System

Abstract

A system is provided.SOLUTION: A system comprising: a server that proposes an optimal photographing composition based on evaluation data of a user stored in a terminal and trend information of a destination; a drone that automatically adjusts a flight position and an angle of a camera based on the photographing composition proposed by the server; and a terminal that instructs the drone to perform photographing.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In today's world, taking photos while traveling has become a very important activity for many people. However, taking great photos requires determining the right composition and angle, which takes time and effort. Furthermore, when traveling with a large group, people often have to take turns taking photos, which can waste time and disrupt the rhythm of the trip. There is a need for a solution to these issues and enable smooth, high-quality photography. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following system. Specifically, it uses a server that proposes optimal photo compositions based on user evaluation data stored on a terminal and trend information for the destination. It also uses a drone that automatically adjusts its flight position and camera angle based on the photo composition proposed by the server. Furthermore, by configuring a system that includes a terminal that issues shooting instructions to the drone, users can take efficient, high-quality photos. This system significantly reduces the time and effort required for taking photos while traveling, further enhancing the enjoyment of traveling.

[0006] A "terminal" is a portable electronic device that can be operated by a user and has the function of communicating with a drone and issuing shooting instructions.

[0007] A "server" is a computer system that is connected via a network and provides data and performs calculations in response to requests from terminals.

[0008] A "user" is a person who operates a terminal and takes photographs using a drone.

[0009] "Rating data" refers to data relating to photos and media content that users have rated in the past, and is data that reflects the user's preferences and tendencies.

[0010] "Trend information" refers to the latest information that is widely shared and appreciated, as well as information about popular compositions and photo spots at specific times and places.

[0011] "Photography composition" refers to the layout of a photograph that combines elements such as the subject's position, background, and viewpoint.

[0012] A "drone" is an unmanned aerial vehicle that can fly remotely or autonomously and is equipped with a camera to take photographs and videos.

[0013] A "flight position" is a position in the air where a drone can stay at a specific location, indicating the best place for filming.

[0014] "Angle" refers to the direction and tilt of the camera mounted on the drone, and is an element that can be adjusted to achieve the optimal shooting composition. [Brief explanation of the drawings]

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

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

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

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

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

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

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

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

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

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

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

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

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

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

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

[0036] As an embodiment of the present invention, a travel photography system using a terminal, a server, and a drone will be described. This system automatically proposes optimal photo compositions based on user evaluation data and destination trend information, and the drone automatically takes photos based on the proposed compositions.

[0037] System configuration

[0038] 1. Device: The user operates a device such as a smartphone or tablet. A dedicated app for controlling the drone is installed on this device. The device's role is to obtain evaluation data and trend information from the server and send it to the drone.

[0039] 2. Server: The server is installed on the cloud and stores and analyzes user evaluation data. It also collects trend information for destinations (e.g., tourist spots) and calculates the optimal shooting composition based on the analysis results.

[0040] 3. Drone: The drone is equipped with a camera and automatically adjusts its flight position and camera angle based on the composition suggested by the server. It also automatically takes photos, performs basic editing, and transfers the photos to the device.

[0041] Program processing overview

[0042] Drone launch and data synchronization

[0043] The user activates the drone and pairs it with a smartphone (terminal). The terminal synchronizes and transmits the user's evaluation data and destination trend information from the server to the drone.

[0044] Obtaining location information and setting destination

[0045] When the user approaches the destination, the device acquires the current location using GPS. The device sends the current location information to the drone, and the server displays a list of photo spots based on the destination. The user selects a photo spot.

[0046] Preparation for shooting and composition suggestions

[0047] The server calculates the optimal composition based on the evaluation data and trend information, and transmits this information to the drone via the device. The drone then sets the appropriate flight position and angle based on the proposed composition.

[0048] Automated shooting and editing

[0049] When the user presses the camera button on the device, the drone takes a photo with the specified composition. After taking the photo, the drone performs basic editing (adjusting brightness, applying filters, etc.) and transfers the photo to the device. The user can then view the photo on the device, make further edits, or share it on social media.

[0050] Specific examples

[0051] For example, when a user visits the Eiffel Tower in Paris, they start up the drone and pair it with their device. The device uses GPS to obtain the user's current location and sends it to the drone. The server calculates the optimal composition for taking a photo of the Eiffel Tower (e.g., "a full-body photo with the Eiffel Tower in the background") based on evaluation data and trend information. This information is sent to the drone via the device, and the drone moves to the appropriate position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, performs basic editing, and transfers it to the device. The user can review the photo, edit it if necessary, and share it with friends.

[0052] This system allows users to reduce the time it takes to take individual photos and easily obtain higher quality photos, which increases the enjoyment of travel and improves user satisfaction.

[0053] The processing flow will be explained below.

[0054] Step 1:

[0055] The user starts the drone and pairs it with the smartphone (device), which then launches a dedicated app and connects to the drone via Bluetooth or Wi-Fi.

[0056] Step 2:

[0057] The device sends the user's rating data (such as photos and videos that they have "liked" in the past) to the server, which receives and analyzes this data.

[0058] Step 3:

[0059] The server analyzes the evaluation data to understand the user's preferences and photography trends, and then collects and analyzes trend information for the destination (popular photo spots and composition).

[0060] Step 4:

[0061] When the user arrives at their travel destination (e.g., the Eiffel Tower), the device uses GPS to obtain their current location, which is then transmitted to the drone, which then sends the information to the server.

[0062] Step 5:

[0063] The server calculates the optimal composition based on the user's current location, rating data, and trend information. For example, it suggests a photo with the Eiffel Tower in the background or a composition shot from a specific angle.

[0064] Step 6:

[0065] The server calculates the composition and sends it to the drone via the device, which then automatically sets the appropriate flight position and camera angle based on the proposed composition.

[0066] Step 7:

[0067] The user operates the shooting instruction button on the device to send a command to the drone to start shooting, and the drone takes a photo with the specified composition.

[0068] Step 8:

[0069] After the drone captures the footage, it performs some basic editing (adjusting brightness, applying filters, etc.) automatically using internal image processing algorithms.

[0070] Step 9:

[0071] The drone then transfers the edited photos to the device, where the user can review them and make further edits if necessary.

[0072] Step 10:

[0073] Finally, users can share the edited photos with friends via social media or email. This process allows users to efficiently and easily obtain high-quality photos.

[0074] Example 1

[0075] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0076] When traveling and visiting beautiful landscapes and famous places, there is a demand for easy, high-quality photos with optimal composition, but this can be a difficult task for users without photography skills. Another problem is that the time spent taking photos reduces the time available to enjoy sightseeing. Furthermore, taking photos using drones requires technical operations that are difficult for average users to operate. There is a demand for a system that solves these problems and allows anyone to easily take high-quality photos.

[0077] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0078] In this invention, the server includes a means for suggesting optimal photo compositions based on user evaluation data stored in the terminal and trend information for destinations, a means for analyzing data on photos that the user has previously liked and rated, and a means for acquiring current location information using a GPS function and generating a list of photo spots, thereby enabling users to easily take high-quality, memorable photos while minimizing the amount of work required.

[0079] The "information processing device" is a computer system that has the function of proposing optimal photographic compositions based on user evaluation data and trend information about destinations.

[0080] An "unmanned aerial vehicle" is a device that automatically adjusts the flight position and camera angle based on the shooting composition proposed by the server, and takes and edits photographs.

[0081] An "information terminal device" is a device operated by a user to instruct an unmanned aerial vehicle to take photos and obtain current location information via GPS, and includes smartphones, tablets, and the like.

[0082] "User evaluation data" refers to data relating to photos taken by the user in the past, evaluations made by the user, and preferences.

[0083] "Trending information" is information about the general popularity or current topics of a particular destination.

[0084] "Photography composition" refers to the photographic conditions, such as the subject placement, camera angle, and focal length, when taking a photograph.

[0085] "GPS function" refers to technology that uses the Global Positioning System to obtain current latitude and longitude location information.

[0086] A "generative AI model" is a model that uses artificial intelligence algorithms to generate new shooting compositions and data patterns.

[0087] The "photography spot list" is a list of multiple candidate photo shooting locations that the server proposes based on the user's current location information.

[0088] "Basic editing" refers to the process of performing basic image processing on photographs, such as adjusting brightness and applying filters.

[0089] As an embodiment of the present invention, a system for enabling a user to take optimal photographs while traveling will be described. This system is configured using an information processing device (server), an information terminal device (terminal), and an unmanned aerial vehicle (drone).

[0090] First, the user activates the drone at their travel destination and pairs it with the device using a dedicated app. The device then connects to an information processing device and obtains the user's evaluation data and trend information for the destination. This evaluation data and trend information are stored in the cloud database of the information processing device.

[0091] Next, the terminal acquires the user's current location using its GPS function and sends it to the information processing device. The information processing device generates a photo spot list based on the acquired current location information and sends it to the user's terminal. The user selects a spot they want to take a photo from the photo spot list displayed on the terminal.

[0092] The information processing device uses a generative AI model to propose the optimal composition for the shot. The proposed composition is then sent to the drone via the device. The drone then automatically sets its flight position and camera angle based on the proposed composition.

[0093] When the user presses the shooting button on the dedicated app, the drone takes a photo with the specified composition. After taking the photo, the drone performs basic editing (adjusting brightness, applying filters, etc.) and transfers the edited photo to the device. The user can then review the transferred photo, make further edits as needed, or share it on social media.

[0094] For example, when a user visits the Eiffel Tower in Paris, they start up the drone and pair it with the device. The device uses GPS to obtain the user's current location and sends it to the information processing device. The information processing device calculates the optimal composition for taking a photo of the Eiffel Tower (e.g., "a full-body photo with the Eiffel Tower in the background") based on evaluation data and trend information, and sends this information to the drone via the device. The drone moves to an appropriate position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, performs basic editing, and transfers it to the device. The user can review the photo, edit it if necessary, and share it with friends.

[0095] An example of a prompt sentence is, "I'm sightseeing at the Eiffel Tower in Paris. I want to take the best photo. Where should I take the photo and what is the best composition?"

[0096] This system allows users to reduce the time it takes to take individual photos and easily obtain high-quality photographs, thereby increasing the enjoyment of travel and improving user satisfaction.

[0097] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0098] Step 1:

[0099] The user starts the drone and pairs it with the device using a dedicated app. The input is for the user to turn on the drone, start the app, and perform the pairing process. The output is for the device and drone to connect via Bluetooth or Wi-Fi. Specifically, the user selects "Start pairing" in the app and presses the pairing button on the drone, which links the device and drone.

[0100] Step 2:

[0101] After pairing is complete, the device connects to an information processing device (server) on the cloud and obtains evaluation data and trend information. The user's identification information and location information are sent to the server as input. Based on this data, the server sends the user's evaluation data and destination trend information to the device as output. In concrete terms, the device sends a request to the server via an internet connection and performs communication processing to obtain the required data.

[0102] Step 3:

[0103] The device uses its GPS function to obtain the user's current location. As input, location data is obtained from the device's GPS sensor. As output, current location information is generated and sent to the server. Specifically, the device continuously monitors the user's current location and sends the obtained data to the server in real time.

[0104] Step 4:

[0105] The server generates a list of photo spots based on the acquired current location information. The input includes the user's current location information and trend information. The output is a list of photo spots that is generated and sent to the device. Specifically, the server performs a database search and AI analysis to create a list of popular spots near the user's current location.

[0106] Step 5:

[0107] The user selects a photo spot from the photo spot list displayed on the device. The photo spot list sent from the server is displayed as input. The selected photo spot information is saved on the device as output. In concrete terms, the user selects a photo spot using the touch screen and presses the confirm button.

[0108] Step 6:

[0109] The server uses a generative AI model to calculate the optimal composition based on the selected photo spot information. Inputs include user evaluation data, trend information, and selected photo spot information. As output, optimal composition data is generated and sent to the device. Specifically, the server runs the AI ​​model, calculates the optimal composition within a few seconds, and sends the results.

[0110] Step 7:

[0111] The terminal transfers the received shooting composition data to the drone. The input includes the shooting composition data from the server. The output is the composition data sent to the drone. Specifically, the terminal sends the data to the drone via wireless communication.

[0112] Step 8:

[0113] The drone automatically sets its flight position and camera angle based on the received composition data. The input includes the shooting composition data from the device. The output is the flight position and camera angle. The drone uses GPS and internal sensors to navigate to the appropriate position and adjust the camera angle.

[0114] Step 9:

[0115] When the user operates the camera button on the device, the drone automatically takes a photo. The input includes the user's shooting instructions. The output is the captured photo data. Specifically, the user taps the camera button on the device, and the drone takes a picture.

[0116] Step 10:

[0117] The drone performs some basic editing on the captured photos and transmits them to the device. The input includes the raw image data captured. The output is the edited photo data sent to the device. Specifically, the drone uses internal algorithms to adjust brightness and apply filters, and transmits the image to the device via wireless communication.

[0118] Step 11:

[0119] The user can then review the photos received on their device, make further edits, or share them on social media. The input includes the edited photo data transferred from the drone. The output is the user's final edited photo or the photo data they want to share. Specifically, the user uses the editing functions on their device to edit the photo and then posts it to social media using the share button.

[0120] In this way, users can easily take and share high-quality photos through individual processing steps.

[0121] (Application example 1)

[0122] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0123] Conventional product inspection methods are primarily performed manually, which is problematic due to low efficiency and inconsistent quality. Manual inspection is also time-consuming and can undermine overall factory productivity. Furthermore, inspection results often vary depending on the level of expertise of workers, making the process unreliable. There is a need for technology that can solve these issues and automate product quality inspection while improving efficiency and accuracy.

[0124] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0125] In this invention, the server includes a means for suggesting optimal shooting compositions based on user evaluation data stored on a terminal and trend information for the destination, a drone or robot that automatically adjusts its flight position and camera angle based on the shooting composition suggested by the server, a terminal that issues shooting instructions to the drone or robot, and an AI image analysis model that analyzes the captured image data and detects abnormalities. This enables the automation of product quality inspections, improving the efficiency and accuracy of inspections. It also contributes to alleviating labor shortages and improving productivity.

[0126] A "terminal" is a device operated by a user, specifically a smartphone or tablet, which is a means of controlling drones and robots via a dedicated app.

[0127] The "server" is a device installed on the cloud that stores and analyzes user evaluation data and trend information, and calculates and provides optimal shooting compositions and inspection methods.

[0128] "Drone or robot" means a mobile device that moves autonomously to take photographs or perform inspections and collect data through cameras and sensors.

[0129] The "AI image analysis model" is an artificial intelligence machine learning model that analyzes captured image data and detects abnormalities, and performs quality inspections using image processing technology.

[0130] A "prompt" is an instruction used to have the AI ​​image analysis model detect abnormalities, and is text data used to provide the AI ​​with specific inspection details and criteria.

[0131] MODE FOR CARRYING OUT THE INVENTION

[0132] As an embodiment of the present invention, an automatic product quality inspection system using a terminal, a server, and a robot will be described. This system automatically proposes optimal inspection methods and compositions based on product quality data and trend information related to inspection, and the robot then automatically performs the inspection based on these.

[0133] System configuration

[0134] 1. Terminal: Quality control personnel operate a terminal such as a smartphone or tablet. A dedicated app for controlling the robot is installed on this terminal. The terminal's role is to obtain quality data and trend information from the server and send it to the robot.

[0135] 2. Server: The server is installed in the cloud and stores and analyzes quality data. It also collects trend information on the production line and inspection environment, and calculates the optimal inspection method and composition based on the analysis results.

[0136] 3. Robot: The robot is equipped with a camera and sensors, and automatically adjusts its position and the angle of the camera and sensor based on the inspection method and composition proposed by the server. It also automatically performs inspections, performs basic data analysis, and transfers the results to a terminal.

[0137] Program processing overview

[0138] Robot startup and data synchronization

[0139] A quality control officer activates the robot and pairs it with a smartphone (terminal), which then synchronizes quality data and trend information from the server and sends it to the robot.

[0140] Obtaining and setting inspection locations

[0141] The terminal acquires the position information of the production line and sends it to the robot. The server displays a list of inspection spots based on the production line. The quality control personnel selects an inspection spot.

[0142] Inspection preparation and composition proposal

[0143] The server calculates the optimal inspection method and composition based on quality data and trend information, and sends this information to the robot via a terminal. The robot then sets the appropriate movement position and angle based on the proposed inspection method.

[0144] Automated Inspection and Data Collection

[0145] When a quality control officer presses the inspection button on the terminal, the robot performs an inspection according to the specified composition. After the inspection, the robot performs basic data analysis (such as detecting anomalies) and transfers the results to the terminal. The quality control officer checks the inspection results on the terminal and performs further analysis and recording.

[0146] Specific examples

[0147] For example, on an electrical appliance production line, a quality control officer activates a robot and pairs it with a terminal. The terminal obtains information about the production line's location and sends it to the robot. The server calculates the optimal inspection method and composition (e.g., "camera angle and position to detect wiring errors") based on quality data and trend information. This information is sent to the robot via the terminal, and the robot moves to the appropriate position and adjusts the camera and sensor angles. When the quality control officer presses the inspection button, the robot automatically inspects the product, and if it detects an abnormality, it transfers the results, including information about it, to the terminal. The quality control officer checks this data and, if necessary, records it or conducts further inspection.

[0148] Example prompt sentence:

[0149] Inspect products on the production line to detect defects. Specifically, check the following:

[0150] 1. Wiring error

[0151] 2. Surface scratches

[0152] 3. Missing parts

[0153] Please use the image data and specify the location if an anomaly is detected.

[0154] This system will reduce the time required for product quality inspection and improve the rate at which defective products are detected, while also helping to alleviate labor shortages and improve the efficiency of production lines.

[0155] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0156] Step 1:

[0157] The user starts the robot and pairs it with a device (smartphone or tablet). The device obtains the user's evaluation data and inspection trend information from the cloud server and sends it to the robot. The input in this step is the user's operation and data obtained from the server, and the output is the inspection data sent to the robot.

[0158] Step 2:

[0159] The terminal acquires the location information of the production line and sends it to the server. The server generates an inspection spot list for the production line based on this location information and displays it on the terminal. The input in this step is the location information of the production line, and the output is the inspection spot list generated by the server.

[0160] Step 3:

[0161] The user selects an inspection spot on the terminal and sends that information to the robot. Based on the selected inspection spot, the server analyzes past quality data and trend information and calculates the optimal inspection method and composition. This generates data for the robot to move to the optimal position and set the camera and sensor angles. The input in this step is the inspection spot selected by the user, quality data, and trend information, and the output is the composition and movement position data sent to the robot.

[0162] Step 4:

[0163] The server calculates the optimal inspection method and composition based on the quality data and trend information, and sends that information to the robot via the terminal. The robot moves to an appropriate position based on the proposed inspection method and sets the camera and sensor angles. The input in this step is the quality data and trend information received from the server, and the output is the robot's movement position and camera / sensor setting information.

[0164] Step 5:

[0165] When the user operates the inspection button on the terminal, the robot inspects the product using the specified composition. The robot sends the captured image data and sensor information to a cloud server, which then uses an AI model to analyze the image and detect any abnormalities. The input in this step is the image data and sensor information acquired by the robot, and the output is the analysis results of the abnormality detection by the server.

[0166] Step 6:

[0167] Based on the analysis results, the server notifies the terminal of any abnormalities or problems. The user checks these analysis results on the terminal, and records or further examines them as necessary. The input in this step is the analysis results from the server, and the output is the inspection results displayed on the terminal.

