists of a server, terminals, and a user interface. These components are intended to provide users with efficient search and recommendation of tourist facilities.

[0067] The server receives data indicating the user's current location and information about their preferences, and uses this data to search a database of tourist facilities. The database contains detailed information about tourist facilities, including location, features, reviews, and popularity. The server uses this information and analyzes the data using a generative AI model to recommend appropriate facilities to the user.

[0068] The evaluation criteria for tourist facilities include ease of access, review ratings, and popularity. The server generates rankings based on the evaluation results, identifying the most suitable facilities for the user. This process significantly reduces the amount of information users need to search for themselves, helping them to intuitively select facilities.

[0069] Furthermore, the server collects visual materials from selected tourist facilities and automatically generates short videos using a generative AI model. These videos are designed to concisely convey the attractions of the facilities and are intended to be visually understandable to users. The generated videos are sent to the device and displayed in real time.

[0070] As a concrete example, consider a scenario where a user enters a prompt such as "a quiet cafe I can get to in the next hour." The server analyzes this prompt and identifies suitable cafes from its database based on the user's current location. The server evaluates the candidate cafes and presents them to the user in a ranking format. Furthermore, a short video about the selected cafe is generated and displayed on the device. This allows the user to intuitively get a feel for the cafe's atmosphere and efficiently decide where to visit.

[0071] This system allows users to easily plan high-quality travel experiences without having to process large amounts of information.

[0072] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0073] Step 1:

[0074] The server receives a request for tourist spot recommendations from the user's terminal. The input includes the user's current location, preferences, and a prompt message. The server uses this information as source data for database searches and analysis. Based on the user's request, it generates an appropriate query and performs a search on the tourist facility database.

[0075] Step 2:

[0076] The server searches a database of tourist attractions based on location and preferences, and extracts relevant candidates. The input for this step is the query obtained in the previous step. The server filters the facilities in the database that match the location and calculates a relevance score based on preferences to identify the most suitable facilities for the user. The output is a list of identified tourist attractions.

[0077] Step 3:

[0078] The server evaluates and generates rankings based on an extracted list of tourist attractions. A list of candidate tourist attractions is used as input. Evaluation criteria include ease of access, review ratings, and popularity, and a generative AI model is used to calculate a numerical evaluation score. Based on this, the server outputs a ranked list.

[0079] Step 4:

[0080] The server collects visual materials about top-ranked tourist attractions and generates short videos. The input consists of a rated ranking list and visual materials related to each attraction. The server utilizes a generation AI model to automatically generate videos combining visual materials and feature descriptions. The generated videos aim to effectively convey the attractions of the attractions. The output is the generated short video.

[0081] Step 5:

[0082] The server sends the generated short video to the user's device. The input is the completed short video file. The server transfers the video to the device using the appropriate communication protocol. The device receives the video and makes it available for real-time display to the user. The output is the display on the device.

[0083] By executing each step in sequence, users can make decisions about tourist attractions quickly and intuitively.

[0084] (Application Example 1)

[0085] 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."

[0086] When travelers select appropriate tourist destinations, they need to be able to quickly and personalizedly identify spots of interest without being overwhelmed by a vast amount of information. In particular, there is a lack of systems that recommend tourist destinations that reflect the user's location and individual preferences, and that visually convey the appeal of these destinations in an intuitively understandable way.

[0087] 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.

[0088] In this invention, the server includes means for searching for relevant tourist destinations using information based on the user's location and preferences; means for evaluating the searched tourist destinations based on ease of access, reviews, and popularity, and generating rankings; and means for automatically generating short videos that represent the characteristics of the tourist destinations based on the rankings. This makes it possible for users to efficiently find tourist spots that suit their interests while they are on location, and to more easily decide where to visit.

[0089] A "user" is an individual who attempts to obtain information about tourist destinations using the system.

[0090] "Location information" refers to data that indicates the user's current geographical location, and is primarily obtained using GPS.

[0091] "Preferences" refer to a user's personal tastes and interests, and are factors that influence their choice of tourist destinations.

[0092] A "tourist spot" is a geographical location or facility that visitors intend to visit, and is valued as a tourist resource.

[0093] "Search methods" refer to a system that includes a process of finding relevant tourist destinations from a database based on the user's location information and preferences.

[0094] "Evaluation" is the process of judging a tourist destination based on criteria such as ease of access, reviews, and popularity, and determining the value associated with these factors.

[0095] A "ranking" is a list of tourist destinations sorted according to priority based on evaluation results.

[0096] "Short videos" are automatically generated short-form visual content designed to intuitively convey the characteristics of tourist destinations.

[0097] "Automatic generation methods" refer to mechanisms in which a program executes a specific process and produces deliverables without human intervention.

[0098] A "user device" is an electronic device used by a user to receive or manipulate information, and generally includes smartphones and tablets.

[0099] "Real-time delivery methods" refer to systems that transmit generated content to user devices instantly and without delay for display.

[0100] An "information processing device" is a set of hardware and program structures that collect, analyze, and process data to provide users with valuable information.

[0101] The present invention's system efficiently searches for relevant tourist destinations based on the user's location information and preferences, and automatically generates and delivers short videos that intuitively showcase their appeal. This system is implemented using a server, a user device, and related software.

[0102] First, the device uses its GPS function to obtain highly accurate location information and sends it to the server. In addition to this, the server collects user preference data from past travel history data and social media. Using this data, the server searches a database of tourist destinations and evaluates them based on criteria such as ease of access, reviews, and popularity.

[0103] The evaluated tourist destinations are organized in a ranking format, and based on this ranking, libraries such as OpenCV are used to visualize the characteristics of the tourist destinations. The automatically generated short videos effectively incorporate visual materials and explanatory text of the tourist spots. Since these videos are immediately delivered to the user's device in real time, users can quickly decide on their destinations based on abundant information, even while they are at the location.

[0104] For example, if a user traveling requests a "park that can be enjoyed with children," this system can instantly search for parks near their current location, generate short videos of suitable parks based on evaluation information, and suggest them.

[0105] In generating the short video created in this way, a generation AI model is used, and an example of a prompt message used in that process is as follows:

[0106] "Please generate a short video suggesting parks in the surrounding area that are suitable for family use, based on the user's current location and preferences."

[0107] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0108] Step 1:

[0109] The device obtains its current location using GPS functionality. It uses GPS data from the user's device as input and sends the location information to the server. As output, the server can accurately determine the user's current location. Specifically, the device periodically acquires GPS data and sends it to the server via the internet.

[0110] Step 2:

[0111] The server collects preference data from past travel history and social media to understand user preferences. It collects and analyzes the user's past behavioral history and social media posts as input. The output is a profile of the user's interests and preferences. Specifically, the server retrieves past history from the database and extracts user preferences using text analysis techniques.

[0112] Step 3:

[0113] The server searches a tourist destination database based on location information and preference data. It uses the user's current location and preferences as input to extract matching tourist destinations from the database. The output generates a list of multiple related tourist spots. Specifically, the server uses database queries to efficiently find relevant tourist destinations.

[0114] Step 4:

[0115] The server evaluates a list of tourist destinations based on accessibility, reviews, and popularity. It uses an extracted list of tourist destinations and their associated information as input, ranking them according to evaluation criteria. The output is a ranking list based on these evaluations. Specifically, the server uses a point system to numerically evaluate each tourist destination and generates a ranking based on these evaluations.

[0116] Step 5:

[0117] The server automatically generates short videos that represent the characteristics of tourist destinations based on rankings, using the OpenCV library. It uses a ranking list of evaluated tourist destinations and visual materials as input, editing them to generate the short videos. The output is visual content introducing the characteristics of each tourist destination. Specifically, the server processes the visual materials using a video editing library and adds appropriate explanations to the videos using a generation AI model.

[0118] Step 6:

[0119] The server generates short video clips and delivers them to the user's device in real time. The generated visual content is used as input and sent to the user's device in streaming format. The output is that the user's device receives the video and makes it playable. Specifically, the server transmits data over the network, and the streaming player on the device displays the video.

[0120] A generative AI model is used, and an example of a prompt message would be, "Generate a short video suggesting parks in the surrounding area that are suitable for family use, based on your current location and preferences."

[0121] 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.

[0122] This invention relates to a tourism information provision system equipped with an emotion engine that recognizes the user's emotional state. The aim of this system is to reduce the burden of decision-making in selecting tourist destinations within the time available to the user and to provide a more personalized travel experience.

[0123] First, the user uses the device to input their desired criteria for choosing a tourist destination and their current mood. The device is equipped with sensors to capture the user's voice and facial expressions, which are then analyzed by an emotion engine. The emotion engine determines the user's current emotional state from the input data and generates emotion tags such as "happy" or "tired."

[0124] The server receives the current location information, user input data, and sentiment tags sent from the terminal, and searches the tourist destination database based on this information. As a result, tourist destinations that match the user's preferences and current sentiments are identified. The identified tourist destinations are then evaluated using additional evaluation criteria based on sentiment tags, and a ranking is generated.

[0125] Based on this ranking, highly-rated tourist destinations are automatically generated as short videos incorporating content tailored to emotional tags. For example, if a user wants to relax, videos of quiet cafes or places with beautiful scenery will be generated. These videos are delivered to the device, and users can watch them in real time.

[0126] As a concrete example, suppose a user is seeking a short break during a busy schedule, and the device receives a request for a "relaxing place." At this point, the emotion engine detects the user's calm facial expression and gentle tone of voice, and sets the emotion tag to "relaxed." The server then evaluates tourist destinations based on these conditions, ranks the best places for relaxation, and generates and provides corresponding videos to the device. In this way, users can quickly and smoothly find tourist destinations that match their emotional state.

[0127] The following describes the processing flow.

[0128] Step 1:

[0129] The user provides verbal or touch input to the device regarding their desired conditions and current mood. The device acquires the input data, as well as voice and facial expression data using its built-in camera and microphone.

[0130] Step 2:

[0131] The emotion engine built into the device analyzes acquired voice and facial expression data to determine the user's current emotional state. The determined emotional state is then converted into emotion tags such as "relaxed," "excited," and "fatigued."

[0132] Step 3:

[0133] The device sends user input data, generated emotion tags, and current location information to the server. This allows the server to receive information that provides a comprehensive understanding of the user's situation.

[0134] Step 4:

[0135] The server searches a tourist destination database based on the received information and extracts candidate tourist spots that correspond to the user's preferences and emotional tags. In this process, locations that are geographically close and that match the user's tastes are given priority.

[0136] Step 5:

[0137] The server evaluates the extracted candidates and generates rankings based on relevance derived from sentiment tags, in addition to reviews and ease of access. Each tourist destination receives a special evaluation that takes into account the user's emotional state.

[0138] Step 6:

[0139] The server automatically generates short videos incorporating visual elements and information related to emotion tags, based on the rankings. These videos include visuals that match the user's current emotional state.

[0140] Step 7:

[0141] The server delivers the generated short video to the terminal. The terminal displays the received video to the user, who can then select tourist destinations to visit based on it.

[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] In today's information-driven society, selecting the optimal tourist destination from numerous options is a significant burden for travelers and tourists. In this context, there is a need to provide personalized tourist information based on the current emotional state of each individual user. However, conventional systems have the drawback of failing to consider the user's emotions, resulting in merely providing information without any real substance.

[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 searching for relevant regions based on the user's current location, preferences, and emotional state; means for analyzing acquired voice and facial expression data to generate emotional tags; and means for evaluating the searched regions and generating rankings. This makes it possible to provide personalized tourist information tailored to the user's current emotional state.

[0147] "Users" refer to individuals who use the system to obtain tourist information and plan their trips.

[0148] "Current location" refers to information indicating the geographical location of the user while they are using the system.

[0149] "Preferences" refer to information that indicates the user's personal tastes and interests, and serve as an important criterion in selecting tourist destinations.

[0150] "Emotional state" refers to the user's emotions and psychological condition at that time, and is a factor used to recommend tourist destinations.

[0151] An "emotion tag" is a label that indicates a user's emotions, generated by an emotion engine that analyzes voice and facial expression data.

[0152] "Search method" refers to the function that allows the system to find relevant regions based on the user's location, preferences, and emotional state.

[0153] A "ranking" is a list that evaluates and prioritizes specific tourist destinations based on user information.

[0154] A "short video" is video content that visually conveys an overview of a tourist destination to users based on the generated rankings.

[0155] "Distribution method" refers to the technical function that transmits the generated video to the user's device and makes it viewable.

[0156] This invention relates to a tourism information provision system equipped with an emotion engine that recognizes the emotional state of the user. This system utilizes multiple hardware and software components to enhance natural dialogue and user experience.