[0168] Step 7:

[0169] The server uses the generative AI model to automatically generate prompts for anomaly detection and provide the user with recommendations for the next inspection and improvement measures. The inputs in this step are the analysis results and past quality data, and the output is the generated prompts.

[0170] Example prompt sentence:

[0171] Inspect products on the production line to detect defects. Specifically, check the following:

[0172] 1. Wiring error

[0173] 2. Surface scratches

[0174] 3. Missing parts

[0175] Please use the image data and specify the location if an anomaly is detected.

[0176] These steps enable the automation of product quality inspections and the detection of abnormalities with high accuracy and efficiency.

[0177] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0178] As an embodiment of the present invention, a travel photography system using a terminal, a server, a drone, and an emotion engine will be described. This system automatically proposes optimal photo compositions based on user evaluation data, destination trend information, and user emotion data, and the drone automatically takes photos based on the proposed compositions.

[0179] System configuration

[0180] 1. Device: The user operates a device such as a smartphone or tablet. A dedicated app with drone control and emotion engine functions is installed on this device. The device acquires evaluation data and trend information from the server and transmits it to the drone. It also analyzes the user's voice and facial expressions to recognize emotions and transmits the data to the server.

[0181] 2. Server: The server is installed in the cloud and stores and analyzes user evaluation data. It also collects and analyzes trend information for destinations (such as tourist spots) and calculates optimal photo compositions based on emotional data.

[0182] 3. Drone: The drone is equipped with a camera and automatically adjusts its flight position and camera angle based on the composition suggested by the server. It also automatically takes photos, performs basic editing, and transfers the photos to the device.

[0183] 4. Emotion Engine: The emotion engine is built into the device and analyzes the user's voice and facial expressions to recognize emotions. The recognized emotion data is sent to the server and used to optimize the shooting composition.

[0184] Program processing overview

[0185] Drone launch and data synchronization

[0186] The user activates the drone and pairs it with their smartphone (device). The device then launches a dedicated app and connects to the drone via Bluetooth or Wi-Fi. The device then sends the user's evaluation data, trend information, and past emotion data to the server.

[0187] Acquiring emotion data

[0188] While the user is operating the drone, an emotion engine built into the device analyzes the user's voice and facial expressions to recognize their emotions, and this emotion data is sent to a server in real time.

[0189] Composition suggestions

[0190] The server analyzes the user's rating data, trend information, and emotional data to calculate the optimal composition for the photo. For example, if the user is showing signs of great enjoyment, a composition with a wide background may be selected. The results of this calculation are sent to the drone via the device.

[0191] Drone movement and filming

[0192] The drone automatically adjusts its flight position and camera angle based on the composition of the shot. When the user commands the drone to start shooting, it automatically takes a photo. After that, the drone performs basic editing (adjusting brightness and applying filters) on the photo and transfers it to the device.

[0193] Specific examples

[0194] A specific example of this system is shown below. For example, when a user visits the Eiffel Tower in Paris, they first start up the drone and pair it with the device. The device obtains the user's current location using GPS and sends it to the drone. The emotion engine is also running, analyzing the user's facial expressions in real time. If the user shows a happy expression with the Eiffel Tower in the background, the server will suggest the optimal composition based on that emotional data. This composition information is sent to the drone via the device, and the drone moves to the optimal position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, edits it, and transfers it to the device. The user can then review the photo, make further edits, and share it on social media.

[0195] This system allows users to efficiently take the best photos that suit their emotions, not only reducing the time spent taking photos while traveling but also making it easier to obtain photos that they are satisfied with.

[0196] The processing flow will be explained below.

[0197] Step 1:

[0198] The user starts the drone and pairs it with the smartphone (device), which then launches a dedicated app and connects to the drone via Bluetooth or Wi-Fi.

[0199] Step 2:

[0200] The device connects to the server, obtains user evaluation data and trend information, and synchronizes it with the drone. It also obtains previously saved emotion data from the server.

[0201] Step 3:

[0202] The device uses a camera and microphone to monitor the user's voice and facial expressions in real time, and analyzes their emotions using an emotion engine. For example, it analyzes smiles, surprised expressions, tone of voice, etc. to obtain emotional data. This emotional data is then sent to a server.

[0203] Step 4:

[0204] When the user approaches a destination (e.g., the Eiffel Tower), the device uses GPS to obtain its current location and transmits the location information to the drone, which then sends the information to the server.

[0205] Step 5:

[0206] The server calculates the optimal composition for the photo based on the user's current location, rating data, trend information, and real-time emotional data. For example, if the user is showing signs of joy, the server will suggest using a wide-angle composition or incorporating the surrounding scenery. This information is sent to the drone via the device.

[0207] Step 6:

[0208] The drone automatically adjusts its flight position and camera angle based on the composition information received from the server, and uses a gimbal to correct for camera shake and tilt.

[0209] Step 7:

[0210] The user operates the shooting command button on the device to send a command to the drone to start shooting, and the drone takes a photo with the specified composition.

[0211] Step 8:

[0212] After the drone takes the photo, it uses its built-in image processing algorithm to perform basic editing (adjusting brightness, color correction, applying filters, etc.) and transfers the edited photo to your device.

[0213] Step 9:

[0214] The user can review the received photos on the device and, if necessary, make additional edits to match the emotion, such as adding a specific filter to the photo or cropping it.

[0215] Step 10:

[0216] Finally, users can share the edited photos with friends via social media or email. Through this process, users can efficiently obtain high-quality photos that match their emotions and trends.

[0217] Example 2

[0218] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0219] Conventional travel photography systems require users to determine the appropriate composition and shooting location, and also operate the drone and camera themselves, which results in a lot of time and effort required for the photo shoot. It is also difficult to capture photos that reflect the user's emotions and preferences, making it difficult to obtain photos that are satisfactory. This poses a problem that reduces the enjoyment of traveling.

[0220] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0221] In this invention, the server includes means for proposing optimal photographic compositions based on user evaluation data stored in the terminal and trend information for destinations, means for transmitting user emotional data to the server via an emotion analysis device built into the terminal, and means for analyzing the user emotional data and calculating optimal photographic compositions, thereby enabling users to easily and automatically take optimal photographs that match their emotions and preferences.

[0222] A "terminal" is a portable electronic device such as a smartphone or tablet that is operated by a user.

[0223] "Rating data" refers to information about photos and reviews that users have liked and rated in the past.

[0224] "Destination trend information" is the latest popularity and rating information about destinations such as tourist spots.

[0225] The "information processing device" is a server installed on the cloud that analyzes user data and suggests optimal shooting compositions.

[0226] An "unmanned flying device" is a drone that flies automatically and is equipped with a camera to take pictures.

[0227] An "emotion analysis device" is a system that analyzes a user's voice and facial expressions to recognize emotional data.

[0228] "Emotion data" refers to emotional information analyzed based on the user's voice and facial expressions.

[0229] "Photography composition" refers to the screen composition and subject placement when taking a photograph.

[0230] As an embodiment of the present invention, a travel photography system using a terminal, a server, an unmanned aerial vehicle, and an emotion analysis device will be described. This system automatically proposes optimal photo compositions based on user evaluation data, destination trend information, and user emotion data, and the unmanned aerial vehicle automatically takes photos based on the proposed compositions.

[0231] System configuration

[0232] 1. Device: The user operates a device such as a smartphone or tablet. This device has a dedicated app installed to control the drone and use the emotion analysis device. The device is responsible for obtaining evaluation data and trend information from the server and sending it to the drone. It also analyzes the user's voice and facial expressions to recognize emotions and sends the data to the server.

[0233] 2. Server: The server is installed on the cloud and stores and analyzes user evaluation data. It also collects and analyzes trend information about destinations and calculates optimal photo compositions based on emotional data.

[0234] 3. Unmanned aerial vehicle: The unmanned aerial vehicle (drone) is equipped with a camera and automatically adjusts its flight position and camera angle based on the composition of the photo proposed by the server. It also automatically takes photos, performs basic editing, and transfers the photos to the device.

[0235] 4. Emotion Analysis Device: The emotion analysis device is built into the device and recognizes emotions by analyzing the user's voice and facial expressions. The recognized emotional data is sent to the server and used to optimize the shooting composition.

[0236] Program processing overview

[0237] The system's programming begins when the user activates the drone and pairs it with the device. The device then launches a dedicated app and connects to the drone via Bluetooth or Wi-Fi. The device then sends the user's evaluation data, trend information, and past emotional data to the server. While the user is operating the drone, an emotion analyzer built into the device analyzes the user's voice and facial expressions to recognize their emotions. This emotional data is then sent to the server in real time.

[0238] The server analyzes the evaluation data, trend information, and emotion data to calculate the optimal composition for the photo. For example, if the user is showing a very happy emotion, a composition with a wide background may be selected. The calculation results are sent to the unmanned aerial vehicle via the terminal.

[0239] The drone automatically adjusts its flight position and camera angle based on the proposed composition. When the user issues a command to start shooting, the drone automatically takes a photo. After that, the drone performs basic editing (adjusting brightness and applying filters) on the photo and transfers it to the device.

[0240] Specific examples

[0241] Next, we will show a concrete example of this system. For example, when a user visits the Eiffel Tower in Paris, they first start up the drone and pair it with their device. The device obtains the user's current location using GPS and sends it to the drone. An emotion analysis device is also running, analyzing the user's facial expressions in real time. If the user shows a happy expression with the Eiffel Tower in the background, the server will suggest the optimal composition based on that emotional data. This composition information is sent to the drone via the device, and the drone moves to the optimal position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, edits it, and transfers it to the device. The user can then review the photo, make further edits, and share it on social media.

[0242] An example of a prompt is as follows:

[0243] "When you arrive at the Eiffel Tower in Paris, simply launch the drone and pair it with your smartphone. Smile with the Eiffel Tower in the background, and the drone will calculate the optimal composition and take the photo automatically. It will then edit the photo and transfer it to your device."

[0244] This system allows users to efficiently take the best photos that suit their emotions, not only reducing the time spent taking photos while traveling but also making it easier to obtain photos that satisfy users.

[0245] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0246] Step 1:

[0247] Initial Setup and Data Synchronization

[0248] The user starts the unmanned flying device and pairs it with a smartphone (terminal).

[0249] Input: User operation (starting the drone, pairing with the device)

[0250] Specific operation: The user launches a dedicated app installed on the device and connects to the drone via Bluetooth or Wi-Fi. The device then uses its GPS function to obtain the user's current location and sends that information to the server.

[0251] Output: GPS data is sent to the server, and the server sends evaluation data, trend information, and past emotion data to the device.

[0252] Step 2:

[0253] Real-time acquisition of emotion data

[0254] The user begins operating the unmanned flying device.

[0255] Input: User operation, user voice and facial expression data

[0256] Specific operation: The emotion analysis device built into the device analyzes the user's voice and facial expressions in real time using a camera and microphone. The device then transmits this emotion data to a server in real time.

[0257] Output: The recognized emotion data is sent to the server in real time.

[0258] Step 3:

[0259] Shooting composition calculation and suggestions

[0260] The server calculates the shooting composition based on the data received.

[0261] Input: Rating data, trend information, sentiment data

[0262] Specific operation: The server analyzes the evaluation data, trend information, and emotion data to generate the optimal photo composition. For example, if the user looks happy, it uses an extensive search algorithm to suggest a composition that includes a wide background.

[0263] Output: The optimal shooting composition data is generated and sent to the device.

[0264] Step 4:

[0265] Flying and filming unmanned aerial vehicles

[0266] The unmanned flying device is operated based on the photographic composition.

[0267] Input: Shooting composition data, user's instruction to start shooting

[0268] How it works: The unmanned flying device automatically adjusts its flight position and camera angle based on composition suggestion data from the server. When the user presses the shooting button in the dedicated app, the unmanned flying device automatically releases the shutter. The camera inside the drone uses an autofocus function to set the optimal shooting conditions.

[0269] Output: The captured photo data is stored in the drone.

[0270] Step 5:

[0271] Photo editing and transfer

[0272] The drone then edits the photos and transfers them to the device.

[0273] Input: Photographed photo data

[0274] How it works: After taking a photo, the drone automatically adjusts brightness and applies filters, then transfers the edited photo to your device via Wi-Fi or Bluetooth.

[0275] Output: The edited photo data is transferred to the device and displayed to the user.

[0276] (Application example 2)

[0277] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0278] The present invention relates to a system for taking optimal advertising photos by utilizing user evaluation data, destination trend information, and emotional data. Conventional photography systems have difficulty proposing optimal compositions that reflect user emotions and real-time evaluation data, making it impossible to take advertising photos with high satisfaction. Furthermore, since there were no systems specialized for advertising photography and manual editing was required, there was a demand for efficient photography and easy editing.

[0279] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0280] In this invention, the server includes a means for proposing an optimal photographic composition based on user evaluation data stored in the terminal and trend information for the destination, a flying device that automatically adjusts the flight position and camera angle based on the photographic composition proposed by the server, a terminal that instructs the flying device to take a photograph, an emotion analysis engine that analyzes user emotion data and transmits it to the server, a means for proposing an optimal photographic composition for an advertising photograph based on the user emotion data, and a means for basic editing of the photographed advertising photograph and transferring it to the terminal. This makes it possible to efficiently take optimal advertising photographs that reflect the user's emotions and automatically perform basic editing work after photographing.

[0281] A "terminal" is an information processing device operated by a user, and specifically includes a smartphone, tablet, computer, etc.

[0282] "User evaluation data" includes information on photos, videos, etc. that users have previously evaluated, and is data that is analyzed based on those evaluations.

[0283] "Destination Trends" is data based on the latest information and popular topics related to specific locations and events.

[0284] A "server" is an information processing device that is installed on the cloud and stores, analyzes, and transmits data.

[0285] "Shooting composition" refers to suggestions for determining the optimal viewpoint and frame when taking photographs or videos.

[0286] A "flying device" is a device equipped with a camera that takes photographs by flying at a specified position and angle, and specifically includes drones.

[0287] "Emotion analysis engine" refers to software or hardware that analyzes a user's facial expressions and voice to recognize their emotions.

[0288] "Advertising photography" is photography taken for commercial or promotional purposes.

[0289] "Basic editing" refers to basic editing tasks such as adjusting brightness and applying filters to photos after they have been taken.

[0290] As an embodiment of the present invention, a system for taking advertising photographs at travel destinations, event venues, etc. This system automatically proposes optimal compositions for advertising photographs based on user evaluation data, trend information for destinations, and user emotional data, and the flying device automatically takes the photographs based on the proposed compositions.

[0291] System configuration

[0292] 1. Device:

[0293] The user operates a device such as a smartphone or tablet. A dedicated app with flight device control and emotion analysis engine functions is installed on this device. The device acquires evaluation data and trend information from the server and sends it to the flight device. It also analyzes the user's voice and facial expressions to recognize emotions and sends the data to the server.

[0294] 2. Server:

[0295] The server is installed in the cloud and stores and analyzes user evaluation data. It also collects and analyzes trend information for destinations (such as tourist spots and event venues) and calculates optimal composition for advertising photos based on emotional data.

[0296] 3. Flight equipment:

[0297] The flying device is equipped with a camera and automatically adjusts the flight position and camera angle based on the composition of the photo suggested by the server. It also automatically takes photos, performs basic editing, and transfers the photos to the device.

[0298] 4. Sentiment Analysis Engine:

[0299] The emotion analysis engine is built into the device and recognizes emotions by analyzing the user's voice and facial expressions. The recognized emotion data is sent to a server and used to optimize the shooting composition.

[0300] Processing Description

[0301] The server operates using a cloud computing service. It receives user evaluation data, destination trend information, and emotional data, and then calculates the optimal photo composition based on this data. This calculation uses a machine learning algorithm called a generative AI model. This generative AI model predicts the user's preferences and emotional state based on past data, and then suggests the optimal composition.

[0302] The user's device is a smartphone or tablet. The device is equipped with a camera and microphone, which are used to analyze the user's facial expressions and voice in real time. The analysis results are sent to the server via the device's emotion analysis engine.

[0303] A standard drone is used as the flying device. This drone is equipped with a high-resolution camera and automatically flies and takes photos according to the optimal shooting composition sent from the server. After taking the photos, it automatically performs basic editing (adjusting brightness and applying filters) and transfers the photos to the device.

[0304] Specific examples

[0305] For example, if a user visits a famous tourist spot and wants to take a photo for an advertisement, they first start the drone and pair it with the device. The device uses GPS to obtain the user's current location and sends it to the server. At the same time, an emotion analysis engine is running, analyzing the user's facial expressions and voice in real time. If the user smiles or shows a happy expression, the server uses that emotional data to suggest the optimal composition. This composition information is sent to the drone via the device, and the drone moves to the optimal position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, performs some basic editing, and then transfers the photo to the device. This system allows users to efficiently take optimal advertising photos that reflect their emotions.

[0306] Prompt Sentence Examples

[0307] "I want to take the perfect advertising photo at the Eiffel Tower in Paris."

[0308] "Please suggest advertising photos that express emotions based on the user's smile."

[0309] This system allows users to easily take high-quality advertising photos.

[0310] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0311] Step 1:

[0312] Starting the drone and pairing it with your device

[0313] The user starts the drone and pairs it with a device such as a smartphone or tablet. This pairing is done via Bluetooth or Wi-Fi. The input data is the drone's start-up signal and the device's connection request, and the output is a status indicating that pairing is complete. This pairing procedure prepares the entire system to work together and begin operation.

[0314] Step 2:

[0315] Location and emotion data acquisition

[0316] The device uses GPS to obtain the user's current location and activates the emotion analysis engine. The emotion analysis engine uses the device's camera and microphone to analyze the user's facial expressions and voice in real time and generate emotion data. The input data is camera footage, audio, and GPS information, and the output is emotion data and the current location. This allows the user's real-time emotional state and location information to be understood.

[0317] Step 3:

[0318] Sending data to the server

[0319] The device sends the acquired evaluation data, location information, trend information, and emotion data to the server. The input data is the various data collected by the device, and the output data is sent to the server. The server receives this data and prepares to calculate the optimal composition for the advertising photo based on the user's emotion and location information.

[0320] Step 4:

[0321] Calculating the composition of the photo

[0322] The server uses a generative AI model to calculate the optimal shooting composition based on the received evaluation data, trend information, and emotion data. The input data is the entire set of received data, and the output is optimal shooting composition information. This composition information includes the shooting position and camera angle. The generative AI model learns from past data and proposes the optimal composition.

[0323] Step 5:

[0324] Sending the composition

[0325] The server sends the calculated optimal shooting composition information to the drone via the terminal. The input data is the generated shooting composition information, and that information is sent to the drone as output. This allows the drone to automatically start operating based on that composition.

[0326] Step 6:

[0327] Automatic drone flight and photography

[0328] The drone moves to the optimal flight position and camera angle based on the received shooting composition information. After moving, it automatically takes photos according to the user's instructions. The input data is the shooting composition information and the user's shooting instructions, and the output is the captured photo. The drone uses a high-resolution camera to take photos that match the composition.

[0329] Step 7:

[0330] Basic photo editing and transfer

[0331] After taking a photo, the drone performs basic editing such as adjusting the brightness and applying filters to the photo. The edited photo is then transferred to the device. The input data is the captured photo, and the output is the edited photo sent to the device. This allows the user to immediately review the photo and make further edits if necessary.

[0332] Step 8:

[0333] View and share photos

[0334] Users can view the transferred photos on their devices and make further edits. They can then share them on social media. The input data is the edited photo, and the output is the shared photo or content. Through this process, users can efficiently take and share high-quality advertising photos.