[0157] First, the user uses a device to input their desired criteria for choosing a tourist destination. The device is equipped with sensors such as a microphone for voice recognition and a camera for facial recognition, which collect the user's voice and facial expressions in real time.

[0158] The collected data is sent to an emotion engine, which uses machine learning algorithms to perform emotion analysis. For example, frameworks such as "TENSORFLOW®" and "PyTorch" are used to generate emotion tags such as "relaxed" and "excited" from voice tone and facial expressions.

[0159] The server receives location information, preferences, and sentiment tags from the device. Based on this data, the server uses a search algorithm to scan a tourist destination database and identify the most suitable location for the user. This database stores information on a large number of tourist destinations, and the system uses database management systems such as MySQL® or PostgreSQL.

[0160] Subsequently, the server uses a ranking algorithm to compare the selected tourist destinations and prioritize presenting the most beneficial ones to the user. Based on the ranking, it automatically generates short videos. Media libraries such as "FFmpeg" are used for video generation.

[0161] The generated videos are delivered to the user's device, and the user can watch them in real time. For example, if a user requests a "relaxing place," the emotion engine generates an emotion tag of "relax," and based on this, videos of quiet cafes or places with beautiful scenery are recommended. An example of a prompt would be, "Please suggest a refreshing spot that suits my current mood."

[0162] This system has the ability to automate the suggestion of tourist destinations that align with the user's emotional state, thereby providing a more personalized travel experience.

[0163] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0164] Step 1:

[0165] The user operates the device to input criteria for selecting a tourist destination. This includes specifying the type of place they want to visit (e.g., park, museum) and the activities they wish to engage in. The device then prepares this information for transmission to the emotion engine. The input data is processed in text format.

[0166] Step 2:

[0167] The device uses its built-in sensors to acquire user voice and facial expression data. Voice data is collected from the microphone, and facial expression data from the camera. This data is sent in real time to an emotion engine to determine the user's current emotional state. The emotion engine uses this input data to run machine learning algorithms and outputs emotion tags such as "relaxed" and "happy."

[0168] Step 3:

[0169] The server receives the user's current location, desired criteria, and generated sentiment tags from the device. Based on the received information, the server queries a tourist destination database and retrieves a list of tourist destinations that match the criteria. The database search is performed using SQL queries, and the tourist destination data is output in list format. This process identifies tourist destinations that the user is likely to be interested in.

[0170] Step 4:

[0171] The server generates a ranking based on the acquired list of tourist destinations and sentiment tags. The ranking algorithm prioritizes each destination, taking into account its attributes (rating, ease of access, user sentiment, etc.). Through this process, the ranked tourist destinations are output again in list format. Users can receive suggestions for tourist destinations in an easy-to-select format.

[0172] Step 5:

[0173] The server automatically generates short videos tailored to the user's emotions, based on top-ranked tourist destinations. Using a media library, it edits photos and videos of tourist destinations and inserts music and text. This creates visually and aurally engaging content, which is then output as a video file.

[0174] Step 6:

[0175] The server delivers the generated video to the device. The device saves the received video in the appropriate format and makes it ready for immediate playback. Users can watch the video on their device and check detailed information about tourist destinations that match their interests. This allows users to obtain relevant travel destination information in real time.

[0176] (Application Example 2)

[0177] 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".

[0178] Current tourism information services have a challenge in that they do not adequately consider the individual emotional state of users, making it difficult to suggest the optimal tourism experience for each user. In particular, there is a lack of real-time suggestions for tourist destinations based on users' emotional tags, and the provision of personalized visual content.

[0179] 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.

[0180] In this invention, the server includes means for searching for relevant tourist destinations based on the user's current location, preferences, and emotional state; means for evaluating the searched tourist destinations and generating rankings; and means for automatically generating short videos tailored to emotional tags based on the rankings. This makes it possible to suggest optimal tourist destinations according to the user's emotional state and provide personalized short videos.

[0181] A "user" refers to an individual or group that uses the system and acts as a recipient of tourism information.

[0182] "Current location" refers to data that indicates the geographical information of the user's current location and serves as the basis for searching for tourist destinations.

[0183] "Preferences" refer to information that indicates a user's interests and preferences, and are used as an indicator when identifying tourist destinations.

[0184] "Emotional state" refers to the emotional response exhibited by the user, and is a psychological state determined from the voice and facial expressions acquired by the system.

[0185] A "tourist spot" refers to a geographical or cultural location that visitors can access and that aligns with the purpose of tourism.

[0186] A "ranking" is a list of tourist destinations selected by the system and arranged in order of highest rating, organized to be useful for recommending them to users.

[0187] "Emotional tags" are labels or identifiers used to describe a user's emotional state, and are useful information for suggesting tourism content.

[0188] "Short videos" refer to video content edited to allow viewers to see visual information related to tourist destinations in a short amount of time, and are structured to attract the viewer's interest.

[0189] A "user terminal" is an information-processing device carried by a user that has the function of receiving and displaying tourist information.

[0190] This invention is a system that provides tourist information based on the user's emotional state. The server receives emotional state, current location, and preference information from the user's terminal, searches for relevant tourist locations based on this information, and generates rankings.

[0191] Specifically, the system uses the camera and microphone on the user's device to capture their facial expressions and voice. This data is processed by an emotion analysis engine using OpenCV and TensorFlow, generating emotion tags that indicate the user's emotional state. These emotion tags, along with the user's current location and preferences, are sent to the server. The server uses Scikit-learn to execute an evaluation algorithm, generating a list of tourist destinations and creating a ranking. Furthermore, based on the ranking, it automatically generates short videos of the tourist destinations using a generative AI model. These videos are tailored to the user's emotions and can be viewed in real time. Template-based video editing technology is used to generate this visual content.

[0192] For example, if a user is in a calm mood and desires a relaxing sightseeing experience, the device will request "relaxing places." The server will then rank sightseeing locations suitable for this sentiment tag and generate videos featuring quiet cafes or beautiful scenery as backgrounds, which will be provided to the user. An example of a prompt to input into the generating AI model would be, "Based on the user's emotional state, 'relaxed,' please suggest recommended sightseeing spots." In this way, a personalized sightseeing experience tailored to the user's emotional state becomes possible.

[0193] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0194] Step 1:

[0195] The device activates its camera and microphone to capture the user's emotional state, collecting facial expression and audio data. Input is real-time video and audio data, while output is pre-processed images and audio signals. This data is then processed through noise reduction and format conversion to a format suitable for analysis.

[0196] Step 2:

[0197] The device uses pre-processed data to activate an emotion analysis engine. Here, OpenCV and TensorFlow are used to determine the user's emotional state from the acquired data and generate emotion tags. The input consists of pre-processed image and audio data, and the output is a tag representing the user's emotion (e.g., "relaxed"). This process includes facial recognition through image analysis and extraction and classification of audio features.

[0198] Step 3:

[0199] The device sends generated sentiment tags, current location information, and preference information to the server. The inputs are sentiment tags, geographic coordinates, and user preference data, and the output is a request to narrow down the list of tourist destination candidates. The purpose here is to aggregate the information that will serve as the basis for tourist destination searches and prepare the server for reception.

[0200] Step 4:

[0201] The server searches a tourist destination database based on the received information and applies a ranking algorithm to evaluate and select potential tourist destinations. Inputs include sentiment tags, user location, and preference information, while output is a ranked list of evaluated tourist destinations. Scikit-learn is used to assign scores that consider the popularity of the location and the user's past preferences.

[0202] Step 5:

[0203] The server generates short videos using template-based video editing technology based on a ranking list. Input consists of evaluated input data and visual material data of tourist destinations, and output is a personalized short video. A generation AI model is used to automatically synthesize content tailored to the user's emotions.

[0204] Step 6:

[0205] The server delivers the generated short video to the terminal, which the user watches in real time. The input is the generated video data, and the output is the video playback on the terminal. During playback, the user can watch the video and make decisions about their next action (e.g., visiting a tourist spot). At this stage, it is also possible to collect user experience feedback using prompt messages.

[0206] 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.

[0207] 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.

[0208] 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.

[0209] [Second Embodiment]

[0210] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0211] 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.

[0212] 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).

[0213] 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.

[0214] 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.

[0215] 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).

[0216] 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.

[0217] 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.

[0218] 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.

[0219] 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.

[0220] 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.

[0221] 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".

[0222] This invention is a system for quickly recommending tourist destinations suitable for users, and mainly consists of a server, terminals, and a user interface. This system utilizes the user's current location information and preferences to identify relevant tourist spots, ranks them, and automatically generates short videos that convey their appeal.

[0223] When the server receives a request from a user, it first searches a pre-prepared database of tourist spots using the user's location and preferences. This extracts potential tourist spots accessible from the user's current location. The extracted tourist spots are then evaluated by the server based on criteria such as ease of access, user reviews, and popularity. Based on this evaluation, a ranking is generated, which identifies the most suitable spots based on the user's interests.

[0224] Next, the server retrieves visual materials and related information for each tourist spot and automatically generates a short video based on them. This video condenses the characteristics and appeal of the tourist spot and is designed to be easily understood by the user. The video created in this way is sent to the user's device and displayed in real time.

[0225] For example, if a user is planning a sightseeing trip during limited free time on a weekday, they might enter a request via their device such as "a quiet cafe I can get to in under an hour." The server analyzes this information and provides a ranking of recommended spots that reflect the user's current location and cafe preferences. Based on this information, the server generates a concise and engaging short video, which is displayed on the device, allowing the user to quickly decide where to go.

[0226] This system eliminates the need for users to process vast amounts of information, allowing them to select their destination in a relaxed manner.

[0227] The following describes the processing flow.

[0228] Step 1:

[0229] The user uses their device to enter their current location along with a request for "a good Japanese restaurant I can get to within the next hour." The device retrieves this information and sends it to an available server.

[0230] Step 2:

[0231] The server analyzes the received data and searches a tourist destination database based on the user's current location and preferences. As a result, it extracts candidate restaurants that meet the specified criteria.

[0232] Step 3:

[0233] The server evaluates the extracted restaurant candidates based on multiple criteria, including how well they match preferences, ease of access, and user reviews. Based on this evaluation, it generates a ranking that prioritizes the candidate restaurants.

[0234] Step 4:

[0235] The server uses information from ranked restaurants to automatically generate engaging short videos by incorporating visual materials and descriptions for each restaurant.

[0236] Step 5:

[0237] The server sends the generated short videos to the user's device. The videos are sorted by ranking, making it easy for users to compare them.

[0238] Step 6:

[0239] The user reviews short videos received on their device and selects restaurants that interest them. Based on the selected information, the next action is determined.

[0240] (Example 1)

[0241] 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."

[0242] Conventional tourist destination recommendation systems struggled to select the most suitable tourist facilities based on the user's current location and preferences, requiring users to manually sift through a large amount of information. Furthermore, the lack of effective means for intuitively understanding the appeal of tourist facilities made it difficult to quickly decide on the best destination.

[0243] 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.

[0244] In this invention, the server includes means for searching for relevant tourist facilities based on the user's current location and preferences, means for evaluating the searched tourist facilities and generating rankings based on location and popularity, and means for generating short videos that convey the characteristics of the tourist facilities based on the rankings. This makes it possible for users to quickly find tourist facilities that are easily accessible from their current location and that interest them. Furthermore, through the generated short videos, users can intuitively grasp the appeal of the facilities and efficiently decide where to visit.

[0245] "Users" refer to individuals who use this system to search for tourist facilities and select their destinations through the interface.

[0246] "Current location information" refers to data indicating the geographical location obtained from the user's device.

[0247] "Preferences" refers to information about the user's preferences, including past preferences, interests, or pre-entered conditions.

[0248] "Tourist facilities" refer to tourist destinations and leisure facilities that users visit for their own purposes, and the database includes information about their location, characteristics, and popularity.

[0249] "Searching method" refers to the method or process used to identify tourist facilities that meet the specified criteria from a database.

[0250] "Means of evaluation" refers to the process of judging the value of search results for tourist facilities based on criteria such as ease of access, reviews, and popularity.

[0251] "Means for generating rankings" refers to the methods and processes for ranking and displaying tourist facilities based on evaluation results.

[0252] "Methods for generating short videos" refers to the process of editing images and videos to create short, viewable video formats in order to visually convey the characteristics of tourist facilities.

[0253] "Means for transmitting to a display device" refers to communication means or protocols for transmitting the generated short video to the user's device and making it viewable.

[0254] The system of this invention mainly consists of a server, terminals, and a user interface. These components are intended to provide users with efficient search and recommendation of tourist facilities.

[0255] The server receives data indicating the user's current location and information about their preferences, and uses this data to search a database of tourist facilities. The database contains detailed information about tourist facilities, including location, features, reviews, and popularity. The server uses this information and analyzes the data using a generative AI model to recommend appropriate facilities to the user.

[0256] The evaluation criteria for tourist facilities include ease of access, review ratings, and popularity. The server generates rankings based on the evaluation results, identifying the most suitable facilities for the user. This process significantly reduces the amount of information users need to search for themselves, helping them to intuitively select facilities.

[0257] Furthermore, the server collects visual materials from selected tourist facilities and automatically generates short videos using a generative AI model. These videos are designed to concisely convey the attractions of the facilities and are intended to be visually understandable to users. The generated videos are sent to the device and displayed in real time.

[0258] As a concrete example, consider a scenario where a user enters a prompt such as "a quiet cafe I can get to in the next hour." The server analyzes this prompt and identifies suitable cafes from its database based on the user's current location. The server evaluates the candidate cafes and presents them to the user in a ranking format. Furthermore, a short video about the selected cafe is generated and displayed on the device. This allows the user to intuitively get a feel for the cafe's atmosphere and efficiently decide where to visit.

[0259] This system allows users to easily plan high-quality travel experiences without having to process large amounts of information.

[0260] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0261] Step 1:

[0262] The server receives a request for tourist spot recommendations from the user's terminal. The input includes the user's current location, preferences, and a prompt message. The server uses this information as source data for database searches and analysis. Based on the user's request, it generates an appropriate query and performs a search on the tourist facility database.

[0263] Step 2:

[0264] The server searches a database of tourist attractions based on location and preferences, and extracts relevant candidates. The input for this step is the query obtained in the previous step. The server filters the facilities in the database that match the location and calculates a relevance score based on preferences to identify the most suitable facilities for the user. The output is a list of identified tourist attractions.

[0265] Step 3:

[0266] The server evaluates and generates rankings based on an extracted list of tourist attractions. A list of candidate tourist attractions is used as input. Evaluation criteria include ease of access, review ratings, and popularity, and a generative AI model is used to calculate a numerical evaluation score. Based on this, the server outputs a ranked list.

[0267] Step 4:

[0268] The server collects visual materials about top-ranked tourist attractions and generates short videos. The input consists of a rated ranking list and visual materials related to each attraction. The server utilizes a generation AI model to automatically generate videos combining visual materials and feature descriptions. The generated videos aim to effectively convey the attractions of the attractions. The output is the generated short video.

[0269] Step 5:

[0270] The server sends the generated short video to the user's device. The input is the completed short video file. The server transfers the video to the device using the appropriate communication protocol. The device receives the video and makes it available for real-time display to the user. The output is the display on the device.

[0271] By executing each step in sequence, users can make decisions about tourist attractions quickly and intuitively.

[0272] (Application Example 1)

[0273] 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."

[0274] When travelers select appropriate tourist destinations, they need to be able to quickly and personalizedly identify spots of interest without being overwhelmed by a vast amount of information. In particular, there is a lack of systems that recommend tourist destinations that reflect the user's location and individual preferences, and that visually convey the appeal of these destinations in an intuitively understandable way.

[0275] 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.

[0276] In this invention, the server includes means for searching for relevant tourist destinations using information based on the user's location and preferences; means for evaluating the searched tourist destinations based on ease of access, reviews, and popularity, and generating rankings; and means for automatically generating short videos that represent the characteristics of the tourist destinations based on the rankings. This makes it possible for users to efficiently find tourist spots that suit their interests while they are on location, and to more easily decide where to visit.

[0277] A "user" is an individual who attempts to obtain information about tourist destinations using the system.

[0278] "Location information" refers to data that indicates the user's current geographical location, and is primarily obtained using GPS.

[0279] "Preferences" refer to a user's personal tastes and interests, and are factors that influence their choice of tourist destinations.

[0280] A "tourist spot" is a geographical location or facility that visitors intend to visit, and is valued as a tourist resource.

[0281] The "searching means" is a mechanism that includes the process of retrieving relevant tourist attractions from a database based on the user's location information and preferences.

[0282] "Evaluation" is a process of judging tourist attractions based on criteria such as ease of access, reviews, popularity, etc., and determining the value indicating them.

[0283] "Ranking" is a list that arranges tourist attractions according to their priorities based on the evaluation results.

[0284] "Short-time video" is short-scale visual content that is automatically generated for the purpose of intuitively conveying the characteristics of tourist attractions.

[0285] The "automatically generating means" is a mechanism in which a program executes a specific process without human intervention to produce a result.

[0286] The "user device" is an electronic device used by the user to receive and operate information, and generally includes smartphones and tablets.

[0287] The "means for real-time distribution" is a mechanism that immediately transmits the generated content to the user device without delay for display.

[0288] The "information processing device" is a series of hardware and program structures that collect, analyze, and process data to provide information valuable to the user

[0289] The system of the present invention efficiently searches for relevant tourist attractions based on the user's location information and preferences, and automatically generates and distributes short-time videos for intuitively showing their charm. This system is realized using a server, a user device, and related software.

[0290] First, the device uses its GPS function to obtain highly accurate location information and sends it to the server. In addition to this, the server collects user preference data from past travel history data and social media. Using this data, the server searches a database of tourist destinations and evaluates them based on criteria such as ease of access, reviews, and popularity.

[0291] The evaluated tourist destinations are organized in a ranking format, and based on this ranking, libraries such as OpenCV are used to visualize the characteristics of the tourist destinations. The automatically generated short videos effectively incorporate visual materials and explanatory text of the tourist spots. Since these videos are immediately delivered to the user's device in real time, users can quickly decide on their destinations based on abundant information, even while they are at the location.

[0292] For example, if a user traveling requests a "park that can be enjoyed with children," this system can instantly search for parks near their current location, generate short videos of suitable parks based on evaluation information, and suggest them.

[0293] In generating the short video created in this way, a generation AI model is used, and an example of a prompt message used in that process is as follows:

[0294] "Please generate a short video suggesting parks in the surrounding area that are suitable for family use, based on the user's current location and preferences."

[0295] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0296] Step 1:

[0297] The device obtains its current location using GPS functionality. It uses GPS data from the user's device as input and sends the location information to the server. As output, the server can accurately determine the user's current location. Specifically, the device periodically acquires GPS data and sends it to the server via the internet.

[0298] Step 2:

[0299] The server collects preference data from past travel history and social media to understand user preferences. It collects and analyzes the user's past behavioral history and social media posts as input. The output is a profile of the user's interests and preferences. Specifically, the server retrieves past history from the database and extracts user preferences using text analysis techniques.

[0300] Step 3:

[0301] The server searches a tourist destination database based on location information and preference data. It uses the user's current location and preferences as input to extract matching tourist destinations from the database. The output generates a list of multiple related tourist spots. Specifically, the server uses database queries to efficiently find relevant tourist destinations.

[0302] Step 4:

[0303] The server evaluates a list of tourist destinations based on accessibility, reviews, and popularity. It uses an extracted list of tourist destinations and their associated information as input, ranking them according to evaluation criteria. The output is a ranking list based on these evaluations. Specifically, the server uses a point system to numerically evaluate each tourist destination and generates a ranking based on these evaluations.

[0304] Step 5:

[0305] The server automatically generates short videos that represent the characteristics of tourist attractions based on rankings using the OpenCV library. Using the ranked list of evaluated tourist destinations and visual materials as inputs, they are edited to generate short videos. As output, visual content that introduces the characteristics of each tourist attraction is generated. As a specific operation, the server processes the visual materials using a video editing library and adds appropriate explanations to the videos using a generative AI model.

[0306] Step 6:

[0307] The server distributes the short videos generated in real time to the user's terminal. Using the generated visual content as input, it is transmitted to the user's device in a streaming format. As output, the user terminal can receive and play the video. As a specific operation, the server sends data via the network, and on the terminal side, a streaming player displays the video.

[0308] A generative AI model is used, and examples of prompt texts at that time include "Please generate a short video that proposes a park suitable for family use in the vicinity based on the current location and preferences."

[0309] Furthermore, an emotion engine that estimates the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion recognition model 59 and perform specific processing using the user's emotions.

[0310] 0This invention is a tourist information providing system equipped with an emotion engine that recognizes the user's emotional state. This system aims to reduce the burden of decision-making in selecting tourist attractions within the time the user faces and provide a more individualized travel experience.

[0311] First, the user uses the device to input their desired criteria for choosing a tourist destination and their current mood. The device is equipped with sensors to capture the user's voice and facial expressions, which are then analyzed by an emotion engine. The emotion engine determines the user's current emotional state from the input data and generates emotion tags such as "happy" or "tired."

[0312] The server receives the current location information, user input data, and sentiment tags sent from the terminal, and searches the tourist destination database based on this information. As a result, tourist destinations that match the user's preferences and current sentiments are identified. The identified tourist destinations are then evaluated using additional evaluation criteria based on sentiment tags, and a ranking is generated.

[0313] Based on this ranking, highly-rated tourist destinations are automatically generated as short videos incorporating content tailored to emotional tags. For example, if a user wants to relax, videos of quiet cafes or places with beautiful scenery will be generated. These videos are delivered to the device, and users can watch them in real time.

[0314] As a concrete example, suppose a user is seeking a short break during a busy schedule, and the device receives a request for a "relaxing place." At this point, the emotion engine detects the user's calm facial expression and gentle tone of voice, and sets the emotion tag to "relaxed." The server then evaluates tourist destinations based on these conditions, ranks the best places for relaxation, and generates and provides corresponding videos to the device. In this way, users can quickly and smoothly find tourist destinations that match their emotional state.

[0315] The following describes the processing flow.

[0316] Step 1:

[0317] The user provides verbal or touch input to the device regarding their desired conditions and current mood. The device acquires the input data, as well as voice and facial expression data using its built-in camera and microphone.

[0318] Step 2:

[0319] The emotion engine built into the device analyzes acquired voice and facial expression data to determine the user's current emotional state. The determined emotional state is then converted into emotion tags such as "relaxed," "excited," and "fatigued."

[0320] Step 3:

[0321] The device sends user input data, generated emotion tags, and current location information to the server. This allows the server to receive information that provides a comprehensive understanding of the user's situation.

[0322] Step 4:

[0323] The server searches a tourist destination database based on the received information and extracts candidate tourist spots that correspond to the user's preferences and emotional tags. In this process, locations that are geographically close and that match the user's tastes are given priority.

[0324] Step 5:

[0325] The server evaluates the extracted candidates and generates rankings based on relevance derived from sentiment tags, in addition to reviews and ease of access. Each tourist destination receives a special evaluation that takes into account the user's emotional state.

[0326] Step 6:

[0327] The server automatically generates short videos incorporating visual elements and information related to emotion tags, based on the rankings. These videos include visuals that match the user's current emotional state.

[0328] Step 7:

[0329] The server delivers the generated short video to the terminal. The terminal displays the received video to the user, who can then select tourist destinations to visit based on it.

[0330] (Example 2)

[0331] 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".

[0332] In today's information-driven society, selecting the optimal tourist destination from numerous options is a significant burden for travelers and tourists. In this context, there is a need to provide personalized tourist information based on the current emotional state of each individual user. However, conventional systems have the drawback of failing to consider the user's emotions, resulting in merely providing information without any real substance.

[0333] 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.

[0334] In this invention, the server includes means for searching for relevant regions based on the user's current location, preferences, and emotional state; means for analyzing acquired voice and facial expression data to generate emotional tags; and means for evaluating the searched regions and generating rankings. This makes it possible to provide personalized tourist information tailored to the user's current emotional state.

[0335] "Users" refer to individuals who use the system to obtain tourist information and plan their trips.

[0336] "Current location" refers to information indicating the geographical location of the user while they are using the system.

[0337] "Preferences" refer to information that indicates the user's personal tastes and interests, and serve as an important criterion in selecting tourist destinations.

[0338] "Emotional state" refers to the user's emotions and psychological condition at that time, and is a factor used to recommend tourist destinations.

[0339] An "emotion tag" is a label that indicates a user's emotions, generated by an emotion engine that analyzes voice and facial expression data.

[0340] "Search method" refers to the function that allows the system to find relevant regions based on the user's location, preferences, and emotional state.

[0341] A "ranking" is a list that evaluates and prioritizes specific tourist destinations based on user information.

[0342] A "short video" is video content that visually conveys an overview of a tourist destination to users based on the generated rankings.

[0343] "Distribution method" refers to the technical function that transmits the generated video to the user's device and makes it viewable.