[0335] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0336] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0337] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0338] [Second embodiment]

[0339] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0340] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0341] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0342] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0343] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0344] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0345] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0346] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0347] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0348] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0349] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0350] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0351] As an embodiment of the present invention, a travel photography system using a terminal, a server, and a drone will be described. This system automatically proposes optimal photo compositions based on user evaluation data and destination trend information, and the drone automatically takes photos based on the proposed compositions.

[0352] System configuration

[0353] 1. Device: The user operates a device such as a smartphone or tablet. A dedicated app for controlling the drone is installed on this device. The device's role is to obtain evaluation data and trend information from the server and send it to the drone.

[0354] 2. Server: The server is installed on the cloud and stores and analyzes user evaluation data. It also collects trend information for destinations (e.g., tourist spots) and calculates the optimal shooting composition based on the analysis results.

[0355] 3. Drone: The drone is equipped with a camera and automatically adjusts its flight position and camera angle based on the composition suggested by the server. It also automatically takes photos, performs basic editing, and transfers the photos to the device.

[0356] Program processing overview

[0357] Drone launch and data synchronization

[0358] The user activates the drone and pairs it with a smartphone (terminal). The terminal synchronizes and transmits the user's evaluation data and destination trend information from the server to the drone.

[0359] Obtaining location information and setting destination

[0360] When the user approaches the destination, the device acquires the current location using GPS. The device sends the current location information to the drone, and the server displays a list of photo spots based on the destination. The user selects a photo spot.

[0361] Preparation for shooting and composition suggestions

[0362] The server calculates the optimal composition based on the evaluation data and trend information, and transmits this information to the drone via the device. The drone then sets the appropriate flight position and angle based on the proposed composition.

[0363] Automated shooting and editing

[0364] When the user presses the camera button on the device, the drone takes a photo with the specified composition. After taking the photo, the drone performs basic editing (adjusting brightness, applying filters, etc.) and transfers the photo to the device. The user can then view the photo on the device, make further edits, or share it on social media.

[0365] Specific examples

[0366] For example, when a user visits the Eiffel Tower in Paris, they start up the drone and pair it with their device. The device uses GPS to obtain the user's current location and sends it to the drone. The server calculates the optimal composition for taking a photo of the Eiffel Tower (e.g., "a full-body photo with the Eiffel Tower in the background") based on evaluation data and trend information. This information is sent to the drone via the device, and the drone moves to the appropriate position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, performs basic editing, and transfers it to the device. The user can review the photo, edit it if necessary, and share it with friends.

[0367] This system allows users to reduce the time it takes to take individual photos and easily obtain higher quality photos, which increases the enjoyment of travel and improves user satisfaction.

[0368] The processing flow will be explained below.

[0369] Step 1:

[0370] The user starts the drone and pairs it with the smartphone (device), which then launches a dedicated app and connects to the drone via Bluetooth or Wi-Fi.

[0371] Step 2:

[0372] The device sends the user's rating data (such as photos and videos that they have "liked" in the past) to the server, which receives and analyzes this data.

[0373] Step 3:

[0374] The server analyzes the evaluation data to understand the user's preferences and photography trends, and then collects and analyzes trend information for the destination (popular photo spots and composition).

[0375] Step 4:

[0376] When the user arrives at their travel destination (e.g., the Eiffel Tower), the device uses GPS to obtain their current location, which is then transmitted to the drone, which then sends the information to the server.

[0377] Step 5:

[0378] The server calculates the optimal composition based on the user's current location, rating data, and trend information. For example, it suggests a photo with the Eiffel Tower in the background or a composition shot from a specific angle.

[0379] Step 6:

[0380] The server calculates the composition and sends it to the drone via the device, which then automatically sets the appropriate flight position and camera angle based on the proposed composition.

[0381] Step 7:

[0382] The user operates the shooting instruction button on the device to send a command to the drone to start shooting, and the drone takes a photo with the specified composition.

[0383] Step 8:

[0384] After the drone captures the footage, it performs some basic editing (adjusting brightness, applying filters, etc.) automatically using internal image processing algorithms.

[0385] Step 9:

[0386] The drone then transfers the edited photos to the device, where the user can review them and make further edits if necessary.

[0387] Step 10:

[0388] Finally, users can share the edited photos with friends via social media or email. This process allows users to efficiently and easily obtain high-quality photos.

[0389] Example 1

[0390] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0391] When traveling and visiting beautiful landscapes and famous places, there is a demand for easy, high-quality photos with optimal composition, but this can be a difficult task for users without photography skills. Another problem is that the time spent taking photos reduces the time available to enjoy sightseeing. Furthermore, taking photos using drones requires technical operations that are difficult for average users to operate. There is a demand for a system that solves these problems and allows anyone to easily take high-quality photos.

[0392] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0393] In this invention, the server includes a means for suggesting optimal photo compositions based on user evaluation data stored in the terminal and trend information for destinations, a means for analyzing data on photos that the user has previously liked and rated, and a means for acquiring current location information using a GPS function and generating a list of photo spots, thereby enabling users to easily take high-quality, memorable photos while minimizing the amount of work required.

[0394] The "information processing device" is a computer system that has the function of proposing optimal photographic compositions based on user evaluation data and trend information about destinations.

[0395] An "unmanned aerial vehicle" is a device that automatically adjusts the flight position and camera angle based on the shooting composition proposed by the server, and takes and edits photographs.

[0396] An "information terminal device" is a device operated by a user to instruct an unmanned aerial vehicle to take photos and obtain current location information via GPS, and includes smartphones, tablets, and the like.

[0397] "User evaluation data" refers to data relating to photos taken by the user in the past, evaluations made by the user, and preferences.

[0398] "Trending information" is information about the general popularity or current topics of a particular destination.

[0399] "Photography composition" refers to the photographic conditions, such as the subject placement, camera angle, and focal length, when taking a photograph.

[0400] "GPS function" refers to technology that uses the Global Positioning System to obtain current latitude and longitude location information.

[0401] A "generative AI model" is a model that uses artificial intelligence algorithms to generate new shooting compositions and data patterns.

[0402] The "photography spot list" is a list of multiple candidate photo shooting locations that the server proposes based on the user's current location information.

[0403] "Basic editing" refers to the process of performing basic image processing on photographs, such as adjusting brightness and applying filters.

[0404] As an embodiment of the present invention, a system for enabling a user to take optimal photographs while traveling will be described. This system is configured using an information processing device (server), an information terminal device (terminal), and an unmanned aerial vehicle (drone).

[0405] First, the user activates the drone at their travel destination and pairs it with the device using a dedicated app. The device then connects to an information processing device and obtains the user's evaluation data and trend information for the destination. This evaluation data and trend information are stored in the cloud database of the information processing device.

[0406] Next, the terminal acquires the user's current location using its GPS function and sends it to the information processing device. The information processing device generates a photo spot list based on the acquired current location information and sends it to the user's terminal. The user selects a spot they want to take a photo from the photo spot list displayed on the terminal.

[0407] The information processing device uses a generative AI model to propose the optimal composition for the shot. The proposed composition is then sent to the drone via the device. The drone then automatically sets its flight position and camera angle based on the proposed composition.

[0408] When the user presses the shooting button on the dedicated app, the drone takes a photo with the specified composition. After taking the photo, the drone performs basic editing (adjusting brightness, applying filters, etc.) and transfers the edited photo to the device. The user can then review the transferred photo, make further edits as needed, or share it on social media.

[0409] For example, when a user visits the Eiffel Tower in Paris, they start up the drone and pair it with the device. The device uses GPS to obtain the user's current location and sends it to the information processing device. The information processing device calculates the optimal composition for taking a photo of the Eiffel Tower (e.g., "a full-body photo with the Eiffel Tower in the background") based on evaluation data and trend information, and sends this information to the drone via the device. The drone moves to an appropriate position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, performs basic editing, and transfers it to the device. The user can review the photo, edit it if necessary, and share it with friends.

[0410] An example of a prompt sentence is, "I'm sightseeing at the Eiffel Tower in Paris. I want to take the best photo. Where should I take the photo and what is the best composition?"

[0411] This system allows users to reduce the time it takes to take individual photos and easily obtain high-quality photographs, thereby increasing the enjoyment of travel and improving user satisfaction.

[0412] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0413] Step 1:

[0414] The user starts the drone and pairs it with the device using a dedicated app. The input is for the user to turn on the drone, start the app, and perform the pairing process. The output is for the device and drone to connect via Bluetooth or Wi-Fi. Specifically, the user selects "Start pairing" in the app and presses the pairing button on the drone, which links the device and drone.

[0415] Step 2:

[0416] After pairing is complete, the device connects to an information processing device (server) on the cloud and obtains evaluation data and trend information. The user's identification information and location information are sent to the server as input. Based on this data, the server sends the user's evaluation data and destination trend information to the device as output. In concrete terms, the device sends a request to the server via an internet connection and performs communication processing to obtain the required data.

[0417] Step 3:

[0418] The device uses its GPS function to obtain the user's current location. As input, location data is obtained from the device's GPS sensor. As output, current location information is generated and sent to the server. Specifically, the device continuously monitors the user's current location and sends the obtained data to the server in real time.

[0419] Step 4:

[0420] The server generates a list of photo spots based on the acquired current location information. The input includes the user's current location information and trend information. The output is a list of photo spots that is generated and sent to the device. Specifically, the server performs a database search and AI analysis to create a list of popular spots near the user's current location.

[0421] Step 5:

[0422] The user selects a photo spot from the photo spot list displayed on the device. The photo spot list sent from the server is displayed as input. The selected photo spot information is saved on the device as output. In concrete terms, the user selects a photo spot using the touch screen and presses the confirm button.

[0423] Step 6:

[0424] The server uses a generative AI model to calculate the optimal composition based on the selected photo spot information. Inputs include user evaluation data, trend information, and selected photo spot information. As output, optimal composition data is generated and sent to the device. Specifically, the server runs the AI ​​model, calculates the optimal composition within a few seconds, and sends the results.

[0425] Step 7:

[0426] The terminal transfers the received shooting composition data to the drone. The input includes the shooting composition data from the server. The output is the composition data sent to the drone. Specifically, the terminal sends the data to the drone via wireless communication.

[0427] Step 8:

[0428] The drone automatically sets its flight position and camera angle based on the received composition data. The input includes the shooting composition data from the device. The output is the flight position and camera angle. The drone uses GPS and internal sensors to navigate to the appropriate position and adjust the camera angle.

[0429] Step 9:

[0430] When the user operates the camera button on the device, the drone automatically takes a photo. The input includes the user's shooting instructions. The output is the captured photo data. Specifically, the user taps the camera button on the device, and the drone takes a picture.

[0431] Step 10:

[0432] The drone performs some basic editing on the captured photos and transmits them to the device. The input includes the raw image data captured. The output is the edited photo data sent to the device. Specifically, the drone uses internal algorithms to adjust brightness and apply filters, and transmits the image to the device via wireless communication.

[0433] Step 11:

[0434] The user can then review the photos received on their device, make further edits, or share them on social media. The input includes the edited photo data transferred from the drone. The output is the user's final edited photo or the photo data they want to share. Specifically, the user uses the editing functions on their device to edit the photo and then posts it to social media using the share button.

[0435] In this way, users can easily take and share high-quality photos through individual processing steps.

[0436] (Application example 1)

[0437] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0438] Conventional product inspection methods are primarily performed manually, which is problematic due to low efficiency and inconsistent quality. Manual inspection is also time-consuming and can undermine overall factory productivity. Furthermore, inspection results often vary depending on the level of expertise of workers, making the process unreliable. There is a need for technology that can solve these issues and automate product quality inspection while improving efficiency and accuracy.

[0439] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0440] In this invention, the server includes a means for suggesting optimal shooting compositions based on user evaluation data stored on a terminal and trend information for the destination, a drone or robot that automatically adjusts its flight position and camera angle based on the shooting composition suggested by the server, a terminal that issues shooting instructions to the drone or robot, and an AI image analysis model that analyzes the captured image data and detects abnormalities. This enables the automation of product quality inspections, improving the efficiency and accuracy of inspections. It also contributes to alleviating labor shortages and improving productivity.

[0441] A "terminal" is a device operated by a user, specifically a smartphone or tablet, which is a means of controlling drones and robots via a dedicated app.

[0442] The "server" is a device installed on the cloud that stores and analyzes user evaluation data and trend information, and calculates and provides optimal shooting compositions and inspection methods.

[0443] "Drone or robot" means a mobile device that moves autonomously to take photographs or perform inspections and collect data through cameras and sensors.

[0444] The "AI image analysis model" is an artificial intelligence machine learning model that analyzes captured image data and detects abnormalities, and performs quality inspections using image processing technology.

[0445] A "prompt" is an instruction used to have the AI ​​image analysis model detect abnormalities, and is text data used to provide the AI ​​with specific inspection details and criteria.

[0446] MODE FOR CARRYING OUT THE INVENTION

[0447] As an embodiment of the present invention, an automatic product quality inspection system using a terminal, a server, and a robot will be described. This system automatically proposes optimal inspection methods and compositions based on product quality data and trend information related to inspection, and the robot then automatically performs the inspection based on these.

[0448] System configuration

[0449] 1. Terminal: Quality control personnel operate a terminal such as a smartphone or tablet. A dedicated app for controlling the robot is installed on this terminal. The terminal's role is to obtain quality data and trend information from the server and send it to the robot.

[0450] 2. Server: The server is installed in the cloud and stores and analyzes quality data. It also collects trend information on the production line and inspection environment, and calculates the optimal inspection method and composition based on the analysis results.

[0451] 3. Robot: The robot is equipped with a camera and sensors, and automatically adjusts its position and the angle of the camera and sensor based on the inspection method and composition proposed by the server. It also automatically performs inspections, performs basic data analysis, and transfers the results to a terminal.

[0452] Program processing overview

[0453] Robot startup and data synchronization

[0454] A quality control officer activates the robot and pairs it with a smartphone (terminal), which then synchronizes quality data and trend information from the server and sends it to the robot.

[0455] Obtaining and setting inspection locations

[0456] The terminal acquires the position information of the production line and sends it to the robot. The server displays a list of inspection spots based on the production line. The quality control personnel selects an inspection spot.

[0457] Inspection preparation and composition proposal

[0458] The server calculates the optimal inspection method and composition based on quality data and trend information, and sends this information to the robot via a terminal. The robot then sets the appropriate movement position and angle based on the proposed inspection method.

[0459] Automated Inspection and Data Collection

[0460] When a quality control officer presses the inspection button on the terminal, the robot performs an inspection according to the specified composition. After the inspection, the robot performs basic data analysis (such as detecting anomalies) and transfers the results to the terminal. The quality control officer checks the inspection results on the terminal and performs further analysis and recording.

[0461] Specific examples

[0462] For example, on an electrical appliance production line, a quality control officer activates a robot and pairs it with a terminal. The terminal obtains information about the production line's location and sends it to the robot. The server calculates the optimal inspection method and composition (e.g., "camera angle and position to detect wiring errors") based on quality data and trend information. This information is sent to the robot via the terminal, and the robot moves to the appropriate position and adjusts the camera and sensor angles. When the quality control officer presses the inspection button, the robot automatically inspects the product, and if it detects an abnormality, it transfers the results, including information about it, to the terminal. The quality control officer checks this data and, if necessary, records it or conducts further inspection.

[0463] Example prompt sentence:

[0464] Inspect products on the production line to detect defects. Specifically, check the following:

[0465] 1. Wiring error

[0466] 2. Surface scratches

[0467] 3. Missing parts

[0468] Please use the image data and specify the location if an anomaly is detected.

[0469] This system will reduce the time required for product quality inspection and improve the rate at which defective products are detected, while also helping to alleviate labor shortages and improve the efficiency of production lines.

[0470] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0471] Step 1:

[0472] The user starts the robot and pairs it with a device (smartphone or tablet). The device obtains the user's evaluation data and inspection trend information from the cloud server and sends it to the robot. The input in this step is the user's operation and data obtained from the server, and the output is the inspection data sent to the robot.

[0473] Step 2:

[0474] The terminal acquires the location information of the production line and sends it to the server. The server generates an inspection spot list for the production line based on this location information and displays it on the terminal. The input in this step is the location information of the production line, and the output is the inspection spot list generated by the server.

[0475] Step 3:

[0476] The user selects an inspection spot on the terminal and sends that information to the robot. Based on the selected inspection spot, the server analyzes past quality data and trend information and calculates the optimal inspection method and composition. This generates data for the robot to move to the optimal position and set the camera and sensor angles. The input in this step is the inspection spot selected by the user, quality data, and trend information, and the output is the composition and movement position data sent to the robot.

[0477] Step 4:

[0478] The server calculates the optimal inspection method and composition based on the quality data and trend information, and sends that information to the robot via the terminal. The robot moves to an appropriate position based on the proposed inspection method and sets the camera and sensor angles. The input in this step is the quality data and trend information received from the server, and the output is the robot's movement position and camera / sensor setting information.

[0479] Step 5:

[0480] When the user operates the inspection button on the terminal, the robot inspects the product using the specified composition. The robot sends the captured image data and sensor information to a cloud server, which then uses an AI model to analyze the image and detect any abnormalities. The input in this step is the image data and sensor information acquired by the robot, and the output is the analysis results of the abnormality detection by the server.

[0481] Step 6:

[0482] Based on the analysis results, the server notifies the terminal of any abnormalities or problems. The user checks these analysis results on the terminal, and records or further examines them as necessary. The input in this step is the analysis results from the server, and the output is the inspection results displayed on the terminal.

[0483] Step 7:

[0484] The server uses the generative AI model to automatically generate prompts for anomaly detection and provide the user with recommendations for the next inspection and improvement measures. The inputs in this step are the analysis results and past quality data, and the output is the generated prompts.

[0485] Example prompt sentence:

[0486] Inspect products on the production line to detect defects. Specifically, check the following:

[0487] 1. Wiring error

[0488] 2. Surface scratches

[0489] 3. Missing parts

[0490] Please use the image data and specify the location if an anomaly is detected.

[0491] These steps enable the automation of product quality inspections and the detection of abnormalities with high accuracy and efficiency.

[0492] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0493] As an embodiment of the present invention, a travel photography system using a terminal, a server, a drone, and an emotion engine will be described. This system automatically proposes optimal photo compositions based on user evaluation data, destination trend information, and user emotion data, and the drone automatically takes photos based on the proposed compositions.

[0494] System configuration

[0495] 1. Device: The user operates a device such as a smartphone or tablet. A dedicated app with drone control and emotion engine functions is installed on this device. The device acquires evaluation data and trend information from the server and transmits it to the drone. It also analyzes the user's voice and facial expressions to recognize emotions and transmits the data to the server.

[0496] 2. Server: The server is installed in the cloud and stores and analyzes user evaluation data. It also collects and analyzes trend information for destinations (such as tourist spots) and calculates optimal photo compositions based on emotional data.

[0497] 3. Drone: The drone is equipped with a camera and automatically adjusts its flight position and camera angle based on the composition suggested by the server. It also automatically takes photos, performs basic editing, and transfers the photos to the device.

[0498] 4. Emotion Engine: The emotion engine is built into the device and analyzes the user's voice and facial expressions to recognize emotions. The recognized emotion data is sent to the server and used to optimize the shooting composition.

[0499] Program processing overview

[0500] Drone launch and data synchronization

[0501] The user activates the drone and pairs it with their smartphone (device). The device then launches a dedicated app and connects to the drone via Bluetooth or Wi-Fi. The device then sends the user's evaluation data, trend information, and past emotion data to the server.