[0344] This invention relates to a tourism information provision system equipped with an emotion engine that recognizes the emotional state of the user. This system utilizes multiple hardware and software components to enhance natural dialogue and user experience.

[0345] First, the user uses a device to input their desired criteria for choosing a tourist destination. The device is equipped with sensors such as a microphone for voice recognition and a camera for facial recognition, which collect the user's voice and facial expressions in real time.

[0346] The collected data is sent to an emotion engine, which uses machine learning algorithms to perform sentiment analysis. For example, it uses frameworks such as "TensorFlow" or "PyTorch" to generate sentiment tags such as "relaxed" or "excited" from voice tone and facial expressions.

[0347] The server receives location information, preferences, and sentiment tags from the device. Based on this data, the server uses a search algorithm to scan a tourist destination database and identify the best location for the user. This database stores information on a large number of tourist destinations, and the system uses database management systems such as MySQL or PostgreSQL.

[0348] Subsequently, the server uses a ranking algorithm to compare the selected tourist destinations and prioritize presenting the most beneficial ones to the user. Based on the ranking, it automatically generates short videos. Media libraries such as "FFmpeg" are used for video generation.

[0349] The generated videos are delivered to the user's device, and the user can watch them in real time. For example, if a user requests a "relaxing place," the emotion engine generates an emotion tag of "relax," and based on this, videos of quiet cafes or places with beautiful scenery are recommended. An example of a prompt would be, "Please suggest a refreshing spot that suits my current mood."

[0350] This system has the ability to automate the suggestion of tourist destinations that align with the user's emotional state, thereby providing a more personalized travel experience.

[0351] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0352] Step 1:

[0353] The user operates the device to input criteria for selecting a tourist destination. This includes specifying the type of place they want to visit (e.g., park, museum) and the activities they wish to engage in. The device then prepares this information for transmission to the emotion engine. The input data is processed in text format.

[0354] Step 2:

[0355] The device uses its built-in sensors to acquire user voice and facial expression data. Voice data is collected from the microphone, and facial expression data from the camera. This data is sent in real time to an emotion engine to determine the user's current emotional state. The emotion engine uses this input data to run machine learning algorithms and outputs emotion tags such as "relaxed" and "happy."

[0356] Step 3:

[0357] The server receives the user's current location, desired criteria, and generated sentiment tags from the device. Based on the received information, the server queries a tourist destination database and retrieves a list of tourist destinations that match the criteria. The database search is performed using SQL queries, and the tourist destination data is output in list format. This process identifies tourist destinations that the user is likely to be interested in.

[0358] Step 4:

[0359] The server generates a ranking based on the acquired list of tourist destinations and sentiment tags. The ranking algorithm prioritizes each destination, taking into account its attributes (rating, ease of access, user sentiment, etc.). Through this process, the ranked tourist destinations are output again in list format. Users can receive suggestions for tourist destinations in an easy-to-select format.

[0360] Step 5:

[0361] The server automatically generates short videos tailored to the user's emotions, based on top-ranked tourist destinations. Using a media library, it edits photos and videos of tourist destinations and inserts music and text. This creates visually and aurally engaging content, which is then output as a video file.

[0362] Step 6:

[0363] The server delivers the generated video to the device. The device saves the received video in the appropriate format and makes it ready for immediate playback. Users can watch the video on their device and check detailed information about tourist destinations that match their interests. This allows users to obtain relevant travel destination information in real time.

[0364] (Application Example 2)

[0365] 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 as the "terminal".

[0366] Current tourism information services have a challenge in that they do not adequately consider the individual emotional state of users, making it difficult to suggest the optimal tourism experience for each user. In particular, there is a lack of real-time suggestions for tourist destinations based on users' emotional tags, and the provision of personalized visual content.

[0367] 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.

[0368] In this invention, the server includes means for searching for relevant tourist destinations based on the user's current location, preferences, and emotional state; means for evaluating the searched tourist destinations and generating rankings; and means for automatically generating short videos tailored to emotional tags based on the rankings. This makes it possible to suggest optimal tourist destinations according to the user's emotional state and provide personalized short videos.

[0369] A "user" refers to an individual or group that uses the system and acts as a recipient of tourism information.

[0370] "Current location" refers to data that indicates the geographical information of the user's current location and serves as the basis for searching for tourist destinations.

[0371] "Preferences" refer to information that indicates a user's interests and preferences, and are used as an indicator when identifying tourist destinations.

[0372] "Emotional state" refers to the emotional response exhibited by the user, and is a psychological state determined from the voice and facial expressions acquired by the system.

[0373] A "tourist spot" refers to a geographical or cultural location that visitors can access and that aligns with the purpose of tourism.

[0374] A "ranking" is a list of tourist destinations selected by the system and arranged in order of highest rating, organized to be useful for recommending them to users.

[0375] "Emotional tags" are labels or identifiers used to describe a user's emotional state, and are useful information for suggesting tourism content.

[0376] "Short videos" refer to video content edited to allow viewers to see visual information related to tourist destinations in a short amount of time, and are structured to attract the viewer's interest.

[0377] A "user terminal" is an information-processing device carried by a user that has the function of receiving and displaying tourist information.

[0378] This invention is a system that provides tourist information based on the user's emotional state. The server receives emotional state, current location, and preference information from the user's terminal, searches for relevant tourist locations based on this information, and generates rankings.

[0379] Specifically, the system uses the camera and microphone on the user's device to capture their facial expressions and voice. This data is processed by an emotion analysis engine using OpenCV and TensorFlow, generating emotion tags that indicate the user's emotional state. These emotion tags, along with the user's current location and preferences, are sent to the server. The server uses Scikit-learn to execute an evaluation algorithm, generating a list of tourist destinations and creating a ranking. Furthermore, based on the ranking, it automatically generates short videos of the tourist destinations using a generative AI model. These videos are tailored to the user's emotions and can be viewed in real time. Template-based video editing technology is used to generate this visual content.

[0380] For example, if a user is in a calm mood and desires a relaxing sightseeing experience, the device will request "relaxing places." The server will then rank sightseeing locations suitable for this sentiment tag and generate videos featuring quiet cafes or beautiful scenery as backgrounds, which will be provided to the user. An example of a prompt to input into the generating AI model would be, "Based on the user's emotional state, 'relaxed,' please suggest recommended sightseeing spots." In this way, a personalized sightseeing experience tailored to the user's emotional state becomes possible.

[0381] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0382] Step 1:

[0383] The device activates its camera and microphone to capture the user's emotional state, collecting facial expression and audio data. Input is real-time video and audio data, while output is pre-processed images and audio signals. This data is then processed through noise reduction and format conversion to a format suitable for analysis.

[0384] Step 2:

[0385] The device uses pre-processed data to activate an emotion analysis engine. Here, OpenCV and TensorFlow are used to determine the user's emotional state from the acquired data and generate emotion tags. The input consists of pre-processed image and audio data, and the output is a tag representing the user's emotion (e.g., "relaxed"). This process includes facial recognition through image analysis and extraction and classification of audio features.

[0386] Step 3:

[0387] The device sends generated sentiment tags, current location information, and preference information to the server. The inputs are sentiment tags, geographic coordinates, and user preference data, and the output is a request to narrow down the list of tourist destination candidates. The purpose here is to aggregate the information that will serve as the basis for tourist destination searches and prepare the server for reception.

[0388] Step 4:

[0389] The server searches a tourist destination database based on the received information and applies a ranking algorithm to evaluate and select potential tourist destinations. Inputs include sentiment tags, user location, and preference information, while output is a ranked list of evaluated tourist destinations. Scikit-learn is used to assign scores that consider the popularity of the location and the user's past preferences.

[0390] Step 5:

[0391] The server generates short videos using template-based video editing technology based on a ranking list. Input consists of evaluated input data and visual material data of tourist destinations, and output is a personalized short video. A generation AI model is used to automatically synthesize content tailored to the user's emotions.

[0392] Step 6:

[0393] The server delivers the generated short video to the terminal, which the user watches in real time. The input is the generated video data, and the output is the video playback on the terminal. During playback, the user can watch the video and make decisions about their next action (e.g., visiting a tourist spot). At this stage, it is also possible to collect user experience feedback using prompt messages.

[0394] 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.

[0395] 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.

[0396] 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.

[0397] [Third Embodiment]

[0398] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0399] 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.

[0400] 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).

[0401] 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.

[0402] 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.

[0403] 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).

[0404] 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.

[0405] 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.

[0406] 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.

[0407] 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.

[0408] 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.

[0409] 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".

[0410] This invention is a system for quickly recommending tourist destinations suitable for users, and mainly consists of a server, terminals, and a user interface. This system utilizes the user's current location information and preferences to identify relevant tourist spots, ranks them, and automatically generates short videos that convey their appeal.

[0411] When the server receives a request from a user, it first searches a pre-prepared database of tourist spots using the user's location and preferences. This extracts potential tourist spots accessible from the user's current location. The extracted tourist spots are then evaluated by the server based on criteria such as ease of access, user reviews, and popularity. Based on this evaluation, a ranking is generated, which identifies the most suitable spots based on the user's interests.

[0412] Next, the server retrieves visual materials and related information for each tourist spot and automatically generates a short video based on them. This video condenses the characteristics and appeal of the tourist spot and is designed to be easily understood by the user. The video created in this way is sent to the user's device and displayed in real time.

[0413] For example, if a user is planning a sightseeing trip during limited free time on a weekday, they might enter a request via their device such as "a quiet cafe I can get to in under an hour." The server analyzes this information and provides a ranking of recommended spots that reflect the user's current location and cafe preferences. Based on this information, the server generates a concise and engaging short video, which is displayed on the device, allowing the user to quickly decide where to go.

[0414] This system eliminates the need for users to process vast amounts of information, allowing them to select their destination in a relaxed manner.

[0415] The following describes the processing flow.

[0416] Step 1:

[0417] The user uses their device to enter their current location along with a request for "a good Japanese restaurant I can get to within the next hour." The device retrieves this information and sends it to an available server.

[0418] Step 2:

[0419] The server analyzes the received data and searches a tourist destination database based on the user's current location and preferences. As a result, it extracts candidate restaurants that meet the specified criteria.

[0420] Step 3:

[0421] The server evaluates the extracted restaurant candidates based on multiple criteria, including how well they match preferences, ease of access, and user reviews. Based on this evaluation, it generates a ranking that prioritizes the candidate restaurants.

[0422] Step 4:

[0423] The server uses information from ranked restaurants to automatically generate engaging short videos by incorporating visual materials and descriptions for each restaurant.

[0424] Step 5:

[0425] The server sends the generated short videos to the user's device. The videos are sorted by ranking, making it easy for users to compare them.

[0426] Step 6:

[0427] The user reviews short videos received on their device and selects restaurants that interest them. Based on the selected information, the next action is determined.

[0428] (Example 1)

[0429] 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."

[0430] Conventional tourist destination recommendation systems struggled to select the most suitable tourist facilities based on the user's current location and preferences, requiring users to manually sift through a large amount of information. Furthermore, the lack of effective means for intuitively understanding the appeal of tourist facilities made it difficult to quickly decide on the best destination.

[0431] 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.

[0432] In this invention, the server includes means for searching for relevant tourist facilities based on the user's current location and preferences, means for evaluating the searched tourist facilities and generating rankings based on location and popularity, and means for generating short videos that convey the characteristics of the tourist facilities based on the rankings. This makes it possible for users to quickly find tourist facilities that are easily accessible from their current location and that interest them. Furthermore, through the generated short videos, users can intuitively grasp the appeal of the facilities and efficiently decide where to visit.

[0433] "Users" refer to individuals who use this system to search for tourist facilities and select their destinations through the interface.

[0434] "Current location information" refers to data indicating the geographical location obtained from the user's device.

[0435] "Preferences" refers to information about the user's preferences, including past preferences, interests, or pre-entered conditions.

[0436] "Tourist facilities" refer to tourist destinations and leisure facilities that users visit for their own purposes, and the database includes information about their location, characteristics, and popularity.

[0437] "Searching method" refers to the method or process used to identify tourist facilities that meet the specified criteria from a database.

[0438] "Means of evaluation" refers to the process of judging the value of search results for tourist facilities based on criteria such as ease of access, reviews, and popularity.

[0439] "Means for generating rankings" refers to the methods and processes for ranking and displaying tourist facilities based on evaluation results.

[0440] "Methods for generating short videos" refers to the process of editing images and videos to create short, viewable video formats in order to visually convey the characteristics of tourist facilities.

[0441] "Means for transmitting to a display device" refers to communication means or protocols for transmitting the generated short video to the user's device and making it viewable.