[0502] Acquiring emotion data

[0503] While the user is operating the drone, an emotion engine built into the device analyzes the user's voice and facial expressions to recognize their emotions, and this emotion data is sent to a server in real time.

[0504] Composition suggestions

[0505] The server analyzes the user's rating data, trend information, and emotional data to calculate the optimal composition for the photo. For example, if the user is showing signs of great enjoyment, a composition with a wide background may be selected. The results of this calculation are sent to the drone via the device.

[0506] Drone movement and filming

[0507] The drone automatically adjusts its flight position and camera angle based on the composition of the shot. When the user commands the drone to start shooting, it automatically takes a photo. After that, the drone performs basic editing (adjusting brightness and applying filters) on the photo and transfers it to the device.

[0508] Specific examples

[0509] A specific example of this system is shown below. For example, when a user visits the Eiffel Tower in Paris, they first start up the drone and pair it with the device. The device obtains the user's current location using GPS and sends it to the drone. The emotion engine is also running, analyzing the user's facial expressions in real time. If the user shows a happy expression with the Eiffel Tower in the background, the server will suggest the optimal composition based on that emotional data. This composition information is sent to the drone via the device, and the drone moves to the optimal position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, edits it, and transfers it to the device. The user can then review the photo, make further edits, and share it on social media.

[0510] This system allows users to efficiently take the best photos that suit their emotions, not only reducing the time spent taking photos while traveling but also making it easier to obtain photos that they are satisfied with.

[0511] The processing flow will be explained below.

[0512] Step 1:

[0513] The user starts the drone and pairs it with the smartphone (device), which then launches a dedicated app and connects to the drone via Bluetooth or Wi-Fi.

[0514] Step 2:

[0515] The device connects to the server, obtains user evaluation data and trend information, and synchronizes it with the drone. It also obtains previously saved emotion data from the server.

[0516] Step 3:

[0517] The device uses a camera and microphone to monitor the user's voice and facial expressions in real time, and analyzes their emotions using an emotion engine. For example, it analyzes smiles, surprised expressions, tone of voice, etc. to obtain emotional data. This emotional data is then sent to a server.

[0518] Step 4:

[0519] When the user approaches a destination (e.g., the Eiffel Tower), the device uses GPS to obtain its current location and transmits the location information to the drone, which then sends the information to the server.

[0520] Step 5:

[0521] The server calculates the optimal composition for the photo based on the user's current location, rating data, trend information, and real-time emotional data. For example, if the user is showing signs of joy, the server will suggest using a wide-angle composition or incorporating the surrounding scenery. This information is sent to the drone via the device.

[0522] Step 6:

[0523] The drone automatically adjusts its flight position and camera angle based on the composition information received from the server, and uses a gimbal to correct for camera shake and tilt.

[0524] Step 7:

[0525] The user operates the shooting command button on the device to send a command to the drone to start shooting, and the drone takes a photo with the specified composition.

[0526] Step 8:

[0527] After the drone takes the photo, it uses its built-in image processing algorithm to perform basic editing (adjusting brightness, color correction, applying filters, etc.) and transfers the edited photo to your device.

[0528] Step 9:

[0529] The user can review the received photos on the device and, if necessary, make additional edits to match the emotion, such as adding a specific filter to the photo or cropping it.

[0530] Step 10:

[0531] Finally, users can share the edited photos with friends via social media or email. Through this process, users can efficiently obtain high-quality photos that match their emotions and trends.

[0532] Example 2

[0533] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0534] Conventional travel photography systems require users to determine the appropriate composition and shooting location, and also operate the drone and camera themselves, which results in a lot of time and effort required for the photo shoot. It is also difficult to capture photos that reflect the user's emotions and preferences, making it difficult to obtain photos that are satisfactory. This poses a problem that reduces the enjoyment of traveling.

[0535] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0536] In this invention, the server includes means for proposing optimal photographic compositions based on user evaluation data stored in the terminal and trend information for destinations, means for transmitting user emotional data to the server via an emotion analysis device built into the terminal, and means for analyzing the user emotional data and calculating optimal photographic compositions, thereby enabling users to easily and automatically take optimal photographs that match their emotions and preferences.

[0537] A "terminal" is a portable electronic device such as a smartphone or tablet that is operated by a user.

[0538] "Rating data" refers to information about photos and reviews that users have liked and rated in the past.

[0539] "Destination trend information" is the latest popularity and rating information about destinations such as tourist spots.

[0540] The "information processing device" is a server installed on the cloud that analyzes user data and suggests optimal shooting compositions.

[0541] An "unmanned flying device" is a drone that flies automatically and is equipped with a camera to take pictures.

[0542] An "emotion analysis device" is a system that analyzes a user's voice and facial expressions to recognize emotional data.

[0543] "Emotion data" refers to emotional information analyzed based on the user's voice and facial expressions.

[0544] "Photography composition" refers to the screen composition and subject placement when taking a photograph.

[0545] As an embodiment of the present invention, a travel photography system using a terminal, a server, an unmanned aerial vehicle, and an emotion analysis device will be described. This system automatically proposes optimal photo compositions based on user evaluation data, destination trend information, and user emotion data, and the unmanned aerial vehicle automatically takes photos based on the proposed compositions.

[0546] System configuration

[0547] 1. Device: The user operates a device such as a smartphone or tablet. This device has a dedicated app installed to control the drone and use the emotion analysis device. The device is responsible for obtaining evaluation data and trend information from the server and sending it to the drone. It also analyzes the user's voice and facial expressions to recognize emotions and sends the data to the server.

[0548] 2. Server: The server is installed on the cloud and stores and analyzes user evaluation data. It also collects and analyzes trend information about destinations and calculates optimal photo compositions based on emotional data.

[0549] 3. Unmanned aerial vehicle: The unmanned aerial vehicle (drone) is equipped with a camera and automatically adjusts its flight position and camera angle based on the composition of the photo proposed by the server. It also automatically takes photos, performs basic editing, and transfers the photos to the device.

[0550] 4. Emotion Analysis Device: The emotion analysis device is built into the device and recognizes emotions by analyzing the user's voice and facial expressions. The recognized emotional data is sent to the server and used to optimize the shooting composition.

[0551] Program processing overview

[0552] The system's programming begins when the user activates the drone and pairs it with the device. The device then launches a dedicated app and connects to the drone via Bluetooth or Wi-Fi. The device then sends the user's evaluation data, trend information, and past emotional data to the server. While the user is operating the drone, an emotion analyzer built into the device analyzes the user's voice and facial expressions to recognize their emotions. This emotional data is then sent to the server in real time.

[0553] The server analyzes the evaluation data, trend information, and emotion data to calculate the optimal composition for the photo. For example, if the user is showing a very happy emotion, a composition with a wide background may be selected. The calculation results are sent to the unmanned aerial vehicle via the terminal.

[0554] The drone automatically adjusts its flight position and camera angle based on the proposed composition. When the user issues a command to start shooting, the drone automatically takes a photo. After that, the drone performs basic editing (adjusting brightness and applying filters) on the photo and transfers it to the device.

[0555] Specific examples

[0556] Next, we will show a concrete example of this system. For example, when a user visits the Eiffel Tower in Paris, they first start up the drone and pair it with their device. The device obtains the user's current location using GPS and sends it to the drone. An emotion analysis device is also running, analyzing the user's facial expressions in real time. If the user shows a happy expression with the Eiffel Tower in the background, the server will suggest the optimal composition based on that emotional data. This composition information is sent to the drone via the device, and the drone moves to the optimal position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, edits it, and transfers it to the device. The user can then review the photo, make further edits, and share it on social media.

[0557] An example of a prompt is as follows:

[0558] "When you arrive at the Eiffel Tower in Paris, simply launch the drone and pair it with your smartphone. Smile with the Eiffel Tower in the background, and the drone will calculate the optimal composition and take the photo automatically. It will then edit the photo and transfer it to your device."

[0559] This system allows users to efficiently take the best photos that suit their emotions, not only reducing the time spent taking photos while traveling but also making it easier to obtain photos that satisfy users.

[0560] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0561] Step 1:

[0562] Initial Setup and Data Synchronization

[0563] The user starts the unmanned flying device and pairs it with a smartphone (terminal).

[0564] Input: User operation (starting the drone, pairing with the device)

[0565] Specific operation: The user launches a dedicated app installed on the device and connects to the drone via Bluetooth or Wi-Fi. The device then uses its GPS function to obtain the user's current location and sends that information to the server.

[0566] Output: GPS data is sent to the server, and the server sends evaluation data, trend information, and past emotion data to the device.

[0567] Step 2:

[0568] Real-time acquisition of emotion data

[0569] The user begins operating the unmanned flying device.

[0570] Input: User operation, user voice and facial expression data

[0571] Specific operation: The emotion analysis device built into the device analyzes the user's voice and facial expressions in real time using a camera and microphone. The device then transmits this emotion data to a server in real time.

[0572] Output: The recognized emotion data is sent to the server in real time.

[0573] Step 3:

[0574] Shooting composition calculation and suggestions

[0575] The server calculates the shooting composition based on the data received.

[0576] Input: Rating data, trend information, sentiment data

[0577] Specific operation: The server analyzes the evaluation data, trend information, and emotion data to generate the optimal photo composition. For example, if the user looks happy, it uses an extensive search algorithm to suggest a composition that includes a wide background.

[0578] Output: The optimal shooting composition data is generated and sent to the device.

[0579] Step 4:

[0580] Flying and filming unmanned aerial vehicles

[0581] The unmanned flying device is operated based on the photographic composition.

[0582] Input: Shooting composition data, user's instruction to start shooting

[0583] How it works: The unmanned flying device automatically adjusts its flight position and camera angle based on composition suggestion data from the server. When the user presses the shooting button in the dedicated app, the unmanned flying device automatically releases the shutter. The camera inside the drone uses an autofocus function to set the optimal shooting conditions.

[0584] Output: The captured photo data is stored in the drone.

[0585] Step 5:

[0586] Photo editing and transfer

[0587] The drone then edits the photos and transfers them to the device.

[0588] Input: Photographed photo data

[0589] How it works: After taking a photo, the drone automatically adjusts brightness and applies filters, then transfers the edited photo to your device via Wi-Fi or Bluetooth.

[0590] Output: The edited photo data is transferred to the device and displayed to the user.

[0591] (Application example 2)

[0592] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0593] The present invention relates to a system for taking optimal advertising photos by utilizing user evaluation data, destination trend information, and emotional data. Conventional photography systems have difficulty proposing optimal compositions that reflect user emotions and real-time evaluation data, making it impossible to take advertising photos with high satisfaction. Furthermore, since there were no systems specialized for advertising photography and manual editing was required, there was a demand for efficient photography and easy editing.

[0594] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0595] In this invention, the server includes a means for proposing an optimal photographic composition based on user evaluation data stored in the terminal and trend information for the destination, a flying device that automatically adjusts the flight position and camera angle based on the photographic composition proposed by the server, a terminal that instructs the flying device to take a photograph, an emotion analysis engine that analyzes user emotion data and transmits it to the server, a means for proposing an optimal photographic composition for an advertising photograph based on the user emotion data, and a means for basic editing of the photographed advertising photograph and transferring it to the terminal. This makes it possible to efficiently take optimal advertising photographs that reflect the user's emotions and automatically perform basic editing work after photographing.

[0596] A "terminal" is an information processing device operated by a user, and specifically includes a smartphone, tablet, computer, etc.

[0597] "User evaluation data" includes information on photos, videos, etc. that users have previously evaluated, and is data that is analyzed based on those evaluations.

[0598] "Destination Trends" is data based on the latest information and popular topics related to specific locations and events.

[0599] A "server" is an information processing device that is installed on the cloud and stores, analyzes, and transmits data.

[0600] "Shooting composition" refers to suggestions for determining the optimal viewpoint and frame when taking photographs or videos.

[0601] A "flying device" is a device equipped with a camera that takes photographs by flying at a specified position and angle, and specifically includes drones.

[0602] "Emotion analysis engine" refers to software or hardware that analyzes a user's facial expressions and voice to recognize their emotions.

[0603] "Advertising photography" is photography taken for commercial or promotional purposes.

[0604] "Basic editing" refers to basic editing tasks such as adjusting brightness and applying filters to photos after they have been taken.

[0605] As an embodiment of the present invention, a system for taking advertising photographs at travel destinations, event venues, etc. This system automatically proposes optimal compositions for advertising photographs based on user evaluation data, trend information for destinations, and user emotional data, and the flying device automatically takes the photographs based on the proposed compositions.

[0606] System configuration

[0607] 1. Device:

[0608] The user operates a device such as a smartphone or tablet. A dedicated app with flight device control and emotion analysis engine functions is installed on this device. The device acquires evaluation data and trend information from the server and sends it to the flight device. It also analyzes the user's voice and facial expressions to recognize emotions and sends the data to the server.

[0609] 2. Server:

[0610] The server is installed in the cloud and stores and analyzes user evaluation data. It also collects and analyzes trend information for destinations (such as tourist spots and event venues) and calculates optimal composition for advertising photos based on emotional data.

[0611] 3. Flight equipment:

[0612] The flying device is equipped with a camera and automatically adjusts the flight position and camera angle based on the composition of the photo suggested by the server. It also automatically takes photos, performs basic editing, and transfers the photos to the device.

[0613] 4. Sentiment Analysis Engine:

[0614] The emotion analysis engine is built into the device and recognizes emotions by analyzing the user's voice and facial expressions. The recognized emotion data is sent to a server and used to optimize the shooting composition.

[0615] Processing Description

[0616] The server operates using a cloud computing service. It receives user evaluation data, destination trend information, and emotional data, and then calculates the optimal photo composition based on this data. This calculation uses a machine learning algorithm called a generative AI model. This generative AI model predicts the user's preferences and emotional state based on past data, and then suggests the optimal composition.

[0617] The user's device is a smartphone or tablet. The device is equipped with a camera and microphone, which are used to analyze the user's facial expressions and voice in real time. The analysis results are sent to the server via the device's emotion analysis engine.

[0618] A standard drone is used as the flying device. This drone is equipped with a high-resolution camera and automatically flies and takes photos according to the optimal shooting composition sent from the server. After taking the photos, it automatically performs basic editing (adjusting brightness and applying filters) and transfers the photos to the device.

[0619] Specific examples

[0620] For example, if a user visits a famous tourist spot and wants to take a photo for an advertisement, they first start the drone and pair it with the device. The device uses GPS to obtain the user's current location and sends it to the server. At the same time, an emotion analysis engine is running, analyzing the user's facial expressions and voice in real time. If the user smiles or shows a happy expression, the server uses that emotional data to suggest the optimal composition. This composition information is sent to the drone via the device, and the drone moves to the optimal position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, performs some basic editing, and then transfers the photo to the device. This system allows users to efficiently take optimal advertising photos that reflect their emotions.

[0621] Prompt Sentence Examples

[0622] "I want to take the perfect advertising photo at the Eiffel Tower in Paris."

[0623] "Please suggest advertising photos that express emotions based on the user's smile."

[0624] This system allows users to easily take high-quality advertising photos.

[0625] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0626] Step 1:

[0627] Starting the drone and pairing it with your device

[0628] The user starts the drone and pairs it with a device such as a smartphone or tablet. This pairing is done via Bluetooth or Wi-Fi. The input data is the drone's start-up signal and the device's connection request, and the output is a status indicating that pairing is complete. This pairing procedure prepares the entire system to work together and begin operation.

[0629] Step 2:

[0630] Location and emotion data acquisition

[0631] The device uses GPS to obtain the user's current location and activates the emotion analysis engine. The emotion analysis engine uses the device's camera and microphone to analyze the user's facial expressions and voice in real time and generate emotion data. The input data is camera footage, audio, and GPS information, and the output is emotion data and the current location. This allows the user's real-time emotional state and location information to be understood.

[0632] Step 3:

[0633] Sending data to the server

[0634] The device sends the acquired evaluation data, location information, trend information, and emotion data to the server. The input data is the various data collected by the device, and the output data is sent to the server. The server receives this data and prepares to calculate the optimal composition for the advertising photo based on the user's emotion and location information.

[0635] Step 4:

[0636] Calculating the composition of the photo

[0637] The server uses a generative AI model to calculate the optimal shooting composition based on the received evaluation data, trend information, and emotion data. The input data is the entire set of received data, and the output is optimal shooting composition information. This composition information includes the shooting position and camera angle. The generative AI model learns from past data and proposes the optimal composition.

[0638] Step 5:

[0639] Sending the composition

[0640] The server sends the calculated optimal shooting composition information to the drone via the terminal. The input data is the generated shooting composition information, and that information is sent to the drone as output. This allows the drone to automatically start operating based on that composition.

[0641] Step 6:

[0642] Automatic drone flight and photography

[0643] The drone moves to the optimal flight position and camera angle based on the received shooting composition information. After moving, it automatically takes photos according to the user's instructions. The input data is the shooting composition information and the user's shooting instructions, and the output is the captured photo. The drone uses a high-resolution camera to take photos that match the composition.

[0644] Step 7:

[0645] Basic photo editing and transfer

[0646] After taking a photo, the drone performs basic editing such as adjusting the brightness and applying filters to the photo. The edited photo is then transferred to the device. The input data is the captured photo, and the output is the edited photo sent to the device. This allows the user to immediately review the photo and make further edits if necessary.

[0647] Step 8:

[0648] View and share photos

[0649] Users can view the transferred photos on their devices and make further edits. They can then share them on social media. The input data is the edited photo, and the output is the shared photo or content. Through this process, users can efficiently take and share high-quality advertising photos.

[0650] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0651] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0652] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0653] [Third embodiment]

[0654] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0655] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0656] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0657] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0658] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0659] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0660] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0661] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0662] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0663] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0664] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0665] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0666] As an embodiment of the present invention, a travel photography system using a terminal, a server, and a drone will be described. This system automatically proposes optimal photo compositions based on user evaluation data and destination trend information, and the drone automatically takes photos based on the proposed compositions.

[0667] System configuration

[0668] 1. Device: The user operates a device such as a smartphone or tablet. A dedicated app for controlling the drone is installed on this device. The device's role is to obtain evaluation data and trend information from the server and send it to the drone.

[0669] 2. Server: The server is installed on the cloud and stores and analyzes user evaluation data. It also collects trend information for destinations (e.g., tourist spots) and calculates the optimal shooting composition based on the analysis results.

[0670] 3. Drone: The drone is equipped with a camera and automatically adjusts its flight position and camera angle based on the composition suggested by the server. It also automatically takes photos, performs basic editing, and transfers the photos to the device.

[0671] Program processing overview

[0672] Drone launch and data synchronization

[0673] The user activates the drone and pairs it with a smartphone (terminal). The terminal synchronizes and transmits the user's evaluation data and destination trend information from the server to the drone.

[0674] Obtaining location information and setting destination

[0675] When the user approaches the destination, the device acquires the current location using GPS. The device sends the current location information to the drone, and the server displays a list of photo spots based on the destination. The user selects a photo spot.

[0676] Preparation for shooting and composition suggestions

[0677] The server calculates the optimal composition based on the evaluation data and trend information, and transmits this information to the drone via the device. The drone then sets the appropriate flight position and angle based on the proposed composition.

[0678] Automated shooting and editing

[0679] When the user presses the camera button on the device, the drone takes a photo with the specified composition. After taking the photo, the drone performs basic editing (adjusting brightness, applying filters, etc.) and transfers the photo to the device. The user can then view the photo on the device, make further edits, or share it on social media.