[0442] The system of this invention mainly consists of a server, terminals, and a user interface. These components are intended to provide users with efficient search and recommendation of tourist facilities.

[0443] The server receives data indicating the user's current location and information about their preferences, and uses this data to search a database of tourist facilities. The database contains detailed information about tourist facilities, including location, features, reviews, and popularity. The server uses this information and analyzes the data using a generative AI model to recommend appropriate facilities to the user.

[0444] The evaluation criteria for tourist facilities include ease of access, review ratings, and popularity. The server generates rankings based on the evaluation results, identifying the most suitable facilities for the user. This process significantly reduces the amount of information users need to search for themselves, helping them to intuitively select facilities.

[0445] Furthermore, the server collects visual materials from selected tourist facilities and automatically generates short videos using a generative AI model. These videos are designed to concisely convey the attractions of the facilities and are intended to be visually understandable to users. The generated videos are sent to the device and displayed in real time.

[0446] As a concrete example, consider a scenario where a user enters a prompt such as "a quiet cafe I can get to in the next hour." The server analyzes this prompt and identifies suitable cafes from its database based on the user's current location. The server evaluates the candidate cafes and presents them to the user in a ranking format. Furthermore, a short video about the selected cafe is generated and displayed on the device. This allows the user to intuitively get a feel for the cafe's atmosphere and efficiently decide where to visit.

[0447] This system allows users to easily plan high-quality travel experiences without having to process large amounts of information.

[0448] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0449] Step 1:

[0450] The server receives a request for tourist spot recommendations from the user's terminal. The input includes the user's current location, preferences, and a prompt message. The server uses this information as source data for database searches and analysis. Based on the user's request, it generates an appropriate query and performs a search on the tourist facility database.

[0451] Step 2:

[0452] The server searches a database of tourist attractions based on location and preferences, and extracts relevant candidates. The input for this step is the query obtained in the previous step. The server filters the facilities in the database that match the location and calculates a relevance score based on preferences to identify the most suitable facilities for the user. The output is a list of identified tourist attractions.

[0453] Step 3:

[0454] The server evaluates and generates rankings based on an extracted list of tourist attractions. A list of candidate tourist attractions is used as input. Evaluation criteria include ease of access, review ratings, and popularity, and a generative AI model is used to calculate a numerical evaluation score. Based on this, the server outputs a ranked list.

[0455] Step 4:

[0456] The server collects visual materials about top-ranked tourist attractions and generates short videos. The input consists of a rated ranking list and visual materials related to each attraction. The server utilizes a generation AI model to automatically generate videos combining visual materials and feature descriptions. The generated videos aim to effectively convey the attractions of the attractions. The output is the generated short video.

[0457] Step 5:

[0458] The server sends the generated short video to the user's device. The input is the completed short video file. The server transfers the video to the device using the appropriate communication protocol. The device receives the video and makes it available for real-time display to the user. The output is the display on the device.

[0459] By executing each step in sequence, users can make decisions about tourist attractions quickly and intuitively.

[0460] (Application Example 1)

[0461] 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."

[0462] When travelers select appropriate tourist destinations, they need to be able to quickly and personalizedly identify spots of interest without being overwhelmed by a vast amount of information. In particular, there is a lack of systems that recommend tourist destinations that reflect the user's location and individual preferences, and that visually convey the appeal of these destinations in an intuitively understandable way.

[0463] 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.

[0464] In this invention, the server includes means for searching for relevant tourist destinations using information based on the user's location and preferences; means for evaluating the searched tourist destinations based on ease of access, reviews, and popularity, and generating rankings; and means for automatically generating short videos that represent the characteristics of the tourist destinations based on the rankings. This makes it possible for users to efficiently find tourist spots that suit their interests while they are on location, and to more easily decide where to visit.

[0465] A "user" is an individual who attempts to obtain information about tourist destinations using the system.

[0466] "Location information" refers to data that indicates the user's current geographical location, and is primarily obtained using GPS.

[0467] "Preferences" refer to a user's personal tastes and interests, and are factors that influence their choice of tourist destinations.

[0468] A "tourist spot" is a geographical location or facility that visitors intend to visit, and is valued as a tourist resource.

[0469] "Search methods" refer to a system that includes a process of finding relevant tourist destinations from a database based on the user's location information and preferences.

[0470] "Evaluation" is the process of judging a tourist destination based on criteria such as ease of access, reviews, and popularity, and determining the value associated with these factors.

[0471] A "ranking" is a list of tourist destinations sorted according to priority based on evaluation results.

[0472] "Short videos" are automatically generated short-form visual content designed to intuitively convey the characteristics of tourist destinations.

[0473] "Automatic generation methods" refer to mechanisms in which a program executes a specific process and produces deliverables without human intervention.

[0474] A "user device" is an electronic device used by a user to receive or manipulate information, and generally includes smartphones and tablets.

[0475] "Real-time delivery methods" refer to systems that transmit generated content to user devices instantly and without delay for display.

[0476] An "information processing device" is a set of hardware and program structures that collect, analyze, and process data to provide users with valuable information.

[0477] The present invention's system efficiently searches for relevant tourist destinations based on the user's location information and preferences, and automatically generates and delivers short videos that intuitively showcase their appeal. This system is implemented using a server, a user device, and related software.

[0478] First, the device uses its GPS function to obtain highly accurate location information and sends it to the server. In addition to this, the server collects user preference data from past travel history data and social media. Using this data, the server searches a database of tourist destinations and evaluates them based on criteria such as ease of access, reviews, and popularity.

[0479] The evaluated tourist destinations are organized in a ranking format, and based on this ranking, libraries such as OpenCV are used to visualize the characteristics of the tourist destinations. The automatically generated short videos effectively incorporate visual materials and explanatory text of the tourist spots. Since these videos are immediately delivered to the user's device in real time, users can quickly decide on their destinations based on abundant information, even while they are at the location.

[0480] For example, if a user traveling requests a "park that can be enjoyed with children," this system can instantly search for parks near their current location, generate short videos of suitable parks based on evaluation information, and suggest them.

[0481] In generating the short video created in this way, a generation AI model is used, and an example of a prompt message used in that process is as follows:

[0482] "Please generate a short video suggesting parks in the surrounding area that are suitable for family use, based on the user's current location and preferences."

[0483] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0484] Step 1:

[0485] The device obtains its current location using GPS functionality. It uses GPS data from the user's device as input and sends the location information to the server. As output, the server can accurately determine the user's current location. Specifically, the device periodically acquires GPS data and sends it to the server via the internet.

[0486] Step 2:

[0487] The server collects preference data from past travel history and social media to understand user preferences. It collects and analyzes the user's past behavioral history and social media posts as input. The output is a profile of the user's interests and preferences. Specifically, the server retrieves past history from the database and extracts user preferences using text analysis techniques.

[0488] Step 3:

[0489] The server searches a tourist destination database based on location information and preference data. It uses the user's current location and preferences as input to extract matching tourist destinations from the database. The output generates a list of multiple related tourist spots. Specifically, the server uses database queries to efficiently find relevant tourist destinations.

[0490] Step 4:

[0491] The server evaluates a list of tourist destinations based on accessibility, reviews, and popularity. It uses an extracted list of tourist destinations and their associated information as input, ranking them according to evaluation criteria. The output is a ranking list based on these evaluations. Specifically, the server uses a point system to numerically evaluate each tourist destination and generates a ranking based on these evaluations.

[0492] Step 5:

[0493] The server automatically generates short videos that represent the characteristics of tourist destinations based on rankings, using the OpenCV library. It uses a ranking list of evaluated tourist destinations and visual materials as input, editing them to generate the short videos. The output is visual content introducing the characteristics of each tourist destination. Specifically, the server processes the visual materials using a video editing library and adds appropriate explanations to the videos using a generation AI model.

[0494] Step 6:

[0495] The server generates short video clips and delivers them to the user's device in real time. The generated visual content is used as input and sent to the user's device in streaming format. The output is that the user's device receives the video and makes it playable. Specifically, the server transmits data over the network, and the streaming player on the device displays the video.

[0496] A generative AI model is used, and an example of a prompt message would be, "Generate a short video suggesting parks in the surrounding area that are suitable for family use, based on your current location and preferences."

[0497] 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.

[0498] This invention relates to a tourism information provision system equipped with an emotion engine that recognizes the user's emotional state. The aim of this system is to reduce the burden of decision-making in selecting tourist destinations within the time available to the user and to provide a more personalized travel experience.

[0499] First, the user uses the device to input their desired criteria for choosing a tourist destination and their current mood. The device is equipped with sensors to capture the user's voice and facial expressions, which are then analyzed by an emotion engine. The emotion engine determines the user's current emotional state from the input data and generates emotion tags such as "happy" or "tired."

[0500] The server receives the current location information, user input data, and sentiment tags sent from the terminal, and searches the tourist destination database based on this information. As a result, tourist destinations that match the user's preferences and current sentiments are identified. The identified tourist destinations are then evaluated using additional evaluation criteria based on sentiment tags, and a ranking is generated.

[0501] Based on this ranking, highly-rated tourist destinations are automatically generated as short videos incorporating content tailored to emotional tags. For example, if a user wants to relax, videos of quiet cafes or places with beautiful scenery will be generated. These videos are delivered to the device, and users can watch them in real time.

[0502] As a concrete example, suppose a user is seeking a short break during a busy schedule, and the device receives a request for a "relaxing place." At this point, the emotion engine detects the user's calm facial expression and gentle tone of voice, and sets the emotion tag to "relaxed." The server then evaluates tourist destinations based on these conditions, ranks the best places for relaxation, and generates and provides corresponding videos to the device. In this way, users can quickly and smoothly find tourist destinations that match their emotional state.

[0503] The following describes the processing flow.

[0504] Step 1:

[0505] The user provides verbal or touch input to the device regarding their desired conditions and current mood. The device acquires the input data, as well as voice and facial expression data using its built-in camera and microphone.

[0506] Step 2:

[0507] The emotion engine built into the device analyzes acquired voice and facial expression data to determine the user's current emotional state. The determined emotional state is then converted into emotion tags such as "relaxed," "excited," and "fatigued."

[0508] Step 3:

[0509] The device sends user input data, generated emotion tags, and current location information to the server. This allows the server to receive information that provides a comprehensive understanding of the user's situation.

[0510] Step 4:

[0511] The server searches a tourist destination database based on the received information and extracts candidate tourist spots that correspond to the user's preferences and emotional tags. In this process, locations that are geographically close and that match the user's tastes are given priority.

[0512] Step 5:

[0513] The server evaluates the extracted candidates and generates rankings based on relevance derived from sentiment tags, in addition to reviews and ease of access. Each tourist destination receives a special evaluation that takes into account the user's emotional state.

[0514] Step 6:

[0515] The server automatically generates short videos incorporating visual elements and information related to emotion tags, based on the rankings. These videos include visuals that match the user's current emotional state.

[0516] Step 7:

[0517] The server delivers the generated short video to the terminal. The terminal displays the received video to the user, who can then select tourist destinations to visit based on it.

[0518] (Example 2)

[0519] 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."

[0520] In today's information-driven society, selecting the optimal tourist destination from numerous options is a significant burden for travelers and tourists. In this context, there is a need to provide personalized tourist information based on the current emotional state of each individual user. However, conventional systems have the drawback of failing to consider the user's emotions, resulting in merely providing information without any real substance.

[0521] 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.

[0522] In this invention, the server includes means for searching for relevant regions based on the user's current location, preferences, and emotional state; means for analyzing acquired voice and facial expression data to generate emotional tags; and means for evaluating the searched regions and generating rankings. This makes it possible to provide personalized tourist information tailored to the user's current emotional state.

[0523] "Users" refer to individuals who use the system to obtain tourist information and plan their trips.

[0524] "Current location" refers to information indicating the geographical location of the user while they are using the system.

[0525] "Preferences" refer to information that indicates the user's personal tastes and interests, and serve as an important criterion in selecting tourist destinations.

[0526] "Emotional state" refers to the user's emotions and psychological condition at that time, and is a factor used to recommend tourist destinations.

[0527] An "emotion tag" is a label that indicates a user's emotions, generated by an emotion engine that analyzes voice and facial expression data.

[0528] "Search method" refers to the function that allows the system to find relevant regions based on the user's location, preferences, and emotional state.

[0529] A "ranking" is a list that evaluates and prioritizes specific tourist destinations based on user information.

[0530] A "short video" is video content that visually conveys an overview of a tourist destination to users based on the generated rankings.

[0531] "Distribution method" refers to the technical function that transmits the generated video to the user's device and makes it viewable.