[0680] Specific examples

[0681] For example, when a user visits the Eiffel Tower in Paris, they start up the drone and pair it with their device. The device uses GPS to obtain the user's current location and sends it to the drone. The server calculates the optimal composition for taking a photo of the Eiffel Tower (e.g., "a full-body photo with the Eiffel Tower in the background") based on evaluation data and trend information. This information is sent to the drone via the device, and the drone moves to the appropriate position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, performs basic editing, and transfers it to the device. The user can review the photo, edit it if necessary, and share it with friends.

[0682] This system allows users to reduce the time it takes to take individual photos and easily obtain higher quality photos, which increases the enjoyment of travel and improves user satisfaction.

[0683] The processing flow will be explained below.

[0684] Step 1:

[0685] The user starts the drone and pairs it with the smartphone (device), which then launches a dedicated app and connects to the drone via Bluetooth or Wi-Fi.

[0686] Step 2:

[0687] The device sends the user's rating data (such as photos and videos that they have "liked" in the past) to the server, which receives and analyzes this data.

[0688] Step 3:

[0689] The server analyzes the evaluation data to understand the user's preferences and photography trends, and then collects and analyzes trend information for the destination (popular photo spots and composition).

[0690] Step 4:

[0691] When the user arrives at their travel destination (e.g., the Eiffel Tower), the device uses GPS to obtain their current location, which is then transmitted to the drone, which then sends the information to the server.

[0692] Step 5:

[0693] The server calculates the optimal composition based on the user's current location, rating data, and trend information. For example, it suggests a photo with the Eiffel Tower in the background or a composition shot from a specific angle.

[0694] Step 6:

[0695] The server calculates the composition and sends it to the drone via the device, which then automatically sets the appropriate flight position and camera angle based on the proposed composition.

[0696] Step 7:

[0697] The user operates the shooting instruction button on the device to send a command to the drone to start shooting, and the drone takes a photo with the specified composition.

[0698] Step 8:

[0699] After the drone captures the footage, it performs some basic editing (adjusting brightness, applying filters, etc.) automatically using internal image processing algorithms.

[0700] Step 9:

[0701] The drone then transfers the edited photos to the device, where the user can review them and make further edits if necessary.

[0702] Step 10:

[0703] Finally, users can share the edited photos with friends via social media or email. This process allows users to efficiently and easily obtain high-quality photos.

[0704] Example 1

[0705] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0706] When traveling and visiting beautiful landscapes and famous places, there is a demand for easy, high-quality photos with optimal composition, but this can be a difficult task for users without photography skills. Another problem is that the time spent taking photos reduces the time available to enjoy sightseeing. Furthermore, taking photos using drones requires technical operations that are difficult for average users to operate. There is a demand for a system that solves these problems and allows anyone to easily take high-quality photos.

[0707] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0708] In this invention, the server includes a means for suggesting optimal photo compositions based on user evaluation data stored in the terminal and trend information for destinations, a means for analyzing data on photos that the user has previously liked and rated, and a means for acquiring current location information using a GPS function and generating a list of photo spots, thereby enabling users to easily take high-quality, memorable photos while minimizing the amount of work required.

[0709] The "information processing device" is a computer system that has the function of proposing optimal photographic compositions based on user evaluation data and trend information about destinations.

[0710] An "unmanned aerial vehicle" is a device that automatically adjusts the flight position and camera angle based on the shooting composition proposed by the server, and takes and edits photographs.

[0711] An "information terminal device" is a device operated by a user to instruct an unmanned aerial vehicle to take photos and obtain current location information via GPS, and includes smartphones, tablets, and the like.

[0712] "User evaluation data" refers to data relating to photos taken by the user in the past, evaluations made by the user, and preferences.

[0713] "Trending information" is information about the general popularity or current topics of a particular destination.

[0714] "Photography composition" refers to the photographic conditions, such as the subject placement, camera angle, and focal length, when taking a photograph.

[0715] "GPS function" refers to technology that uses the Global Positioning System to obtain current latitude and longitude location information.

[0716] A "generative AI model" is a model that uses artificial intelligence algorithms to generate new shooting compositions and data patterns.

[0717] The "photography spot list" is a list of multiple candidate photo shooting locations that the server proposes based on the user's current location information.

[0718] "Basic editing" refers to the process of performing basic image processing on photographs, such as adjusting brightness and applying filters.

[0719] As an embodiment of the present invention, a system for enabling a user to take optimal photographs while traveling will be described. This system is configured using an information processing device (server), an information terminal device (terminal), and an unmanned aerial vehicle (drone).

[0720] First, the user activates the drone at their travel destination and pairs it with the device using a dedicated app. The device then connects to an information processing device and obtains the user's evaluation data and trend information for the destination. This evaluation data and trend information are stored in the cloud database of the information processing device.

[0721] Next, the terminal acquires the user's current location using its GPS function and sends it to the information processing device. The information processing device generates a photo spot list based on the acquired current location information and sends it to the user's terminal. The user selects a spot they want to take a photo from the photo spot list displayed on the terminal.

[0722] The information processing device uses a generative AI model to propose the optimal composition for the shot. The proposed composition is then sent to the drone via the device. The drone then automatically sets its flight position and camera angle based on the proposed composition.

[0723] When the user presses the shooting button on the dedicated app, the drone takes a photo with the specified composition. After taking the photo, the drone performs basic editing (adjusting brightness, applying filters, etc.) and transfers the edited photo to the device. The user can then review the transferred photo, make further edits as needed, or share it on social media.

[0724] For example, when a user visits the Eiffel Tower in Paris, they start up the drone and pair it with the device. The device uses GPS to obtain the user's current location and sends it to the information processing device. The information processing device calculates the optimal composition for taking a photo of the Eiffel Tower (e.g., "a full-body photo with the Eiffel Tower in the background") based on evaluation data and trend information, and sends this information to the drone via the device. The drone moves to an appropriate position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, performs basic editing, and transfers it to the device. The user can review the photo, edit it if necessary, and share it with friends.

[0725] An example of a prompt sentence is, "I'm sightseeing at the Eiffel Tower in Paris. I want to take the best photo. Where should I take the photo and what is the best composition?"

[0726] This system allows users to reduce the time it takes to take individual photos and easily obtain high-quality photographs, thereby increasing the enjoyment of travel and improving user satisfaction.

[0727] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0728] Step 1:

[0729] The user starts the drone and pairs it with the device using a dedicated app. The input is for the user to turn on the drone, start the app, and perform the pairing process. The output is for the device and drone to connect via Bluetooth or Wi-Fi. Specifically, the user selects "Start pairing" in the app and presses the pairing button on the drone, which links the device and drone.

[0730] Step 2:

[0731] After pairing is complete, the device connects to an information processing device (server) on the cloud and obtains evaluation data and trend information. The user's identification information and location information are sent to the server as input. Based on this data, the server sends the user's evaluation data and destination trend information to the device as output. In concrete terms, the device sends a request to the server via an internet connection and performs communication processing to obtain the required data.

[0732] Step 3:

[0733] The device uses its GPS function to obtain the user's current location. As input, location data is obtained from the device's GPS sensor. As output, current location information is generated and sent to the server. Specifically, the device continuously monitors the user's current location and sends the obtained data to the server in real time.

[0734] Step 4:

[0735] The server generates a list of photo spots based on the acquired current location information. The input includes the user's current location information and trend information. The output is a list of photo spots that is generated and sent to the device. Specifically, the server performs a database search and AI analysis to create a list of popular spots near the user's current location.

[0736] Step 5:

[0737] The user selects a photo spot from the photo spot list displayed on the device. The photo spot list sent from the server is displayed as input. The selected photo spot information is saved on the device as output. In concrete terms, the user selects a photo spot using the touch screen and presses the confirm button.

[0738] Step 6:

[0739] The server uses a generative AI model to calculate the optimal composition based on the selected photo spot information. Inputs include user evaluation data, trend information, and selected photo spot information. As output, optimal composition data is generated and sent to the device. Specifically, the server runs the AI ​​model, calculates the optimal composition within a few seconds, and sends the results.

[0740] Step 7:

[0741] The terminal transfers the received shooting composition data to the drone. The input includes the shooting composition data from the server. The output is the composition data sent to the drone. Specifically, the terminal sends the data to the drone via wireless communication.

[0742] Step 8:

[0743] The drone automatically sets its flight position and camera angle based on the received composition data. The input includes the shooting composition data from the device. The output is the flight position and camera angle. The drone uses GPS and internal sensors to navigate to the appropriate position and adjust the camera angle.

[0744] Step 9:

[0745] When the user operates the camera button on the device, the drone automatically takes a photo. The input includes the user's shooting instructions. The output is the captured photo data. Specifically, the user taps the camera button on the device, and the drone takes a picture.

[0746] Step 10:

[0747] The drone performs some basic editing on the captured photos and transmits them to the device. The input includes the raw image data captured. The output is the edited photo data sent to the device. Specifically, the drone uses internal algorithms to adjust brightness and apply filters, and transmits the image to the device via wireless communication.

[0748] Step 11:

[0749] The user can then review the photos received on their device, make further edits, or share them on social media. The input includes the edited photo data transferred from the drone. The output is the user's final edited photo or the photo data they want to share. Specifically, the user uses the editing functions on their device to edit the photo and then posts it to social media using the share button.

[0750] In this way, users can easily take and share high-quality photos through individual processing steps.

[0751] (Application example 1)

[0752] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0753] Conventional product inspection methods are primarily performed manually, which is problematic due to low efficiency and inconsistent quality. Manual inspection is also time-consuming and can undermine overall factory productivity. Furthermore, inspection results often vary depending on the level of expertise of workers, making the process unreliable. There is a need for technology that can solve these issues and automate product quality inspection while improving efficiency and accuracy.

[0754] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0755] In this invention, the server includes a means for suggesting optimal shooting compositions based on user evaluation data stored on a terminal and trend information for the destination, a drone or robot that automatically adjusts its flight position and camera angle based on the shooting composition suggested by the server, a terminal that issues shooting instructions to the drone or robot, and an AI image analysis model that analyzes the captured image data and detects abnormalities. This enables the automation of product quality inspections, improving the efficiency and accuracy of inspections. It also contributes to alleviating labor shortages and improving productivity.

[0756] A "terminal" is a device operated by a user, specifically a smartphone or tablet, which is a means of controlling drones and robots via a dedicated app.

[0757] The "server" is a device installed on the cloud that stores and analyzes user evaluation data and trend information, and calculates and provides optimal shooting compositions and inspection methods.

[0758] "Drone or robot" means a mobile device that moves autonomously to take photographs or perform inspections and collect data through cameras and sensors.

[0759] The "AI image analysis model" is an artificial intelligence machine learning model that analyzes captured image data and detects abnormalities, and performs quality inspections using image processing technology.

[0760] A "prompt" is an instruction used to have the AI ​​image analysis model detect abnormalities, and is text data used to provide the AI ​​with specific inspection details and criteria.

[0761] MODE FOR CARRYING OUT THE INVENTION

[0762] As an embodiment of the present invention, an automatic product quality inspection system using a terminal, a server, and a robot will be described. This system automatically proposes optimal inspection methods and compositions based on product quality data and trend information related to inspection, and the robot then automatically performs the inspection based on these.

[0763] System configuration

[0764] 1. Terminal: Quality control personnel operate a terminal such as a smartphone or tablet. A dedicated app for controlling the robot is installed on this terminal. The terminal's role is to obtain quality data and trend information from the server and send it to the robot.

[0765] 2. Server: The server is installed in the cloud and stores and analyzes quality data. It also collects trend information on the production line and inspection environment, and calculates the optimal inspection method and composition based on the analysis results.

[0766] 3. Robot: The robot is equipped with a camera and sensors, and automatically adjusts its position and the angle of the camera and sensor based on the inspection method and composition proposed by the server. It also automatically performs inspections, performs basic data analysis, and transfers the results to a terminal.

[0767] Program processing overview

[0768] Robot startup and data synchronization

[0769] A quality control officer activates the robot and pairs it with a smartphone (terminal), which then synchronizes quality data and trend information from the server and sends it to the robot.

[0770] Obtaining and setting inspection locations

[0771] The terminal acquires the position information of the production line and sends it to the robot. The server displays a list of inspection spots based on the production line. The quality control personnel selects an inspection spot.

[0772] Inspection preparation and composition proposal

[0773] The server calculates the optimal inspection method and composition based on quality data and trend information, and sends this information to the robot via a terminal. The robot then sets the appropriate movement position and angle based on the proposed inspection method.

[0774] Automated Inspection and Data Collection

[0775] When a quality control officer presses the inspection button on the terminal, the robot performs an inspection according to the specified composition. After the inspection, the robot performs basic data analysis (such as detecting anomalies) and transfers the results to the terminal. The quality control officer checks the inspection results on the terminal and performs further analysis and recording.

[0776] Specific examples

[0777] For example, on an electrical appliance production line, a quality control officer activates a robot and pairs it with a terminal. The terminal obtains information about the production line's location and sends it to the robot. The server calculates the optimal inspection method and composition (e.g., "camera angle and position to detect wiring errors") based on quality data and trend information. This information is sent to the robot via the terminal, and the robot moves to the appropriate position and adjusts the camera and sensor angles. When the quality control officer presses the inspection button, the robot automatically inspects the product, and if it detects an abnormality, it transfers the results, including information about it, to the terminal. The quality control officer checks this data and, if necessary, records it or conducts further inspection.

[0778] Example prompt sentence:

[0779] Inspect products on the production line to detect defects. Specifically, check the following:

[0780] 1. Wiring error

[0781] 2. Surface scratches

[0782] 3. Missing parts

[0783] Please use the image data and specify the location if an anomaly is detected.

[0784] This system will reduce the time required for product quality inspection and improve the rate at which defective products are detected, while also helping to alleviate labor shortages and improve the efficiency of production lines.

[0785] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0786] Step 1:

[0787] The user starts the robot and pairs it with a device (smartphone or tablet). The device obtains the user's evaluation data and inspection trend information from the cloud server and sends it to the robot. The input in this step is the user's operation and data obtained from the server, and the output is the inspection data sent to the robot.

[0788] Step 2:

[0789] The terminal acquires the location information of the production line and sends it to the server. The server generates an inspection spot list for the production line based on this location information and displays it on the terminal. The input in this step is the location information of the production line, and the output is the inspection spot list generated by the server.

[0790] Step 3:

[0791] The user selects an inspection spot on the terminal and sends that information to the robot. Based on the selected inspection spot, the server analyzes past quality data and trend information and calculates the optimal inspection method and composition. This generates data for the robot to move to the optimal position and set the camera and sensor angles. The input in this step is the inspection spot selected by the user, quality data, and trend information, and the output is the composition and movement position data sent to the robot.

[0792] Step 4:

[0793] The server calculates the optimal inspection method and composition based on the quality data and trend information, and sends that information to the robot via the terminal. The robot moves to an appropriate position based on the proposed inspection method and sets the camera and sensor angles. The input in this step is the quality data and trend information received from the server, and the output is the robot's movement position and camera / sensor setting information.

[0794] Step 5:

[0795] When the user operates the inspection button on the terminal, the robot inspects the product using the specified composition. The robot sends the captured image data and sensor information to a cloud server, which then uses an AI model to analyze the image and detect any abnormalities. The input in this step is the image data and sensor information acquired by the robot, and the output is the analysis results of the abnormality detection by the server.

[0796] Step 6:

[0797] Based on the analysis results, the server notifies the terminal of any abnormalities or problems. The user checks these analysis results on the terminal, and records or further examines them as necessary. The input in this step is the analysis results from the server, and the output is the inspection results displayed on the terminal.

[0798] Step 7:

[0799] The server uses the generative AI model to automatically generate prompts for anomaly detection and provide the user with recommendations for the next inspection and improvement measures. The inputs in this step are the analysis results and past quality data, and the output is the generated prompts.

[0800] Example prompt sentence:

[0801] Inspect products on the production line to detect defects. Specifically, check the following:

[0802] 1. Wiring error

[0803] 2. Surface scratches

[0804] 3. Missing parts

[0805] Please use the image data and specify the location if an anomaly is detected.

[0806] These steps enable the automation of product quality inspections and the detection of abnormalities with high accuracy and efficiency.

[0807] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0808] As an embodiment of the present invention, a travel photography system using a terminal, a server, a drone, and an emotion engine will be described. This system automatically proposes optimal photo compositions based on user evaluation data, destination trend information, and user emotion data, and the drone automatically takes photos based on the proposed compositions.

[0809] System configuration

[0810] 1. Device: The user operates a device such as a smartphone or tablet. A dedicated app with drone control and emotion engine functions is installed on this device. The device acquires evaluation data and trend information from the server and transmits it to the drone. It also analyzes the user's voice and facial expressions to recognize emotions and transmits the data to the server.

[0811] 2. Server: The server is installed in the cloud and stores and analyzes user evaluation data. It also collects and analyzes trend information for destinations (such as tourist spots) and calculates optimal photo compositions based on emotional data.

[0812] 3. Drone: The drone is equipped with a camera and automatically adjusts its flight position and camera angle based on the composition suggested by the server. It also automatically takes photos, performs basic editing, and transfers the photos to the device.

[0813] 4. Emotion Engine: The emotion engine is built into the device and analyzes the user's voice and facial expressions to recognize emotions. The recognized emotion data is sent to the server and used to optimize the shooting composition.

[0814] Program processing overview

[0815] Drone launch and data synchronization

[0816] The user activates the drone and pairs it with their smartphone (device). The device then launches a dedicated app and connects to the drone via Bluetooth or Wi-Fi. The device then sends the user's evaluation data, trend information, and past emotion data to the server.

[0817] Acquiring emotion data

[0818] While the user is operating the drone, an emotion engine built into the device analyzes the user's voice and facial expressions to recognize their emotions, and this emotion data is sent to a server in real time.

[0819] Composition suggestions

[0820] The server analyzes the user's rating data, trend information, and emotional data to calculate the optimal composition for the photo. For example, if the user is showing signs of great enjoyment, a composition with a wide background may be selected. The results of this calculation are sent to the drone via the device.

[0821] Drone movement and filming

[0822] The drone automatically adjusts its flight position and camera angle based on the composition of the shot. When the user commands the drone to start shooting, it automatically takes a photo. After that, the drone performs basic editing (adjusting brightness and applying filters) on the photo and transfers it to the device.

[0823] Specific examples

[0824] A specific example of this system is shown below. For example, when a user visits the Eiffel Tower in Paris, they first start up the drone and pair it with the device. The device obtains the user's current location using GPS and sends it to the drone. The emotion engine is also running, analyzing the user's facial expressions in real time. If the user shows a happy expression with the Eiffel Tower in the background, the server will suggest the optimal composition based on that emotional data. This composition information is sent to the drone via the device, and the drone moves to the optimal position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, edits it, and transfers it to the device. The user can then review the photo, make further edits, and share it on social media.

[0825] This system allows users to efficiently take the best photos that suit their emotions, not only reducing the time spent taking photos while traveling but also making it easier to obtain photos that they are satisfied with.

[0826] The processing flow will be explained below.

[0827] Step 1:

[0828] The user starts the drone and pairs it with the smartphone (device), which then launches a dedicated app and connects to the drone via Bluetooth or Wi-Fi.

[0829] Step 2:

[0830] The device connects to the server, obtains user evaluation data and trend information, and synchronizes it with the drone. It also obtains previously saved emotion data from the server.

[0831] Step 3:

[0832] The device uses a camera and microphone to monitor the user's voice and facial expressions in real time, and analyzes their emotions using an emotion engine. For example, it analyzes smiles, surprised expressions, tone of voice, etc. to obtain emotional data. This emotional data is then sent to a server.

[0833] Step 4:

[0834] When the user approaches a destination (e.g., the Eiffel Tower), the device uses GPS to obtain its current location and transmits the location information to the drone, which then sends the information to the server.

[0835] Step 5:

[0836] The server calculates the optimal composition for the photo based on the user's current location, rating data, trend information, and real-time emotional data. For example, if the user is showing signs of joy, the server will suggest using a wide-angle composition or incorporating the surrounding scenery. This information is sent to the drone via the device.

[0837] Step 6:

[0838] The drone automatically adjusts its flight position and camera angle based on the composition information received from the server, and uses a gimbal to correct for camera shake and tilt.

[0839] Step 7:

[0840] The user operates the shooting command button on the device to send a command to the drone to start shooting, and the drone takes a photo with the specified composition.

[0841] Step 8:

[0842] After the drone takes the photo, it uses its built-in image processing algorithm to perform basic editing (adjusting brightness, color correction, applying filters, etc.) and transfers the edited photo to your device.

[0843] Step 9:

[0844] The user can review the received photos on the device and, if necessary, make additional edits to match the emotion, such as adding a specific filter to the photo or cropping it.

[0845] Step 10:

[0846] Finally, users can share the edited photos with friends via social media or email. Through this process, users can efficiently obtain high-quality photos that match their emotions and trends.

[0847] Example 2

[0848] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0849] Conventional travel photography systems require users to determine the appropriate composition and shooting location, and also operate the drone and camera themselves, which results in a lot of time and effort required for the photo shoot. It is also difficult to capture photos that reflect the user's emotions and preferences, making it difficult to obtain photos that are satisfactory. This poses a problem that reduces the enjoyment of traveling.

[0850] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0851] In this invention, the server includes means for proposing optimal photographic compositions based on user evaluation data stored in the terminal and trend information for destinations, means for transmitting user emotional data to the server via an emotion analysis device built into the terminal, and means for analyzing the user emotional data and calculating optimal photographic compositions, thereby enabling users to easily and automatically take optimal photographs that match their emotions and preferences.

[0852] A "terminal" is a portable electronic device such as a smartphone or tablet that is operated by a user.

[0853] "Rating data" refers to information about photos and reviews that users have liked and rated in the past.

[0854] "Destination trend information" is the latest popularity and rating information about destinations such as tourist spots.

[0855] The "information processing device" is a server installed on the cloud that analyzes user data and suggests optimal shooting compositions.

[0856] An "unmanned flying device" is a drone that flies automatically and is equipped with a camera to take pictures.

[0857] An "emotion analysis device" is a system that analyzes a user's voice and facial expressions to recognize emotional data.

[0858] "Emotion data" refers to emotional information analyzed based on the user's voice and facial expressions.

[0859] "Photography composition" refers to the screen composition and subject placement when taking a photograph.

[0860] As an embodiment of the present invention, a travel photography system using a terminal, a server, an unmanned aerial vehicle, and an emotion analysis device will be described. This system automatically proposes optimal photo compositions based on user evaluation data, destination trend information, and user emotion data, and the unmanned aerial vehicle automatically takes photos based on the proposed compositions.

[0861] System configuration

[0862] 1. Device: The user operates a device such as a smartphone or tablet. This device has a dedicated app installed to control the drone and use the emotion analysis device. The device is responsible for obtaining evaluation data and trend information from the server and sending it to the drone. It also analyzes the user's voice and facial expressions to recognize emotions and sends the data to the server.

[0863] 2. Server: The server is installed on the cloud and stores and analyzes user evaluation data. It also collects and analyzes trend information about destinations and calculates optimal photo compositions based on emotional data.

[0864] 3. Unmanned aerial vehicle: The unmanned aerial vehicle (drone) is equipped with a camera and automatically adjusts its flight position and camera angle based on the composition of the photo proposed by the server. It also automatically takes photos, performs basic editing, and transfers the photos to the device.

[0865] 4. Emotion Analysis Device: The emotion analysis device is built into the device and recognizes emotions by analyzing the user's voice and facial expressions. The recognized emotional data is sent to the server and used to optimize the shooting composition.

[0866] Program processing overview

[0867] The system's programming begins when the user activates the drone and pairs it with the device. The device then launches a dedicated app and connects to the drone via Bluetooth or Wi-Fi. The device then sends the user's evaluation data, trend information, and past emotional data to the server. While the user is operating the drone, an emotion analyzer built into the device analyzes the user's voice and facial expressions to recognize their emotions. This emotional data is then sent to the server in real time.

[0868] The server analyzes the evaluation data, trend information, and emotion data to calculate the optimal composition for the photo. For example, if the user is showing a very happy emotion, a composition with a wide background may be selected. The calculation results are sent to the unmanned aerial vehicle via the terminal.

[0869] The drone automatically adjusts its flight position and camera angle based on the proposed composition. When the user issues a command to start shooting, the drone automatically takes a photo. After that, the drone performs basic editing (adjusting brightness and applying filters) on the photo and transfers it to the device.

[0870] Specific examples

[0871] Next, we will show a concrete example of this system. For example, when a user visits the Eiffel Tower in Paris, they first start up the drone and pair it with their device. The device obtains the user's current location using GPS and sends it to the drone. An emotion analysis device is also running, analyzing the user's facial expressions in real time. If the user shows a happy expression with the Eiffel Tower in the background, the server will suggest the optimal composition based on that emotional data. This composition information is sent to the drone via the device, and the drone moves to the optimal position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, edits it, and transfers it to the device. The user can then review the photo, make further edits, and share it on social media.

[0872] An example of a prompt is as follows:

[0873] "When you arrive at the Eiffel Tower in Paris, simply launch the drone and pair it with your smartphone. Smile with the Eiffel Tower in the background, and the drone will calculate the optimal composition and take the photo automatically. It will then edit the photo and transfer it to your device."

[0874] This system allows users to efficiently take the best photos that suit their emotions, not only reducing the time spent taking photos while traveling but also making it easier to obtain photos that satisfy users.

[0875] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0876] Step 1:

[0877] Initial Setup and Data Synchronization

[0878] The user starts the unmanned flying device and pairs it with a smartphone (terminal).

[0879] Input: User operation (starting the drone, pairing with the device)

[0880] Specific operation: The user launches a dedicated app installed on the device and connects to the drone via Bluetooth or Wi-Fi. The device then uses its GPS function to obtain the user's current location and sends that information to the server.

[0881] Output: GPS data is sent to the server, and the server sends evaluation data, trend information, and past emotion data to the device.

[0882] Step 2:

[0883] Real-time acquisition of emotion data

[0884] The user begins operating the unmanned flying device.

[0885] Input: User operation, user voice and facial expression data

[0886] Specific operation: The emotion analysis device built into the device analyzes the user's voice and facial expressions in real time using a camera and microphone. The device then transmits this emotion data to a server in real time.

[0887] Output: The recognized emotion data is sent to the server in real time.

[0888] Step 3:

[0889] Shooting composition calculation and suggestions

[0890] The server calculates the shooting composition based on the data received.

[0891] Input: Rating data, trend information, sentiment data

[0892] Specific operation: The server analyzes the evaluation data, trend information, and emotion data to generate the optimal photo composition. For example, if the user looks happy, it uses an extensive search algorithm to suggest a composition that includes a wide background.

[0893] Output: The optimal shooting composition data is generated and sent to the device.

[0894] Step 4:

[0895] Flying and filming unmanned aerial vehicles

[0896] The unmanned flying device is operated based on the photographic composition.

[0897] Input: Shooting composition data, user's instruction to start shooting

[0898] How it works: The unmanned flying device automatically adjusts its flight position and camera angle based on composition suggestion data from the server. When the user presses the shooting button in the dedicated app, the unmanned flying device automatically releases the shutter. The camera inside the drone uses an autofocus function to set the optimal shooting conditions.

[0899] Output: The captured photo data is stored in the drone.

[0900] Step 5:

[0901] Photo editing and transfer

[0902] The drone then edits the photos and transfers them to the device.

[0903] Input: Photographed photo data

[0904] How it works: After taking a photo, the drone automatically adjusts brightness and applies filters, then transfers the edited photo to your device via Wi-Fi or Bluetooth.

[0905] Output: The edited photo data is transferred to the device and displayed to the user.

[0906] (Application example 2)

[0907] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0908] The present invention relates to a system for taking optimal advertising photos by utilizing user evaluation data, destination trend information, and emotional data. Conventional photography systems have difficulty proposing optimal compositions that reflect user emotions and real-time evaluation data, making it impossible to take advertising photos with high satisfaction. Furthermore, since there were no systems specialized for advertising photography and manual editing was required, there was a demand for efficient photography and easy editing.

[0909] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0910] In this invention, the server includes a means for proposing an optimal photographic composition based on user evaluation data stored in the terminal and trend information for the destination, a flying device that automatically adjusts the flight position and camera angle based on the photographic composition proposed by the server, a terminal that instructs the flying device to take a photograph, an emotion analysis engine that analyzes user emotion data and transmits it to the server, a means for proposing an optimal photographic composition for an advertising photograph based on the user emotion data, and a means for basic editing of the photographed advertising photograph and transferring it to the terminal. This makes it possible to efficiently take optimal advertising photographs that reflect the user's emotions and automatically perform basic editing work after photographing.

[0911] A "terminal" is an information processing device operated by a user, and specifically includes a smartphone, tablet, computer, etc.

[0912] "User evaluation data" includes information on photos, videos, etc. that users have previously evaluated, and is data that is analyzed based on those evaluations.

[0913] "Destination Trends" is data based on the latest information and popular topics related to specific locations and events.

[0914] A "server" is an information processing device that is installed on the cloud and stores, analyzes, and transmits data.

[0915] "Shooting composition" refers to suggestions for determining the optimal viewpoint and frame when taking photographs or videos.

[0916] A "flying device" is a device equipped with a camera that takes photographs by flying at a specified position and angle, and specifically includes drones.

[0917] "Emotion analysis engine" refers to software or hardware that analyzes a user's facial expressions and voice to recognize their emotions.

[0918] "Advertising photography" is photography taken for commercial or promotional purposes.

[0919] "Basic editing" refers to basic editing tasks such as adjusting brightness and applying filters to photos after they have been taken.

[0920] As an embodiment of the present invention, a system for taking advertising photographs at travel destinations, event venues, etc. This system automatically proposes optimal compositions for advertising photographs based on user evaluation data, trend information for destinations, and user emotional data, and the flying device automatically takes the photographs based on the proposed compositions.

[0921] System configuration

[0922] 1. Device:

[0923] The user operates a device such as a smartphone or tablet. A dedicated app with flight device control and emotion analysis engine functions is installed on this device. The device acquires evaluation data and trend information from the server and sends it to the flight device. It also analyzes the user's voice and facial expressions to recognize emotions and sends the data to the server.

[0924] 2. Server:

[0925] The server is installed in the cloud and stores and analyzes user evaluation data. It also collects and analyzes trend information for destinations (such as tourist spots and event venues) and calculates optimal composition for advertising photos based on emotional data.

[0926] 3. Flight equipment:

[0927] The flying device is equipped with a camera and automatically adjusts the flight position and camera angle based on the composition of the photo suggested by the server. It also automatically takes photos, performs basic editing, and transfers the photos to the device.

[0928] 4. Sentiment Analysis Engine:

[0929] The emotion analysis engine is built into the device and recognizes emotions by analyzing the user's voice and facial expressions. The recognized emotion data is sent to a server and used to optimize the shooting composition.

[0930] Processing Description

[0931] The server operates using a cloud computing service. It receives user evaluation data, destination trend information, and emotional data, and then calculates the optimal photo composition based on this data. This calculation uses a machine learning algorithm called a generative AI model. This generative AI model predicts the user's preferences and emotional state based on past data, and then suggests the optimal composition.

[0932] The user's device is a smartphone or tablet. The device is equipped with a camera and microphone, which are used to analyze the user's facial expressions and voice in real time. The analysis results are sent to the server via the device's emotion analysis engine.

[0933] A standard drone is used as the flying device. This drone is equipped with a high-resolution camera and automatically flies and takes photos according to the optimal shooting composition sent from the server. After taking the photos, it automatically performs basic editing (adjusting brightness and applying filters) and transfers the photos to the device.

[0934] Specific examples

[0935] For example, if a user visits a famous tourist spot and wants to take a photo for an advertisement, they first start the drone and pair it with the device. The device uses GPS to obtain the user's current location and sends it to the server. At the same time, an emotion analysis engine is running, analyzing the user's facial expressions and voice in real time. If the user smiles or shows a happy expression, the server uses that emotional data to suggest the optimal composition. This composition information is sent to the drone via the device, and the drone moves to the optimal position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, performs some basic editing, and then transfers the photo to the device. This system allows users to efficiently take optimal advertising photos that reflect their emotions.

[0936] Prompt Sentence Examples

[0937] "I want to take the perfect advertising photo at the Eiffel Tower in Paris."

[0938] "Please suggest advertising photos that express emotions based on the user's smile."

[0939] This system allows users to easily take high-quality advertising photos.

[0940] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0941] Step 1:

[0942] Starting the drone and pairing it with your device

[0943] The user starts the drone and pairs it with a device such as a smartphone or tablet. This pairing is done via Bluetooth or Wi-Fi. The input data is the drone's start-up signal and the device's connection request, and the output is a status indicating that pairing is complete. This pairing procedure prepares the entire system to work together and begin operation.

[0944] Step 2:

[0945] Location and emotion data acquisition

[0946] The device uses GPS to obtain the user's current location and activates the emotion analysis engine. The emotion analysis engine uses the device's camera and microphone to analyze the user's facial expressions and voice in real time and generate emotion data. The input data is camera footage, audio, and GPS information, and the output is emotion data and the current location. This allows the user's real-time emotional state and location information to be understood.

[0947] Step 3:

[0948] Sending data to the server

[0949] The device sends the acquired evaluation data, location information, trend information, and emotion data to the server. The input data is the various data collected by the device, and the output data is sent to the server. The server receives this data and prepares to calculate the optimal composition for the advertising photo based on the user's emotion and location information.

[0950] Step 4:

[0951] Calculating the composition of the photo

[0952] The server uses a generative AI model to calculate the optimal shooting composition based on the received evaluation data, trend information, and emotion data. The input data is the entire set of received data, and the output is optimal shooting composition information. This composition information includes the shooting position and camera angle. The generative AI model learns from past data and proposes the optimal composition.

[0953] Step 5:

[0954] Sending the composition

[0955] The server sends the calculated optimal shooting composition information to the drone via the terminal. The input data is the generated shooting composition information, and that information is sent to the drone as output. This allows the drone to automatically start operating based on that composition.

[0956] Step 6:

[0957] Automatic drone flight and photography

[0958] The drone moves to the optimal flight position and camera angle based on the received shooting composition information. After moving, it automatically takes photos according to the user's instructions. The input data is the shooting composition information and the user's shooting instructions, and the output is the captured photo. The drone uses a high-resolution camera to take photos that match the composition.

[0959] Step 7:

[0960] Basic photo editing and transfer

[0961] After taking a photo, the drone performs basic editing such as adjusting the brightness and applying filters to the photo. The edited photo is then transferred to the device. The input data is the captured photo, and the output is the edited photo sent to the device. This allows the user to immediately review the photo and make further edits if necessary.

[0962] Step 8:

[0963] View and share photos

[0964] Users can view the transferred photos on their devices and make further edits. They can then share them on social media. The input data is the edited photo, and the output is the shared photo or content. Through this process, users can efficiently take and share high-quality advertising photos.

[0965] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0966] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0967] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[0968] [Fourth embodiment]

[0969] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0970] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0971] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0972] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0973] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0974] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0975] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0976] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0977] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0978] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0979] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0980] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0981] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[0982] As an embodiment of the present invention, a travel photography system using a terminal, a server, and a drone will be described. This system automatically proposes optimal photo compositions based on user evaluation data and destination trend information, and the drone automatically takes photos based on the proposed compositions.

[0983] System configuration

[0984] 1. Device: The user operates a device such as a smartphone or tablet. A dedicated app for controlling the drone is installed on this device. The device's role is to obtain evaluation data and trend information from the server and send it to the drone.

[0985] 2. Server: The server is installed on the cloud and stores and analyzes user evaluation data. It also collects trend information for destinations (e.g., tourist spots) and calculates the optimal shooting composition based on the analysis results.

[0986] 3. Drone: The drone is equipped with a camera and automatically adjusts its flight position and camera angle based on the composition suggested by the server. It also automatically takes photos, performs basic editing, and transfers the photos to the device.

[0987] Program processing overview

[0988] Drone launch and data synchronization

[0989] The user activates the drone and pairs it with a smartphone (terminal). The terminal synchronizes and transmits the user's evaluation data and destination trend information from the server to the drone.

[0990] Obtaining location information and setting destination

[0991] When the user approaches the destination, the device acquires the current location using GPS. The device sends the current location information to the drone, and the server displays a list of photo spots based on the destination. The user selects a photo spot.

[0992] Preparation for shooting and composition suggestions

[0993] The server calculates the optimal composition based on the evaluation data and trend information, and transmits this information to the drone via the device. The drone then sets the appropriate flight position and angle based on the proposed composition.

[0994] Automated shooting and editing

[0995] When the user presses the camera button on the device, the drone takes a photo with the specified composition. After taking the photo, the drone performs basic editing (adjusting brightness, applying filters, etc.) and transfers the photo to the device. The user can then view the photo on the device, make further edits, or share it on social media.

[0996] Specific examples

[0997] For example, when a user visits the Eiffel Tower in Paris, they start up the drone and pair it with their device. The device uses GPS to obtain the user's current location and sends it to the drone. The server calculates the optimal composition for taking a photo of the Eiffel Tower (e.g., "a full-body photo with the Eiffel Tower in the background") based on evaluation data and trend information. This information is sent to the drone via the device, and the drone moves to the appropriate position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, performs basic editing, and transfers it to the device. The user can review the photo, edit it if necessary, and share it with friends.

[0998] This system allows users to reduce the time it takes to take individual photos and easily obtain higher quality photos, which increases the enjoyment of travel and improves user satisfaction.

[0999] The processing flow will be explained below.

[1000] Step 1:

[1001] The user starts the drone and pairs it with the smartphone (device), which then launches a dedicated app and connects to the drone via Bluetooth or Wi-Fi.

[1002] Step 2:

[1003] The device sends the user's rating data (such as photos and videos that they have "liked" in the past) to the server, which receives and analyzes this data.

[1004] Step 3:

[1005] The server analyzes the evaluation data to understand the user's preferences and photography trends, and then collects and analyzes trend information for the destination (popular photo spots and composition).

[1006] Step 4:

[1007] When the user arrives at their travel destination (e.g., the Eiffel Tower), the device uses GPS to obtain their current location, which is then transmitted to the drone, which then sends the information to the server.

[1008] Step 5:

[1009] The server calculates the optimal composition based on the user's current location, rating data, and trend information. For example, it suggests a photo with the Eiffel Tower in the background or a composition shot from a specific angle.

[1010] Step 6:

[1011] The server calculates the composition and sends it to the drone via the device, which then automatically sets the appropriate flight position and camera angle based on the proposed composition.

[1012] Step 7:

[1013] The user operates the shooting instruction button on the device to send a command to the drone to start shooting, and the drone takes a photo with the specified composition.