[0532] This invention relates to a tourism information provision system equipped with an emotion engine that recognizes the emotional state of the user. This system utilizes multiple hardware and software components to enhance natural dialogue and user experience.

[0533] First, the user uses a device to input their desired criteria for choosing a tourist destination. The device is equipped with sensors such as a microphone for voice recognition and a camera for facial recognition, which collect the user's voice and facial expressions in real time.

[0534] The collected data is sent to an emotion engine, which uses machine learning algorithms to perform sentiment analysis. For example, it uses frameworks such as "TensorFlow" or "PyTorch" to generate sentiment tags such as "relaxed" or "excited" from voice tone and facial expressions.

[0535] The server receives location information, preferences, and sentiment tags from the device. Based on this data, the server uses a search algorithm to scan a tourist destination database and identify the best location for the user. This database stores information on a large number of tourist destinations, and the system uses database management systems such as MySQL or PostgreSQL.

[0536] Subsequently, the server uses a ranking algorithm to compare the selected tourist destinations and prioritize presenting the most beneficial ones to the user. Based on the ranking, it automatically generates short videos. Media libraries such as "FFmpeg" are used for video generation.

[0537] The generated videos are delivered to the user's device, and the user can watch them in real time. For example, if a user requests a "relaxing place," the emotion engine generates an emotion tag of "relax," and based on this, videos of quiet cafes or places with beautiful scenery are recommended. An example of a prompt would be, "Please suggest a refreshing spot that suits my current mood."

[0538] This system has the ability to automate the suggestion of tourist destinations that align with the user's emotional state, thereby providing a more personalized travel experience.

[0539] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0540] Step 1:

[0541] The user operates the device to input criteria for selecting a tourist destination. This includes specifying the type of place they want to visit (e.g., park, museum) and the activities they wish to engage in. The device then prepares this information for transmission to the emotion engine. The input data is processed in text format.

[0542] Step 2:

[0543] The device uses its built-in sensors to acquire user voice and facial expression data. Voice data is collected from the microphone, and facial expression data from the camera. This data is sent in real time to an emotion engine to determine the user's current emotional state. The emotion engine uses this input data to run machine learning algorithms and outputs emotion tags such as "relaxed" and "happy."

[0544] Step 3:

[0545] The server receives the user's current location, desired criteria, and generated sentiment tags from the device. Based on the received information, the server queries a tourist destination database and retrieves a list of tourist destinations that match the criteria. The database search is performed using SQL queries, and the tourist destination data is output in list format. This process identifies tourist destinations that the user is likely to be interested in.

[0546] Step 4:

[0547] The server generates a ranking based on the acquired list of tourist destinations and sentiment tags. The ranking algorithm prioritizes each destination, taking into account its attributes (rating, ease of access, user sentiment, etc.). Through this process, the ranked tourist destinations are output again in list format. Users can receive suggestions for tourist destinations in an easy-to-select format.

[0548] Step 5:

[0549] The server automatically generates short videos tailored to the user's emotions, based on top-ranked tourist destinations. Using a media library, it edits photos and videos of tourist destinations and inserts music and text. This creates visually and aurally engaging content, which is then output as a video file.

[0550] Step 6:

[0551] The server delivers the generated video to the device. The device saves the received video in the appropriate format and makes it ready for immediate playback. Users can watch the video on their device and check detailed information about tourist destinations that match their interests. This allows users to obtain relevant travel destination information in real time.

[0552] (Application Example 2)

[0553] 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."

[0554] Current tourism information services have a challenge in that they do not adequately consider the individual emotional state of users, making it difficult to suggest the optimal tourism experience for each user. In particular, there is a lack of real-time suggestions for tourist destinations based on users' emotional tags, and the provision of personalized visual content.

[0555] 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.

[0556] In this invention, the server includes means for searching for relevant tourist destinations based on the user's current location, preferences, and emotional state; means for evaluating the searched tourist destinations and generating rankings; and means for automatically generating short videos tailored to emotional tags based on the rankings. This makes it possible to suggest optimal tourist destinations according to the user's emotional state and provide personalized short videos.

[0557] A "user" refers to an individual or group that uses the system and acts as a recipient of tourism information.

[0558] "Current location" refers to data that indicates the geographical information of the user's current location and serves as the basis for searching for tourist destinations.

[0559] "Preferences" refer to information that indicates a user's interests and preferences, and are used as an indicator when identifying tourist destinations.

[0560] "Emotional state" refers to the emotional response exhibited by the user, and is a psychological state determined from the voice and facial expressions acquired by the system.

[0561] A "tourist spot" refers to a geographical or cultural location that visitors can access and that aligns with the purpose of tourism.

[0562] A "ranking" is a list of tourist destinations selected by the system and arranged in order of highest rating, organized to be useful for recommending them to users.

[0563] "Emotional tags" are labels or identifiers used to describe a user's emotional state, and are useful information for suggesting tourism content.

[0564] "Short videos" refer to video content edited to allow viewers to see visual information related to tourist destinations in a short amount of time, and are structured to attract the viewer's interest.

[0565] A "user terminal" is an information-processing device carried by a user that has the function of receiving and displaying tourist information.

[0566] This invention is a system that provides tourist information based on the user's emotional state. The server receives emotional state, current location, and preference information from the user's terminal, searches for relevant tourist locations based on this information, and generates rankings.

[0567] Specifically, the system uses the camera and microphone on the user's device to capture their facial expressions and voice. This data is processed by an emotion analysis engine using OpenCV and TensorFlow, generating emotion tags that indicate the user's emotional state. These emotion tags, along with the user's current location and preferences, are sent to the server. The server uses Scikit-learn to execute an evaluation algorithm, generating a list of tourist destinations and creating a ranking. Furthermore, based on the ranking, it automatically generates short videos of the tourist destinations using a generative AI model. These videos are tailored to the user's emotions and can be viewed in real time. Template-based video editing technology is used to generate this visual content.

[0568] For example, if a user is in a calm mood and desires a relaxing sightseeing experience, the device will request "relaxing places." The server will then rank sightseeing locations suitable for this sentiment tag and generate videos featuring quiet cafes or beautiful scenery as backgrounds, which will be provided to the user. An example of a prompt to input into the generating AI model would be, "Based on the user's emotional state, 'relaxed,' please suggest recommended sightseeing spots." In this way, a personalized sightseeing experience tailored to the user's emotional state becomes possible.

[0569] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0570] Step 1:

[0571] The device activates its camera and microphone to capture the user's emotional state, collecting facial expression and audio data. Input is real-time video and audio data, while output is pre-processed images and audio signals. This data is then processed through noise reduction and format conversion to a format suitable for analysis.

[0572] Step 2:

[0573] The device uses pre-processed data to activate an emotion analysis engine. Here, OpenCV and TensorFlow are used to determine the user's emotional state from the acquired data and generate emotion tags. The input consists of pre-processed image and audio data, and the output is a tag representing the user's emotion (e.g., "relaxed"). This process includes facial recognition through image analysis and extraction and classification of audio features.

[0574] Step 3:

[0575] The device sends generated sentiment tags, current location information, and preference information to the server. The inputs are sentiment tags, geographic coordinates, and user preference data, and the output is a request to narrow down the list of tourist destination candidates. The purpose here is to aggregate the information that will serve as the basis for tourist destination searches and prepare the server for reception.

[0576] Step 4:

[0577] The server searches a tourist destination database based on the received information and applies a ranking algorithm to evaluate and select potential tourist destinations. Inputs include sentiment tags, user location, and preference information, while output is a ranked list of evaluated tourist destinations. Scikit-learn is used to assign scores that consider the popularity of the location and the user's past preferences.

[0578] Step 5:

[0579] The server generates short videos using template-based video editing technology based on a ranking list. Input consists of evaluated input data and visual material data of tourist destinations, and output is a personalized short video. A generation AI model is used to automatically synthesize content tailored to the user's emotions.

[0580] Step 6:

[0581] The server delivers the generated short video to the terminal, which the user watches in real time. The input is the generated video data, and the output is the video playback on the terminal. During playback, the user can watch the video and make decisions about their next action (e.g., visiting a tourist spot). At this stage, it is also possible to collect user experience feedback using prompt messages.

[0582] 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.

[0583] 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.

[0584] 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.

[0585] [Fourth Embodiment]

[0586] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0587] 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.

[0588] 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).

[0589] 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.

[0590] 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.

[0591] 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).

[0592] 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.

[0593] 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.

[0594] 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.

[0595] 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.

[0596] 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.

[0597] 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.

[0598] 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".

[0599] This invention is a system for quickly recommending tourist destinations suitable for users, and mainly consists of a server, terminals, and a user interface. This system utilizes the user's current location information and preferences to identify relevant tourist spots, ranks them, and automatically generates short videos that convey their appeal.

[0600] When the server receives a request from a user, it first searches a pre-prepared database of tourist spots using the user's location and preferences. This extracts potential tourist spots accessible from the user's current location. The extracted tourist spots are then evaluated by the server based on criteria such as ease of access, user reviews, and popularity. Based on this evaluation, a ranking is generated, which identifies the most suitable spots based on the user's interests.

[0601] Next, the server retrieves visual materials and related information for each tourist spot and automatically generates a short video based on them. This video condenses the characteristics and appeal of the tourist spot and is designed to be easily understood by the user. The video created in this way is sent to the user's device and displayed in real time.

[0602] For example, if a user is planning a sightseeing trip during limited free time on a weekday, they might enter a request via their device such as "a quiet cafe I can get to in under an hour." The server analyzes this information and provides a ranking of recommended spots that reflect the user's current location and cafe preferences. Based on this information, the server generates a concise and engaging short video, which is displayed on the device, allowing the user to quickly decide where to go.

[0603] This system eliminates the need for users to process vast amounts of information, allowing them to select their destination in a relaxed manner.

[0604] The following describes the processing flow.

[0605] Step 1:

[0606] The user uses their device to enter their current location along with a request for "a good Japanese restaurant I can get to within the next hour." The device retrieves this information and sends it to an available server.

[0607] Step 2:

[0608] The server analyzes the received data and searches a tourist destination database based on the user's current location and preferences. As a result, it extracts candidate restaurants that meet the specified criteria.

[0609] Step 3:

[0610] The server evaluates the extracted restaurant candidates based on multiple criteria, including how well they match preferences, ease of access, and user reviews. Based on this evaluation, it generates a ranking that prioritizes the candidate restaurants.

[0611] Step 4:

[0612] The server uses information from ranked restaurants to automatically generate engaging short videos by incorporating visual materials and descriptions for each restaurant.

[0613] Step 5:

[0614] The server sends the generated short videos to the user's device. The videos are sorted by ranking, making it easy for users to compare them.

[0615] Step 6:

[0616] The user reviews short videos received on their device and selects restaurants that interest them. Based on the selected information, the next action is determined.

[0617] (Example 1)

[0618] 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".

[0619] Conventional tourist destination recommendation systems struggled to select the most suitable tourist facilities based on the user's current location and preferences, requiring users to manually sift through a large amount of information. Furthermore, the lack of effective means for intuitively understanding the appeal of tourist facilities made it difficult to quickly decide on the best destination.

[0620] 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.

[0621] In this invention, the server includes means for searching for relevant tourist facilities based on the user's current location and preferences, means for evaluating the searched tourist facilities and generating rankings based on location and popularity, and means for generating short videos that convey the characteristics of the tourist facilities based on the rankings. This makes it possible for users to quickly find tourist facilities that are easily accessible from their current location and that interest them. Furthermore, through the generated short videos, users can intuitively grasp the appeal of the facilities and efficiently decide where to visit.

[0622] "Users" refer to individuals who use this system to search for tourist facilities and select their destinations through the interface.

[0623] "Current location information" refers to data indicating the geographical location obtained from the user's device.

[0624] "Preferences" refers to information about the user's preferences, including past preferences, interests, or pre-entered conditions.

[0625] "Tourist facilities" refer to tourist destinations and leisure facilities that users visit for their own purposes, and the database includes information about their location, characteristics, and popularity.

[0626] "Searching method" refers to the method or process used to identify tourist facilities that meet the specified criteria from a database.

[0627] "Means of evaluation" refers to the process of judging the value of search results for tourist facilities based on criteria such as ease of access, reviews, and popularity.

[0628] "Means for generating rankings" refers to the methods and processes for ranking and displaying tourist facilities based on evaluation results.

[0629] "Methods for generating short videos" refers to the process of editing images and videos to create short, viewable video formats in order to visually convey the characteristics of tourist facilities.

[0630] "Means for transmitting to a display device" refers to communication means or protocols for transmitting the generated short video to the user's device and making it viewable.

[0631] The system of this invention mainly consists of a server, terminals, and a user interface. These components are intended to provide users with efficient search and recommendation of tourist facilities.

[0632] The server receives data indicating the user's current location and information about their preferences, and uses this data to search a database of tourist facilities. The database contains detailed information about tourist facilities, including location, features, reviews, and popularity. The server uses this information and analyzes the data using a generative AI model to recommend appropriate facilities to the user.

[0633] The evaluation criteria for tourist facilities include ease of access, review ratings, and popularity. The server generates rankings based on the evaluation results, identifying the most suitable facilities for the user. This process significantly reduces the amount of information users need to search for themselves, helping them to intuitively select facilities.

[0634] Furthermore, the server collects visual materials from selected tourist facilities and automatically generates short videos using a generative AI model. These videos are designed to concisely convey the attractions of the facilities and are intended to be visually understandable to users. The generated videos are sent to the device and displayed in real time.

[0635] As a concrete example, consider a scenario where a user enters a prompt such as "a quiet cafe I can get to in the next hour." The server analyzes this prompt and identifies suitable cafes from its database based on the user's current location. The server evaluates the candidate cafes and presents them to the user in a ranking format. Furthermore, a short video about the selected cafe is generated and displayed on the device. This allows the user to intuitively get a feel for the cafe's atmosphere and efficiently decide where to visit.

[0636] This system allows users to easily plan high-quality travel experiences without having to process large amounts of information.

[0637] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0638] Step 1:

[0639] The server receives a request for tourist spot recommendations from the user's terminal. The input includes the user's current location, preferences, and a prompt message. The server uses this information as source data for database searches and analysis. Based on the user's request, it generates an appropriate query and performs a search on the tourist facility database.

[0640] Step 2:

[0641] The server searches a database of tourist attractions based on location and preferences, and extracts relevant candidates. The input for this step is the query obtained in the previous step. The server filters the facilities in the database that match the location and calculates a relevance score based on preferences to identify the most suitable facilities for the user. The output is a list of identified tourist attractions.

[0642] Step 3:

[0643] The server evaluates and generates rankings based on an extracted list of tourist attractions. A list of candidate tourist attractions is used as input. Evaluation criteria include ease of access, review ratings, and popularity, and a generative AI model is used to calculate a numerical evaluation score. Based on this, the server outputs a ranked list.

[0644] Step 4:

[0645] The server collects visual materials about top-ranked tourist attractions and generates short videos. The input consists of a rated ranking list and visual materials related to each attraction. The server utilizes a generation AI model to automatically generate videos combining visual materials and feature descriptions. The generated videos aim to effectively convey the attractions of the attractions. The output is the generated short video.

[0646] Step 5:

[0647] The server sends the generated short video to the user's device. The input is the completed short video file. The server transfers the video to the device using the appropriate communication protocol. The device receives the video and makes it available for real-time display to the user. The output is the display on the device.

[0648] By executing each step in sequence, users can make decisions about tourist attractions quickly and intuitively.

[0649] (Application Example 1)

[0650] 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".

[0651] When travelers select appropriate tourist destinations, they need to be able to quickly and personalizedly identify spots of interest without being overwhelmed by a vast amount of information. In particular, there is a lack of systems that recommend tourist destinations that reflect the user's location and individual preferences, and that visually convey the appeal of these destinations in an intuitively understandable way.

[0652] 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.

[0653] In this invention, the server includes means for searching for relevant tourist destinations using information based on the user's location and preferences; means for evaluating the searched tourist destinations based on ease of access, reviews, and popularity, and generating rankings; and means for automatically generating short videos that represent the characteristics of the tourist destinations based on the rankings. This makes it possible for users to efficiently find tourist spots that suit their interests while they are on location, and to more easily decide where to visit.

[0654] A "user" is an individual who attempts to obtain information about tourist destinations using the system.

[0655] "Location information" refers to data that indicates the user's current geographical location, and is primarily obtained using GPS.

[0656] "Preferences" refer to a user's personal tastes and interests, and are factors that influence their choice of tourist destinations.

[0657] A "tourist spot" is a geographical location or facility that visitors intend to visit, and is valued as a tourist resource.

[0658] "Search methods" refer to a system that includes a process of finding relevant tourist destinations from a database based on the user's location information and preferences.

[0659] "Evaluation" is the process of judging a tourist destination based on criteria such as ease of access, reviews, and popularity, and determining the value associated with these factors.

[0660] A "ranking" is a list of tourist destinations sorted according to priority based on evaluation results.

[0661] "Short videos" are automatically generated short-form visual content designed to intuitively convey the characteristics of tourist destinations.

[0662] "Automatic generation methods" refer to mechanisms in which a program executes a specific process and produces deliverables without human intervention.

[0663] A "user device" is an electronic device used by a user to receive or manipulate information, and generally includes smartphones and tablets.

[0664] "Real-time delivery methods" refer to systems that transmit generated content to user devices instantly and without delay for display.

[0665] An "information processing device" is a set of hardware and program structures that collect, analyze, and process data to provide users with valuable information.

[0666] The present invention's system efficiently searches for relevant tourist destinations based on the user's location information and preferences, and automatically generates and delivers short videos that intuitively showcase their appeal. This system is implemented using a server, a user device, and related software.

[0667] First, the device uses its GPS function to obtain highly accurate location information and sends it to the server. In addition to this, the server collects user preference data from past travel history data and social media. Using this data, the server searches a database of tourist destinations and evaluates them based on criteria such as ease of access, reviews, and popularity.

[0668] The evaluated tourist destinations are organized in a ranking format, and based on this ranking, libraries such as OpenCV are used to visualize the characteristics of the tourist destinations. The automatically generated short videos effectively incorporate visual materials and explanatory text of the tourist spots. Since these videos are immediately delivered to the user's device in real time, users can quickly decide on their destinations based on abundant information, even while they are at the location.

[0669] For example, if a user traveling requests a "park that can be enjoyed with children," this system can instantly search for parks near their current location, generate short videos of suitable parks based on evaluation information, and suggest them.

[0670] In generating the short video created in this way, a generation AI model is used, and an example of a prompt message used in that process is as follows:

[0671] "Please generate a short video suggesting parks in the surrounding area that are suitable for family use, based on the user's current location and preferences."

[0672] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0673] Step 1:

[0674] The device obtains its current location using GPS functionality. It uses GPS data from the user's device as input and sends the location information to the server. As output, the server can accurately determine the user's current location. Specifically, the device periodically acquires GPS data and sends it to the server via the internet.

[0675] Step 2:

[0676] The server collects preference data from past travel history and social media to understand user preferences. It collects and analyzes the user's past behavioral history and social media posts as input. The output is a profile of the user's interests and preferences. Specifically, the server retrieves past history from the database and extracts user preferences using text analysis techniques.

[0677] Step 3:

[0678] The server searches a tourist destination database based on location information and preference data. It uses the user's current location and preferences as input to extract matching tourist destinations from the database. The output generates a list of multiple related tourist spots. Specifically, the server uses database queries to efficiently find relevant tourist destinations.

[0679] Step 4:

[0680] The server evaluates a list of tourist destinations based on accessibility, reviews, and popularity. It uses an extracted list of tourist destinations and their associated information as input, ranking them according to evaluation criteria. The output is a ranking list based on these evaluations. Specifically, the server uses a point system to numerically evaluate each tourist destination and generates a ranking based on these evaluations.

[0681] Step 5:

[0682] The server automatically generates short videos that represent the characteristics of tourist destinations based on rankings, using the OpenCV library. It uses a ranking list of evaluated tourist destinations and visual materials as input, editing them to generate the short videos. The output is visual content introducing the characteristics of each tourist destination. Specifically, the server processes the visual materials using a video editing library and adds appropriate explanations to the videos using a generation AI model.

[0683] Step 6:

[0684] The server generates short video clips and delivers them to the user's device in real time. The generated visual content is used as input and sent to the user's device in streaming format. The output is that the user's device receives the video and makes it playable. Specifically, the server transmits data over the network, and the streaming player on the device displays the video.

[0685] A generative AI model is used, and an example of a prompt message would be, "Generate a short video suggesting parks in the surrounding area that are suitable for family use, based on your current location and preferences."

[0686] 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.

[0687] This invention relates to a tourism information provision system equipped with an emotion engine that recognizes the user's emotional state. The aim of this system is to reduce the burden of decision-making in selecting tourist destinations within the time available to the user and to provide a more personalized travel experience.

[0688] First, the user uses the device to input their desired criteria for choosing a tourist destination and their current mood. The device is equipped with sensors to capture the user's voice and facial expressions, which are then analyzed by an emotion engine. The emotion engine determines the user's current emotional state from the input data and generates emotion tags such as "happy" or "tired."

[0689] The server receives the current location information, user input data, and sentiment tags sent from the terminal, and searches the tourist destination database based on this information. As a result, tourist destinations that match the user's preferences and current sentiments are identified. The identified tourist destinations are then evaluated using additional evaluation criteria based on sentiment tags, and a ranking is generated.

[0690] Based on this ranking, highly-rated tourist destinations are automatically generated as short videos incorporating content tailored to emotional tags. For example, if a user wants to relax, videos of quiet cafes or places with beautiful scenery will be generated. These videos are delivered to the device, and users can watch them in real time.

[0691] As a concrete example, suppose a user is seeking a short break during a busy schedule, and the device receives a request for a "relaxing place." At this point, the emotion engine detects the user's calm facial expression and gentle tone of voice, and sets the emotion tag to "relaxed." The server then evaluates tourist destinations based on these conditions, ranks the best places for relaxation, and generates and provides corresponding videos to the device. In this way, users can quickly and smoothly find tourist destinations that match their emotional state.

[0692] The following describes the processing flow.

[0693] Step 1:

[0694] The user provides verbal or touch input to the device regarding their desired conditions and current mood. The device acquires the input data, as well as voice and facial expression data using its built-in camera and microphone.

[0695] Step 2:

[0696] The emotion engine built into the device analyzes acquired voice and facial expression data to determine the user's current emotional state. The determined emotional state is then converted into emotion tags such as "relaxed," "excited," and "fatigued."

[0697] Step 3:

[0698] The device sends user input data, generated emotion tags, and current location information to the server. This allows the server to receive information that provides a comprehensive understanding of the user's situation.

[0699] Step 4:

[0700] The server searches a tourist destination database based on the received information and extracts candidate tourist spots that correspond to the user's preferences and emotional tags. In this process, locations that are geographically close and that match the user's tastes are given priority.

[0701] Step 5:

[0702] The server evaluates the extracted candidates and generates rankings based on relevance derived from sentiment tags, in addition to reviews and ease of access. Each tourist destination receives a special evaluation that takes into account the user's emotional state.

[0703] Step 6:

[0704] The server automatically generates short videos incorporating visual elements and information related to emotion tags, based on the rankings. These videos include visuals that match the user's current emotional state.

[0705] Step 7:

[0706] The server delivers the generated short video to the terminal. The terminal displays the received video to the user, who can then select tourist destinations to visit based on it.

[0707] (Example 2)

[0708] 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".

[0709] In today's information-driven society, selecting the optimal tourist destination from numerous options is a significant burden for travelers and tourists. In this context, there is a need to provide personalized tourist information based on the current emotional state of each individual user. However, conventional systems have the drawback of failing to consider the user's emotions, resulting in merely providing information without any real substance.

[0710] 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.

[0711] In this invention, the server includes means for searching for relevant regions based on the user's current location, preferences, and emotional state; means for analyzing acquired voice and facial expression data to generate emotional tags; and means for evaluating the searched regions and generating rankings. This makes it possible to provide personalized tourist information tailored to the user's current emotional state.

[0712] "Users" refer to individuals who use the system to obtain tourist information and plan their trips.

[0713] "Current location" refers to information indicating the geographical location of the user while they are using the system.

[0714] "Preferences" refer to information that indicates the user's personal tastes and interests, and serve as an important criterion in selecting tourist destinations.

[0715] "Emotional state" refers to the user's emotions and psychological condition at that time, and is a factor used to recommend tourist destinations.

[0716] An "emotion tag" is a label that indicates a user's emotions, generated by an emotion engine that analyzes voice and facial expression data.

[0717] "Search method" refers to the function that allows the system to find relevant regions based on the user's location, preferences, and emotional state.

[0718] A "ranking" is a list that evaluates and prioritizes specific tourist destinations based on user information.

[0719] A "short video" is video content that visually conveys an overview of a tourist destination to users based on the generated rankings.

[0720] "Distribution method" refers to the technical function that transmits the generated video to the user's device and makes it viewable.