[1014] Step 8:

[1015] After the drone captures the footage, it performs some basic editing (adjusting brightness, applying filters, etc.) automatically using internal image processing algorithms.

[1016] Step 9:

[1017] The drone then transfers the edited photos to the device, where the user can review them and make further edits if necessary.

[1018] Step 10:

[1019] Finally, users can share the edited photos with friends via social media or email. This process allows users to efficiently and easily obtain high-quality photos.

[1020] Example 1

[1021] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1022] When traveling and visiting beautiful landscapes and famous places, there is a demand for easy, high-quality photos with optimal composition, but this can be a difficult task for users without photography skills. Another problem is that the time spent taking photos reduces the time available to enjoy sightseeing. Furthermore, taking photos using drones requires technical operations that are difficult for average users to operate. There is a demand for a system that solves these problems and allows anyone to easily take high-quality photos.

[1023] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1024] In this invention, the server includes a means for suggesting optimal photo compositions based on user evaluation data stored in the terminal and trend information for destinations, a means for analyzing data on photos that the user has previously liked and rated, and a means for acquiring current location information using a GPS function and generating a list of photo spots, thereby enabling users to easily take high-quality, memorable photos while minimizing the amount of work required.

[1025] The "information processing device" is a computer system that has the function of proposing optimal photographic compositions based on user evaluation data and trend information about destinations.

[1026] An "unmanned aerial vehicle" is a device that automatically adjusts the flight position and camera angle based on the shooting composition proposed by the server, and takes and edits photographs.

[1027] An "information terminal device" is a device operated by a user to instruct an unmanned aerial vehicle to take photos and obtain current location information via GPS, and includes smartphones, tablets, and the like.

[1028] "User evaluation data" refers to data relating to photos taken by the user in the past, evaluations made by the user, and preferences.

[1029] "Trending information" is information about the general popularity or current topics of a particular destination.

[1030] "Photography composition" refers to the photographic conditions, such as the subject placement, camera angle, and focal length, when taking a photograph.

[1031] "GPS function" refers to technology that uses the Global Positioning System to obtain current latitude and longitude location information.

[1032] A "generative AI model" is a model that uses artificial intelligence algorithms to generate new shooting compositions and data patterns.

[1033] The "photography spot list" is a list of multiple candidate photo shooting locations that the server proposes based on the user's current location information.

[1034] "Basic editing" refers to the process of performing basic image processing on photographs, such as adjusting brightness and applying filters.

[1035] As an embodiment of the present invention, a system for enabling a user to take optimal photographs while traveling will be described. This system is configured using an information processing device (server), an information terminal device (terminal), and an unmanned aerial vehicle (drone).

[1036] First, the user activates the drone at their travel destination and pairs it with the device using a dedicated app. The device then connects to an information processing device and obtains the user's evaluation data and trend information for the destination. This evaluation data and trend information are stored in the cloud database of the information processing device.

[1037] Next, the terminal acquires the user's current location using its GPS function and sends it to the information processing device. The information processing device generates a photo spot list based on the acquired current location information and sends it to the user's terminal. The user selects a spot they want to take a photo from the photo spot list displayed on the terminal.

[1038] The information processing device uses a generative AI model to propose the optimal composition for the shot. The proposed composition is then sent to the drone via the device. The drone then automatically sets its flight position and camera angle based on the proposed composition.

[1039] When the user presses the shooting button on the dedicated app, the drone takes a photo with the specified composition. After taking the photo, the drone performs basic editing (adjusting brightness, applying filters, etc.) and transfers the edited photo to the device. The user can then review the transferred photo, make further edits as needed, or share it on social media.

[1040] For example, when a user visits the Eiffel Tower in Paris, they start up the drone and pair it with the device. The device uses GPS to obtain the user's current location and sends it to the information processing device. The information processing device calculates the optimal composition for taking a photo of the Eiffel Tower (e.g., "a full-body photo with the Eiffel Tower in the background") based on evaluation data and trend information, and sends this information to the drone via the device. The drone moves to an appropriate position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, performs basic editing, and transfers it to the device. The user can review the photo, edit it if necessary, and share it with friends.

[1041] An example of a prompt sentence is, "I'm sightseeing at the Eiffel Tower in Paris. I want to take the best photo. Where should I take the photo and what is the best composition?"

[1042] This system allows users to reduce the time it takes to take individual photos and easily obtain high-quality photographs, thereby increasing the enjoyment of travel and improving user satisfaction.

[1043] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1044] Step 1:

[1045] The user starts the drone and pairs it with the device using a dedicated app. The input is for the user to turn on the drone, start the app, and perform the pairing process. The output is for the device and drone to connect via Bluetooth or Wi-Fi. Specifically, the user selects "Start pairing" in the app and presses the pairing button on the drone, which links the device and drone.

[1046] Step 2:

[1047] After pairing is complete, the device connects to an information processing device (server) on the cloud and obtains evaluation data and trend information. The user's identification information and location information are sent to the server as input. Based on this data, the server sends the user's evaluation data and destination trend information to the device as output. In concrete terms, the device sends a request to the server via an internet connection and performs communication processing to obtain the required data.

[1048] Step 3:

[1049] The device uses its GPS function to obtain the user's current location. As input, location data is obtained from the device's GPS sensor. As output, current location information is generated and sent to the server. Specifically, the device continuously monitors the user's current location and sends the obtained data to the server in real time.

[1050] Step 4:

[1051] The server generates a list of photo spots based on the acquired current location information. The input includes the user's current location information and trend information. The output is a list of photo spots that is generated and sent to the device. Specifically, the server performs a database search and AI analysis to create a list of popular spots near the user's current location.

[1052] Step 5:

[1053] The user selects a photo spot from the photo spot list displayed on the device. The photo spot list sent from the server is displayed as input. The selected photo spot information is saved on the device as output. In concrete terms, the user selects a photo spot using the touch screen and presses the confirm button.

[1054] Step 6:

[1055] The server uses a generative AI model to calculate the optimal composition based on the selected photo spot information. Inputs include user evaluation data, trend information, and selected photo spot information. As output, optimal composition data is generated and sent to the device. Specifically, the server runs the AI ​​model, calculates the optimal composition within a few seconds, and sends the results.

[1056] Step 7:

[1057] The terminal transfers the received shooting composition data to the drone. The input includes the shooting composition data from the server. The output is the composition data sent to the drone. Specifically, the terminal sends the data to the drone via wireless communication.

[1058] Step 8:

[1059] The drone automatically sets its flight position and camera angle based on the received composition data. The input includes the shooting composition data from the device. The output is the flight position and camera angle. The drone uses GPS and internal sensors to navigate to the appropriate position and adjust the camera angle.

[1060] Step 9:

[1061] When the user operates the camera button on the device, the drone automatically takes a photo. The input includes the user's shooting instructions. The output is the captured photo data. Specifically, the user taps the camera button on the device, and the drone takes a picture.

[1062] Step 10:

[1063] The drone performs some basic editing on the captured photos and transmits them to the device. The input includes the raw image data captured. The output is the edited photo data sent to the device. Specifically, the drone uses internal algorithms to adjust brightness and apply filters, and transmits the image to the device via wireless communication.

[1064] Step 11:

[1065] The user can then review the photos received on their device, make further edits, or share them on social media. The input includes the edited photo data transferred from the drone. The output is the user's final edited photo or the photo data they want to share. Specifically, the user uses the editing functions on their device to edit the photo and then posts it to social media using the share button.

[1066] In this way, users can easily take and share high-quality photos through individual processing steps.

[1067] (Application example 1)

[1068] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1069] Conventional product inspection methods are primarily performed manually, which is problematic due to low efficiency and inconsistent quality. Manual inspection is also time-consuming and can undermine overall factory productivity. Furthermore, inspection results often vary depending on the level of expertise of workers, making the process unreliable. There is a need for technology that can solve these issues and automate product quality inspection while improving efficiency and accuracy.

[1070] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1071] In this invention, the server includes a means for suggesting optimal shooting compositions based on user evaluation data stored on a terminal and trend information for the destination, a drone or robot that automatically adjusts its flight position and camera angle based on the shooting composition suggested by the server, a terminal that issues shooting instructions to the drone or robot, and an AI image analysis model that analyzes the captured image data and detects abnormalities. This enables the automation of product quality inspections, improving the efficiency and accuracy of inspections. It also contributes to alleviating labor shortages and improving productivity.

[1072] A "terminal" is a device operated by a user, specifically a smartphone or tablet, which is a means of controlling drones and robots via a dedicated app.

[1073] The "server" is a device installed on the cloud that stores and analyzes user evaluation data and trend information, and calculates and provides optimal shooting compositions and inspection methods.

[1074] "Drone or robot" means a mobile device that moves autonomously to take photographs or perform inspections and collect data through cameras and sensors.

[1075] The "AI image analysis model" is an artificial intelligence machine learning model that analyzes captured image data and detects abnormalities, and performs quality inspections using image processing technology.

[1076] A "prompt" is an instruction used to have the AI ​​image analysis model detect abnormalities, and is text data used to provide the AI ​​with specific inspection details and criteria.

[1077] MODE FOR CARRYING OUT THE INVENTION

[1078] As an embodiment of the present invention, an automatic product quality inspection system using a terminal, a server, and a robot will be described. This system automatically proposes optimal inspection methods and compositions based on product quality data and trend information related to inspection, and the robot then automatically performs the inspection based on these.

[1079] System configuration

[1080] 1. Terminal: Quality control personnel operate a terminal such as a smartphone or tablet. A dedicated app for controlling the robot is installed on this terminal. The terminal's role is to obtain quality data and trend information from the server and send it to the robot.

[1081] 2. Server: The server is installed in the cloud and stores and analyzes quality data. It also collects trend information on the production line and inspection environment, and calculates the optimal inspection method and composition based on the analysis results.

[1082] 3. Robot: The robot is equipped with a camera and sensors, and automatically adjusts its position and the angle of the camera and sensor based on the inspection method and composition proposed by the server. It also automatically performs inspections, performs basic data analysis, and transfers the results to a terminal.

[1083] Program processing overview

[1084] Robot startup and data synchronization

[1085] A quality control officer activates the robot and pairs it with a smartphone (terminal), which then synchronizes quality data and trend information from the server and sends it to the robot.

[1086] Obtaining and setting inspection locations

[1087] The terminal acquires the position information of the production line and sends it to the robot. The server displays a list of inspection spots based on the production line. The quality control personnel selects an inspection spot.

[1088] Inspection preparation and composition proposal

[1089] The server calculates the optimal inspection method and composition based on quality data and trend information, and sends this information to the robot via a terminal. The robot then sets the appropriate movement position and angle based on the proposed inspection method.

[1090] Automated Inspection and Data Collection

[1091] When a quality control officer presses the inspection button on the terminal, the robot performs an inspection according to the specified composition. After the inspection, the robot performs basic data analysis (such as detecting anomalies) and transfers the results to the terminal. The quality control officer checks the inspection results on the terminal and performs further analysis and recording.

[1092] Specific examples

[1093] For example, on an electrical appliance production line, a quality control officer activates a robot and pairs it with a terminal. The terminal obtains information about the production line's location and sends it to the robot. The server calculates the optimal inspection method and composition (e.g., "camera angle and position to detect wiring errors") based on quality data and trend information. This information is sent to the robot via the terminal, and the robot moves to the appropriate position and adjusts the camera and sensor angles. When the quality control officer presses the inspection button, the robot automatically inspects the product, and if it detects an abnormality, it transfers the results, including information about it, to the terminal. The quality control officer checks this data and, if necessary, records it or conducts further inspection.

[1094] Example prompt sentence:

[1095] Inspect products on the production line to detect defects. Specifically, check the following:

[1096] 1. Wiring error

[1097] 2. Surface scratches

[1098] 3. Missing parts

[1099] Please use the image data and specify the location if an anomaly is detected.

[1100] This system will reduce the time required for product quality inspection and improve the rate at which defective products are detected, while also helping to alleviate labor shortages and improve the efficiency of production lines.

[1101] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1102] Step 1:

[1103] The user starts the robot and pairs it with a device (smartphone or tablet). The device obtains the user's evaluation data and inspection trend information from the cloud server and sends it to the robot. The input in this step is the user's operation and data obtained from the server, and the output is the inspection data sent to the robot.

[1104] Step 2:

[1105] The terminal acquires the location information of the production line and sends it to the server. The server generates an inspection spot list for the production line based on this location information and displays it on the terminal. The input in this step is the location information of the production line, and the output is the inspection spot list generated by the server.

[1106] Step 3:

[1107] The user selects an inspection spot on the terminal and sends that information to the robot. Based on the selected inspection spot, the server analyzes past quality data and trend information and calculates the optimal inspection method and composition. This generates data for the robot to move to the optimal position and set the camera and sensor angles. The input in this step is the inspection spot selected by the user, quality data, and trend information, and the output is the composition and movement position data sent to the robot.

[1108] Step 4:

[1109] The server calculates the optimal inspection method and composition based on the quality data and trend information, and sends that information to the robot via the terminal. The robot moves to an appropriate position based on the proposed inspection method and sets the camera and sensor angles. The input in this step is the quality data and trend information received from the server, and the output is the robot's movement position and camera / sensor setting information.

[1110] Step 5:

[1111] When the user operates the inspection button on the terminal, the robot inspects the product using the specified composition. The robot sends the captured image data and sensor information to a cloud server, which then uses an AI model to analyze the image and detect any abnormalities. The input in this step is the image data and sensor information acquired by the robot, and the output is the analysis results of the abnormality detection by the server.

[1112] Step 6:

[1113] Based on the analysis results, the server notifies the terminal of any abnormalities or problems. The user checks these analysis results on the terminal, and records or further examines them as necessary. The input in this step is the analysis results from the server, and the output is the inspection results displayed on the terminal.

[1114] Step 7:

[1115] The server uses the generative AI model to automatically generate prompts for anomaly detection and provide the user with recommendations for the next inspection and improvement measures. The inputs in this step are the analysis results and past quality data, and the output is the generated prompts.

[1116] Example prompt sentence:

[1117] Inspect products on the production line to detect defects. Specifically, check the following:

[1118] 1. Wiring error

[1119] 2. Surface scratches

[1120] 3. Missing parts

[1121] Please use the image data and specify the location if an anomaly is detected.

[1122] These steps enable the automation of product quality inspections and the detection of abnormalities with high accuracy and efficiency.

[1123] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1124] As an embodiment of the present invention, a travel photography system using a terminal, a server, a drone, and an emotion engine will be described. This system automatically proposes optimal photo compositions based on user evaluation data, destination trend information, and user emotion data, and the drone automatically takes photos based on the proposed compositions.

[1125] System configuration

[1126] 1. Device: The user operates a device such as a smartphone or tablet. A dedicated app with drone control and emotion engine functions is installed on this device. The device acquires evaluation data and trend information from the server and transmits it to the drone. It also analyzes the user's voice and facial expressions to recognize emotions and transmits the data to the server.

[1127] 2. Server: The server is installed in the cloud and stores and analyzes user evaluation data. It also collects and analyzes trend information for destinations (such as tourist spots) and calculates optimal photo compositions based on emotional data.

[1128] 3. Drone: The drone is equipped with a camera and automatically adjusts its flight position and camera angle based on the composition suggested by the server. It also automatically takes photos, performs basic editing, and transfers the photos to the device.

[1129] 4. Emotion Engine: The emotion engine is built into the device and analyzes the user's voice and facial expressions to recognize emotions. The recognized emotion data is sent to the server and used to optimize the shooting composition.

[1130] Program processing overview

[1131] Drone launch and data synchronization

[1132] The user activates the drone and pairs it with their smartphone (device). The device then launches a dedicated app and connects to the drone via Bluetooth or Wi-Fi. The device then sends the user's evaluation data, trend information, and past emotion data to the server.

[1133] Acquiring emotion data

[1134] While the user is operating the drone, an emotion engine built into the device analyzes the user's voice and facial expressions to recognize their emotions, and this emotion data is sent to a server in real time.

[1135] Composition suggestions

[1136] The server analyzes the user's rating data, trend information, and emotional data to calculate the optimal composition for the photo. For example, if the user is showing signs of great enjoyment, a composition with a wide background may be selected. The results of this calculation are sent to the drone via the device.

[1137] Drone movement and filming

[1138] The drone automatically adjusts its flight position and camera angle based on the composition of the shot. When the user commands the drone to start shooting, it automatically takes a photo. After that, the drone performs basic editing (adjusting brightness and applying filters) on the photo and transfers it to the device.

[1139] Specific examples

[1140] A specific example of this system is shown below. For example, when a user visits the Eiffel Tower in Paris, they first start up the drone and pair it with the device. The device obtains the user's current location using GPS and sends it to the drone. The emotion engine is also running, analyzing the user's facial expressions in real time. If the user shows a happy expression with the Eiffel Tower in the background, the server will suggest the optimal composition based on that emotional data. This composition information is sent to the drone via the device, and the drone moves to the optimal position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, edits it, and transfers it to the device. The user can then review the photo, make further edits, and share it on social media.

[1141] This system allows users to efficiently take the best photos that suit their emotions, not only reducing the time spent taking photos while traveling but also making it easier to obtain photos that they are satisfied with.

[1142] The processing flow will be explained below.

[1143] Step 1:

[1144] The user starts the drone and pairs it with the smartphone (device), which then launches a dedicated app and connects to the drone via Bluetooth or Wi-Fi.

[1145] Step 2:

[1146] The device connects to the server, obtains user evaluation data and trend information, and synchronizes it with the drone. It also obtains previously saved emotion data from the server.

[1147] Step 3:

[1148] The device uses a camera and microphone to monitor the user's voice and facial expressions in real time, and analyzes their emotions using an emotion engine. For example, it analyzes smiles, surprised expressions, tone of voice, etc. to obtain emotional data. This emotional data is then sent to a server.

[1149] Step 4:

[1150] When the user approaches a destination (e.g., the Eiffel Tower), the device uses GPS to obtain its current location and transmits the location information to the drone, which then sends the information to the server.

[1151] Step 5:

[1152] The server calculates the optimal composition for the photo based on the user's current location, rating data, trend information, and real-time emotional data. For example, if the user is showing signs of joy, the server will suggest using a wide-angle composition or incorporating the surrounding scenery. This information is sent to the drone via the device.

[1153] Step 6:

[1154] The drone automatically adjusts its flight position and camera angle based on the composition information received from the server, and uses a gimbal to correct for camera shake and tilt.

[1155] Step 7:

[1156] The user operates the shooting command button on the device to send a command to the drone to start shooting, and the drone takes a photo with the specified composition.

[1157] Step 8:

[1158] After the drone takes the photo, it uses its built-in image processing algorithm to perform basic editing (adjusting brightness, color correction, applying filters, etc.) and transfers the edited photo to your device.

[1159] Step 9:

[1160] The user can review the received photos on the device and, if necessary, make additional edits to match the emotion, such as adding a specific filter to the photo or cropping it.

[1161] Step 10:

[1162] Finally, users can share the edited photos with friends via social media or email. Through this process, users can efficiently obtain high-quality photos that match their emotions and trends.

[1163] Example 2

[1164] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1165] Conventional travel photography systems require users to determine the appropriate composition and shooting location, and also operate the drone and camera themselves, which results in a lot of time and effort required for the photo shoot. It is also difficult to capture photos that reflect the user's emotions and preferences, making it difficult to obtain photos that are satisfactory. This poses a problem that reduces the enjoyment of traveling.