[0721] This invention relates to a tourism information provision system equipped with an emotion engine that recognizes the emotional state of the user. This system utilizes multiple hardware and software components to enhance natural dialogue and user experience.

[0722] First, the user uses a device to input their desired criteria for choosing a tourist destination. The device is equipped with sensors such as a microphone for voice recognition and a camera for facial recognition, which collect the user's voice and facial expressions in real time.

[0723] The collected data is sent to an emotion engine, which uses machine learning algorithms to perform sentiment analysis. For example, it uses frameworks such as "TensorFlow" or "PyTorch" to generate sentiment tags such as "relaxed" or "excited" from voice tone and facial expressions.

[0724] The server receives location information, preferences, and sentiment tags from the device. Based on this data, the server uses a search algorithm to scan a tourist destination database and identify the best location for the user. This database stores information on a large number of tourist destinations, and the system uses database management systems such as MySQL or PostgreSQL.

[0725] Subsequently, the server uses a ranking algorithm to compare the selected tourist destinations and prioritize presenting the most beneficial ones to the user. Based on the ranking, it automatically generates short videos. Media libraries such as "FFmpeg" are used for video generation.

[0726] The generated videos are delivered to the user's device, and the user can watch them in real time. For example, if a user requests a "relaxing place," the emotion engine generates an emotion tag of "relax," and based on this, videos of quiet cafes or places with beautiful scenery are recommended. An example of a prompt would be, "Please suggest a refreshing spot that suits my current mood."

[0727] This system has the ability to automate the suggestion of tourist destinations that align with the user's emotional state, thereby providing a more personalized travel experience.

[0728] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0729] Step 1:

[0730] The user operates the device to input criteria for selecting a tourist destination. This includes specifying the type of place they want to visit (e.g., park, museum) and the activities they wish to engage in. The device then prepares this information for transmission to the emotion engine. The input data is processed in text format.

[0731] Step 2:

[0732] The device uses its built-in sensors to acquire user voice and facial expression data. Voice data is collected from the microphone, and facial expression data from the camera. This data is sent in real time to an emotion engine to determine the user's current emotional state. The emotion engine uses this input data to run machine learning algorithms and outputs emotion tags such as "relaxed" and "happy."

[0733] Step 3:

[0734] The server receives the user's current location, desired criteria, and generated sentiment tags from the device. Based on the received information, the server queries a tourist destination database and retrieves a list of tourist destinations that match the criteria. The database search is performed using SQL queries, and the tourist destination data is output in list format. This process identifies tourist destinations that the user is likely to be interested in.

[0735] Step 4:

[0736] The server generates a ranking based on the acquired list of tourist destinations and sentiment tags. The ranking algorithm prioritizes each destination, taking into account its attributes (rating, ease of access, user sentiment, etc.). Through this process, the ranked tourist destinations are output again in list format. Users can receive suggestions for tourist destinations in an easy-to-select format.

[0737] Step 5:

[0738] The server automatically generates short videos tailored to the user's emotions, based on top-ranked tourist destinations. Using a media library, it edits photos and videos of tourist destinations and inserts music and text. This creates visually and aurally engaging content, which is then output as a video file.

[0739] Step 6:

[0740] The server delivers the generated video to the device. The device saves the received video in the appropriate format and makes it ready for immediate playback. Users can watch the video on their device and check detailed information about tourist destinations that match their interests. This allows users to obtain relevant travel destination information in real time.

[0741] (Application Example 2)

[0742] 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".

[0743] Current tourism information services have a challenge in that they do not adequately consider the individual emotional state of users, making it difficult to suggest the optimal tourism experience for each user. In particular, there is a lack of real-time suggestions for tourist destinations based on users' emotional tags, and the provision of personalized visual content.

[0744] 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.

[0745] In this invention, the server includes means for searching for relevant tourist destinations based on the user's current location, preferences, and emotional state; means for evaluating the searched tourist destinations and generating rankings; and means for automatically generating short videos tailored to emotional tags based on the rankings. This makes it possible to suggest optimal tourist destinations according to the user's emotional state and provide personalized short videos.

[0746] A "user" refers to an individual or group that uses the system and acts as a recipient of tourism information.

[0747] "Current location" refers to data that indicates the geographical information of the user's current location and serves as the basis for searching for tourist destinations.

[0748] "Preferences" refer to information that indicates a user's interests and preferences, and are used as an indicator when identifying tourist destinations.

[0749] "Emotional state" refers to the emotional response exhibited by the user, and is a psychological state determined from the voice and facial expressions acquired by the system.

[0750] A "tourist spot" refers to a geographical or cultural location that visitors can access and that aligns with the purpose of tourism.

[0751] A "ranking" is a list of tourist destinations selected by the system and arranged in order of highest rating, organized to be useful for recommending them to users.

[0752] "Emotional tags" are labels or identifiers used to describe a user's emotional state, and are useful information for suggesting tourism content.

[0753] "Short videos" refer to video content edited to allow viewers to see visual information related to tourist destinations in a short amount of time, and are structured to attract the viewer's interest.

[0754] A "user terminal" is an information-processing device carried by a user that has the function of receiving and displaying tourist information.

[0755] This invention is a system that provides tourist information based on the user's emotional state. The server receives emotional state, current location, and preference information from the user's terminal, searches for relevant tourist locations based on this information, and generates rankings.

[0756] Specifically, the system uses the camera and microphone on the user's device to capture their facial expressions and voice. This data is processed by an emotion analysis engine using OpenCV and TensorFlow, generating emotion tags that indicate the user's emotional state. These emotion tags, along with the user's current location and preferences, are sent to the server. The server uses Scikit-learn to execute an evaluation algorithm, generating a list of tourist destinations and creating a ranking. Furthermore, based on the ranking, it automatically generates short videos of the tourist destinations using a generative AI model. These videos are tailored to the user's emotions and can be viewed in real time. Template-based video editing technology is used to generate this visual content.

[0757] For example, if a user is in a calm mood and desires a relaxing sightseeing experience, the device will request "relaxing places." The server will then rank sightseeing locations suitable for this sentiment tag and generate videos featuring quiet cafes or beautiful scenery as backgrounds, which will be provided to the user. An example of a prompt to input into the generating AI model would be, "Based on the user's emotional state, 'relaxed,' please suggest recommended sightseeing spots." In this way, a personalized sightseeing experience tailored to the user's emotional state becomes possible.

[0758] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0759] Step 1:

[0760] The device activates its camera and microphone to capture the user's emotional state, collecting facial expression and audio data. Input is real-time video and audio data, while output is pre-processed images and audio signals. This data is then processed through noise reduction and format conversion to a format suitable for analysis.

[0761] Step 2:

[0762] The device uses pre-processed data to activate an emotion analysis engine. Here, OpenCV and TensorFlow are used to determine the user's emotional state from the acquired data and generate emotion tags. The input consists of pre-processed image and audio data, and the output is a tag representing the user's emotion (e.g., "relaxed"). This process includes facial recognition through image analysis and extraction and classification of audio features.

[0763] Step 3:

[0764] The device sends generated sentiment tags, current location information, and preference information to the server. The inputs are sentiment tags, geographic coordinates, and user preference data, and the output is a request to narrow down the list of tourist destination candidates. The purpose here is to aggregate the information that will serve as the basis for tourist destination searches and prepare the server for reception.

[0765] Step 4:

[0766] The server searches a tourist destination database based on the received information and applies a ranking algorithm to evaluate and select potential tourist destinations. Inputs include sentiment tags, user location, and preference information, while output is a ranked list of evaluated tourist destinations. Scikit-learn is used to assign scores that consider the popularity of the location and the user's past preferences.

[0767] Step 5:

[0768] The server generates short videos using template-based video editing technology based on a ranking list. Input consists of evaluated input data and visual material data of tourist destinations, and output is a personalized short video. A generation AI model is used to automatically synthesize content tailored to the user's emotions.

[0769] Step 6:

[0770] The server delivers the generated short video to the terminal, which the user watches in real time. The input is the generated video data, and the output is the video playback on the terminal. During playback, the user can watch the video and make decisions about their next action (e.g., visiting a tourist spot). At this stage, it is also possible to collect user experience feedback using prompt messages.

[0771] 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.

[0772] 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.

[0773] 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.

[0774] 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.

[0775] 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.

[0776] 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.

[0777] 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.

[0778] 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.

[0779] 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."

[0780] 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.

[0781] 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.

[0782] 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.

[0783] 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.

[0784] 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.

[0785] 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.

[0786] 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.

[0787] 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.

[0788] 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.

[0789] 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.

[0790] 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.

[0791] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0792] The following is further disclosed regarding the embodiments described above.

[0793] (Claim 1)

[0794] A means of searching for relevant tourist destinations based on the user's current location and preferences,

[0795] A means of evaluating searched tourist destinations and generating rankings,

[0796] A means for automatically generating short videos based on the aforementioned ranking,

[0797] A means of distributing the generated video to the user's terminal,

[0798] A system that includes this.

[0799] (Claim 2)

[0800] The system according to claim 1, which takes into account reviews and ease of access in evaluating tourist destinations.

[0801] (Claim 3)

[0802] The system according to claim 1, which combines visual materials of tourist locations and explanatory text in the aforementioned short video.

[0803] "Example 1"

[0804] (Claim 1)

[0805] A means of searching for relevant tourist facilities based on the user's current location and preferences,

[0806] A means of evaluating searched tourist facilities and generating rankings based on location information and popularity,

[0807] A means for generating a short video that conveys the characteristics of a tourist facility based on the aforementioned ranking,

[0808] A means for transmitting the generated video to the user's display device,

[0809] A system that includes this.

[0810] (Claim 2)

[0811] The system according to claim 1, which takes into account reviews, geographical distance, and ease of access in evaluating tourist facilities.

[0812] (Claim 3)

[0813] The system according to claim 1, which combines visual materials and explanatory information of a tourist facility in the aforementioned short video.

[0814] "Application Example 1"

[0815] (Claim 1)

[0816] A means of searching for relevant tourist destinations using information based on the user's location and preferences,

[0817] A means for evaluating searched tourist destinations based on accessibility, reviews, and popularity, and generating rankings,

[0818] A means for automatically generating short videos that express the characteristics of tourist destinations based on the aforementioned ranking,

[0819] A means of delivering the generated video to the user's device in real time,

[0820] Information processing device including

[0821] (Claim 2)

[0822] The information processing device according to claim 1, which provides an individualized ranking in the evaluation of tourist destinations, taking into account past tourist history and online data.

[0823] (Claim 3)

[0824] The information processing device according to claim 1, which combines visual materials of tourist locations, descriptive text, and evaluation information in the aforementioned short video to facilitate intuitive understanding for the user.

[0825] "Example 2 of combining an emotion engine"

[0826] (Claim 1)

[0827] A means of searching for relevant regions based on the user's current location, preferences, and emotional state,

[0828] A means for analyzing acquired audio and facial expression data and generating emotion tags,

[0829] A means of evaluating the searched region and generating a ranking,

[0830] Based on the aforementioned ranking, a means for automatically generating short videos that match emotion tags,

[0831] A means of delivering the generated video to the user's device,

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, which takes into account reviews, accessibility, and sentiment tags in evaluating tourist destinations.

[0835] (Claim 3)

[0836] The system according to claim 1, which combines local visual materials, descriptive text, and music corresponding to emotions in the aforementioned short video.

[0837] "Application example 2 when combining with an emotional engine"

[0838] (Claim 1)

[0839] A means of searching for relevant tourist destinations based on the user's current location, preferences, and emotional state,

[0840] A means of evaluating searched tourist destinations and generating rankings,

[0841] A means for automatically generating short videos that match emotion tags based on the aforementioned ranking,

[0842] A means of distributing the generated video to the user's device and making it viewable in real time,

[0843] A system that includes this.

[0844] (Claim 2)

[0845] The system according to claim 1, which takes into account user sentiment tags and reviews, and ease of access, when evaluating tourist destinations.

[0846] (Claim 3)

[0847] The system according to claim 1, wherein the short video combines visual materials of tourist locations with descriptive text based on the user's emotions. [Explanation of symbols]

[0848] 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 searching for relevant tourist destinations based on the user's current location and preferences, A means of evaluating searched tourist destinations and generating rankings, A means for automatically generating short videos based on the aforementioned ranking, A means of distributing the generated video to the user's terminal, A system that includes this.

2. The system according to claim 1, which takes into account reviews and ease of access when evaluating tourist destinations.

3. The system according to claim 1, which combines visual materials of tourist locations and explanatory text in the aforementioned short video.

Images