[1166] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1167] In this invention, the server includes means for proposing optimal photographic compositions based on user evaluation data stored in the terminal and trend information for destinations, means for transmitting user emotional data to the server via an emotion analysis device built into the terminal, and means for analyzing the user emotional data and calculating optimal photographic compositions, thereby enabling users to easily and automatically take optimal photographs that match their emotions and preferences.

[1168] A "terminal" is a portable electronic device such as a smartphone or tablet that is operated by a user.

[1169] "Rating data" refers to information about photos and reviews that users have liked and rated in the past.

[1170] "Destination trend information" is the latest popularity and rating information about destinations such as tourist spots.

[1171] The "information processing device" is a server installed on the cloud that analyzes user data and suggests optimal shooting compositions.

[1172] An "unmanned flying device" is a drone that flies automatically and is equipped with a camera to take pictures.

[1173] An "emotion analysis device" is a system that analyzes a user's voice and facial expressions to recognize emotional data.

[1174] "Emotion data" refers to emotional information analyzed based on the user's voice and facial expressions.

[1175] "Photography composition" refers to the screen composition and subject placement when taking a photograph.

[1176] As an embodiment of the present invention, a travel photography system using a terminal, a server, an unmanned aerial vehicle, and an emotion analysis device will be described. This system automatically proposes optimal photo compositions based on user evaluation data, destination trend information, and user emotion data, and the unmanned aerial vehicle automatically takes photos based on the proposed compositions.

[1177] System configuration

[1178] 1. Device: The user operates a device such as a smartphone or tablet. This device has a dedicated app installed to control the drone and use the emotion analysis device. The device is responsible for obtaining evaluation data and trend information from the server and sending it to the drone. It also analyzes the user's voice and facial expressions to recognize emotions and sends the data to the server.

[1179] 2. Server: The server is installed on the cloud and stores and analyzes user evaluation data. It also collects and analyzes trend information about destinations and calculates optimal photo compositions based on emotional data.

[1180] 3. Unmanned aerial vehicle: The unmanned aerial vehicle (drone) is equipped with a camera and automatically adjusts its flight position and camera angle based on the composition of the photo proposed by the server. It also automatically takes photos, performs basic editing, and transfers the photos to the device.

[1181] 4. Emotion Analysis Device: The emotion analysis device is built into the device and recognizes emotions by analyzing the user's voice and facial expressions. The recognized emotional data is sent to the server and used to optimize the shooting composition.

[1182] Program processing overview

[1183] The system's programming begins when the user activates the drone and pairs it with the device. The device then launches a dedicated app and connects to the drone via Bluetooth or Wi-Fi. The device then sends the user's evaluation data, trend information, and past emotional data to the server. While the user is operating the drone, an emotion analyzer built into the device analyzes the user's voice and facial expressions to recognize their emotions. This emotional data is then sent to the server in real time.

[1184] The server analyzes the evaluation data, trend information, and emotion data to calculate the optimal composition for the photo. For example, if the user is showing a very happy emotion, a composition with a wide background may be selected. The calculation results are sent to the unmanned aerial vehicle via the terminal.

[1185] The drone automatically adjusts its flight position and camera angle based on the proposed composition. When the user issues a command to start shooting, the drone automatically takes a photo. After that, the drone performs basic editing (adjusting brightness and applying filters) on the photo and transfers it to the device.

[1186] Specific examples

[1187] Next, we will show a concrete example of this system. For example, when a user visits the Eiffel Tower in Paris, they first start up the drone and pair it with their device. The device obtains the user's current location using GPS and sends it to the drone. An emotion analysis device is also running, analyzing the user's facial expressions in real time. If the user shows a happy expression with the Eiffel Tower in the background, the server will suggest the optimal composition based on that emotional data. This composition information is sent to the drone via the device, and the drone moves to the optimal position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, edits it, and transfers it to the device. The user can then review the photo, make further edits, and share it on social media.

[1188] An example of a prompt is as follows:

[1189] "When you arrive at the Eiffel Tower in Paris, simply launch the drone and pair it with your smartphone. Smile with the Eiffel Tower in the background, and the drone will calculate the optimal composition and take the photo automatically. It will then edit the photo and transfer it to your device."

[1190] This system allows users to efficiently take the best photos that suit their emotions, not only reducing the time spent taking photos while traveling but also making it easier to obtain photos that satisfy users.

[1191] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1192] Step 1:

[1193] Initial Setup and Data Synchronization

[1194] The user starts the unmanned flying device and pairs it with a smartphone (terminal).

[1195] Input: User operation (starting the drone, pairing with the device)

[1196] Specific operation: The user launches a dedicated app installed on the device and connects to the drone via Bluetooth or Wi-Fi. The device then uses its GPS function to obtain the user's current location and sends that information to the server.

[1197] Output: GPS data is sent to the server, and the server sends evaluation data, trend information, and past emotion data to the device.

[1198] Step 2:

[1199] Real-time acquisition of emotion data

[1200] The user begins operating the unmanned flying device.

[1201] Input: User operation, user voice and facial expression data

[1202] Specific operation: The emotion analysis device built into the device analyzes the user's voice and facial expressions in real time using a camera and microphone. The device then transmits this emotion data to a server in real time.

[1203] Output: The recognized emotion data is sent to the server in real time.

[1204] Step 3:

[1205] Shooting composition calculation and suggestions

[1206] The server calculates the shooting composition based on the data received.

[1207] Input: Rating data, trend information, sentiment data

[1208] Specific operation: The server analyzes the evaluation data, trend information, and emotion data to generate the optimal photo composition. For example, if the user looks happy, it uses an extensive search algorithm to suggest a composition that includes a wide background.

[1209] Output: The optimal shooting composition data is generated and sent to the device.

[1210] Step 4:

[1211] Flying and filming unmanned aerial vehicles

[1212] The unmanned flying device is operated based on the photographic composition.

[1213] Input: Shooting composition data, user's instruction to start shooting

[1214] How it works: The unmanned flying device automatically adjusts its flight position and camera angle based on composition suggestion data from the server. When the user presses the shooting button in the dedicated app, the unmanned flying device automatically releases the shutter. The camera inside the drone uses an autofocus function to set the optimal shooting conditions.

[1215] Output: The captured photo data is stored in the drone.

[1216] Step 5:

[1217] Photo editing and transfer

[1218] The drone then edits the photos and transfers them to the device.

[1219] Input: Photographed photo data

[1220] How it works: After taking a photo, the drone automatically adjusts brightness and applies filters, then transfers the edited photo to your device via Wi-Fi or Bluetooth.

[1221] Output: The edited photo data is transferred to the device and displayed to the user.

[1222] (Application example 2)

[1223] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1224] The present invention relates to a system for taking optimal advertising photos by utilizing user evaluation data, destination trend information, and emotional data. Conventional photography systems have difficulty proposing optimal compositions that reflect user emotions and real-time evaluation data, making it impossible to take advertising photos with high satisfaction. Furthermore, since there were no systems specialized for advertising photography and manual editing was required, there was a demand for efficient photography and easy editing.

[1225] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1226] In this invention, the server includes a means for proposing an optimal photographic composition based on user evaluation data stored in the terminal and trend information for the destination, a flying device that automatically adjusts the flight position and camera angle based on the photographic composition proposed by the server, a terminal that instructs the flying device to take a photograph, an emotion analysis engine that analyzes user emotion data and transmits it to the server, a means for proposing an optimal photographic composition for an advertising photograph based on the user emotion data, and a means for basic editing of the photographed advertising photograph and transferring it to the terminal. This makes it possible to efficiently take optimal advertising photographs that reflect the user's emotions and automatically perform basic editing work after photographing.

[1227] A "terminal" is an information processing device operated by a user, and specifically includes a smartphone, tablet, computer, etc.

[1228] "User evaluation data" includes information on photos, videos, etc. that users have previously evaluated, and is data that is analyzed based on those evaluations.

[1229] "Destination Trends" is data based on the latest information and popular topics related to specific locations and events.

[1230] A "server" is an information processing device that is installed on the cloud and stores, analyzes, and transmits data.

[1231] "Shooting composition" refers to suggestions for determining the optimal viewpoint and frame when taking photographs or videos.

[1232] A "flying device" is a device equipped with a camera that takes photographs by flying at a specified position and angle, and specifically includes drones.

[1233] "Emotion analysis engine" refers to software or hardware that analyzes a user's facial expressions and voice to recognize their emotions.

[1234] "Advertising photography" is photography taken for commercial or promotional purposes.

[1235] "Basic editing" refers to basic editing tasks such as adjusting brightness and applying filters to photos after they have been taken.

[1236] As an embodiment of the present invention, a system for taking advertising photographs at travel destinations, event venues, etc. This system automatically proposes optimal compositions for advertising photographs based on user evaluation data, trend information for destinations, and user emotional data, and the flying device automatically takes the photographs based on the proposed compositions.

[1237] System configuration

[1238] 1. Device:

[1239] The user operates a device such as a smartphone or tablet. A dedicated app with flight device control and emotion analysis engine functions is installed on this device. The device acquires evaluation data and trend information from the server and sends it to the flight device. It also analyzes the user's voice and facial expressions to recognize emotions and sends the data to the server.

[1240] 2. Server:

[1241] The server is installed in the cloud and stores and analyzes user evaluation data. It also collects and analyzes trend information for destinations (such as tourist spots and event venues) and calculates optimal composition for advertising photos based on emotional data.

[1242] 3. Flight equipment:

[1243] The flying device is equipped with a camera and automatically adjusts the flight position and camera angle based on the composition of the photo suggested by the server. It also automatically takes photos, performs basic editing, and transfers the photos to the device.

[1244] 4. Sentiment Analysis Engine:

[1245] The emotion analysis engine is built into the device and recognizes emotions by analyzing the user's voice and facial expressions. The recognized emotion data is sent to a server and used to optimize the shooting composition.

[1246] Processing Description

[1247] The server operates using a cloud computing service. It receives user evaluation data, destination trend information, and emotional data, and then calculates the optimal photo composition based on this data. This calculation uses a machine learning algorithm called a generative AI model. This generative AI model predicts the user's preferences and emotional state based on past data, and then suggests the optimal composition.

[1248] The user's device is a smartphone or tablet. The device is equipped with a camera and microphone, which are used to analyze the user's facial expressions and voice in real time. The analysis results are sent to the server via the device's emotion analysis engine.

[1249] A standard drone is used as the flying device. This drone is equipped with a high-resolution camera and automatically flies and takes photos according to the optimal shooting composition sent from the server. After taking the photos, it automatically performs basic editing (adjusting brightness and applying filters) and transfers the photos to the device.

[1250] Specific examples

[1251] For example, if a user visits a famous tourist spot and wants to take a photo for an advertisement, they first start the drone and pair it with the device. The device uses GPS to obtain the user's current location and sends it to the server. At the same time, an emotion analysis engine is running, analyzing the user's facial expressions and voice in real time. If the user smiles or shows a happy expression, the server uses that emotional data to suggest the optimal composition. This composition information is sent to the drone via the device, and the drone moves to the optimal position and adjusts the camera angle. When the user presses the capture button, the drone automatically takes a photo, performs some basic editing, and then transfers the photo to the device. This system allows users to efficiently take optimal advertising photos that reflect their emotions.

[1252] Prompt Sentence Examples

[1253] "I want to take the perfect advertising photo at the Eiffel Tower in Paris."

[1254] "Please suggest advertising photos that express emotions based on the user's smile."

[1255] This system allows users to easily take high-quality advertising photos.

[1256] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1257] Step 1:

[1258] Starting the drone and pairing it with your device

[1259] The user starts the drone and pairs it with a device such as a smartphone or tablet. This pairing is done via Bluetooth or Wi-Fi. The input data is the drone's start-up signal and the device's connection request, and the output is a status indicating that pairing is complete. This pairing procedure prepares the entire system to work together and begin operation.

[1260] Step 2:

[1261] Location and emotion data acquisition

[1262] The device uses GPS to obtain the user's current location and activates the emotion analysis engine. The emotion analysis engine uses the device's camera and microphone to analyze the user's facial expressions and voice in real time and generate emotion data. The input data is camera footage, audio, and GPS information, and the output is emotion data and the current location. This allows the user's real-time emotional state and location information to be understood.

[1263] Step 3:

[1264] Sending data to the server

[1265] The device sends the acquired evaluation data, location information, trend information, and emotion data to the server. The input data is the various data collected by the device, and the output data is sent to the server. The server receives this data and prepares to calculate the optimal composition for the advertising photo based on the user's emotion and location information.

[1266] Step 4:

[1267] Calculating the composition of the photo

[1268] The server uses a generative AI model to calculate the optimal shooting composition based on the received evaluation data, trend information, and emotion data. The input data is the entire set of received data, and the output is optimal shooting composition information. This composition information includes the shooting position and camera angle. The generative AI model learns from past data and proposes the optimal composition.

[1269] Step 5:

[1270] Sending the composition

[1271] The server sends the calculated optimal shooting composition information to the drone via the terminal. The input data is the generated shooting composition information, and that information is sent to the drone as output. This allows the drone to automatically start operating based on that composition.

[1272] Step 6:

[1273] Automatic drone flight and photography

[1274] The drone moves to the optimal flight position and camera angle based on the received shooting composition information. After moving, it automatically takes photos according to the user's instructions. The input data is the shooting composition information and the user's shooting instructions, and the output is the captured photo. The drone uses a high-resolution camera to take photos that match the composition.

[1275] Step 7:

[1276] Basic photo editing and transfer

[1277] After taking a photo, the drone performs basic editing such as adjusting the brightness and applying filters to the photo. The edited photo is then transferred to the device. The input data is the captured photo, and the output is the edited photo sent to the device. This allows the user to immediately review the photo and make further edits if necessary.

[1278] Step 8:

[1279] View and share photos

[1280] Users can view the transferred photos on their devices and make further edits. They can then share them on social media. The input data is the edited photo, and the output is the shared photo or content. Through this process, users can efficiently take and share high-quality advertising photos.

[1281] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1282] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1283] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1284] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1285] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1286] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1287] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1288] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1289] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1290] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1291] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1292] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1293] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1294] 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.

[1295] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1296] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1297] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1298] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1299] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1300] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1301] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1302] The following is further disclosed regarding the above embodiment.

[1303] (Claim 1)

[1304] a server that proposes optimal photo compositions based on user evaluation data stored in the device and trend information for the destination;

[1305] a drone that automatically adjusts its flight position and camera angle based on the shooting composition proposed by the server;

[1306] a terminal that instructs the drone to take photographs;

[1307] A system including:

[1308] (Claim 2)

[1309] 2. The system according to claim 1, wherein the step of suggesting a composition for a photograph includes a step of analyzing data on photographs that the user has previously liked and rated.

[1310] (Claim 3)

[1311] The system according to claim 1, further comprising means for performing basic editing of the photographs taken by the drone after the photographs are taken automatically and transferring the photographs to a terminal.

[1312] "Example 1"

[1313] (Claim 1)

[1314] an information processing device that suggests optimal photographic compositions based on user evaluation data stored in a terminal and trend information for a destination;

[1315] an unmanned aerial vehicle that automatically adjusts a flight position and a camera angle based on a photographing composition proposed by the information processing device;

[1316] an information terminal device that instructs the unmanned aerial vehicle to take photographs;

[1317] A system including:

[1318] (Claim 2)

[1319] 2. The system according to claim 1, wherein the step of suggesting a composition for a photograph includes a step of analyzing data of photographs that the user has previously liked and rated.

[1320] (Claim 3)

[1321] 2. The system according to claim 1, further comprising means for performing basic editing of the photographs taken by the unmanned aerial vehicle after automatic photographing and transferring the photographs to an information terminal device.

[1322] (Claim 4)

[1323] a means for the information terminal device to acquire current location information using a GPS function and transmit the information to the information processing device;

[1324] a means for generating a photography spot list based on the current location information transmitted by the information processing device and transmitting the list to the information terminal device;

[1325] 10. The system of claim 1, comprising:

[1326] (Claim 5)

[1327] a means for generating a plurality of photographic compositions by using a generation AI model in an information processing device, selecting an optimal photographic composition, and transmitting the optimal photographic composition to an information terminal device;

[1328] a means for transferring the photographic composition information selected by the information terminal device to the unmanned aerial vehicle;

[1329] 10. The system of claim 1, comprising:

[1330] "Application Example 1"

[1331] Claims based on new inventive subject matter:

[1332] (Claim 1)

[1333] a server that proposes optimal photo compositions based on user evaluation data stored in the device and trend information for the destination;

[1334] a drone or robot that automatically adjusts its flight position and camera angle based on the shooting composition proposed by the server;

[1335] a terminal that instructs the drone or robot to take photographs;

[1336] An AI image analysis model that analyzes captured image data and detects abnormalities,

[1337] A system including:

[1338] (Claim 2)

[1339] 2. The system according to claim 1, wherein the step of suggesting a composition for a photograph includes a step of analyzing data on photographs that the user has previously liked and rated.

[1340] (Claim 3)

[1341] The system of claim 1 further comprises a means for performing basic editing of the photographs taken by the drone or robot after the automatic photographing and transferring the photographs to a terminal, and a means for generating prompt sentences to detect abnormalities based on the photographic data.

[1342] "Example 2: Combining Emotion Engines"

[1343] (Claim 1)

[1344] an information processing device that suggests optimal photographic compositions based on user evaluation data stored in a terminal and trend information for a destination;

[1345] An unmanned flying device that automatically adjusts a flight position and a camera angle based on a shooting composition proposed by the information processing device;

[1346] a terminal that issues a photographing instruction to the unmanned flying device;

[1347] means for transmitting user emotion data to a server via an emotion analysis device incorporated in the terminal;

[1348] means for the server to analyze the user's emotional data and calculate the optimal photographic composition;

[1349] A system including:

[1350] (Claim 2)

[1351] 2. The system according to claim 1, wherein the step of suggesting a composition for a photograph includes a step of analyzing data on photographs that the user has previously liked and rated.

[1352] (Claim 3)

[1353] The system according to claim 1, further comprising means for performing basic editing of the photographs taken by the unmanned flying device after automatic photographing and transferring the photographs to a terminal.

[1354] "Application example 2 when combining emotion engines"

[1355] (Claim 1)

[1356] a server that proposes optimal photo compositions based on user evaluation data stored in the device and trend information for the destination;

[1357] A flying device that automatically adjusts the flight position and camera angle based on the shooting composition proposed by the server;

[1358] a terminal that instructs the flying device to take photographs;

[1359] an emotion analysis engine that analyzes the user's emotion data and transmits the data to the server;

[1360] A means for proposing an optimal composition for photographing an advertisement photograph based on the user's emotional data;

[1361] A means to basically edit the advertising photos taken and transfer them to the device,

[1362] A system including:

[1363] (Claim 2)

[1364] 2. The system according to claim 1, wherein the step of suggesting a composition for a photograph includes a step of analyzing data on photographs that the user has previously liked and rated.

[1365] (Claim 3)

[1366] 2. The system according to claim 1, further comprising means for performing basic editing of the photographs taken by the flying device after automatic photographing and transferring the photographs to a terminal. [Explanation of symbols]

[1367] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a server that proposes optimal photo compositions based on user evaluation data stored in the device and trend information for the destination; a drone that automatically adjusts its flight position and camera angle based on the shooting composition proposed by the server; a terminal that instructs the drone to take photographs; A system including:

2. The system according to claim 1 , wherein the step of suggesting a composition for a photograph includes a step of analyzing data of photographs that the user has previously liked and rated.

3. The system according to claim 1, further comprising means for performing basic editing of the photographs taken by the drone after the photographs are taken automatically and transferring the photographs to a terminal.

Images