system

Abstract

We provide the system. [Solution] A location information management system for managing dining experiences provided in unused spaces, A control means for safely and stably controlling the target device, A reservation method that allows users to manage their reservations, A monitoring system to collect various types of information in real time and ensure safety, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] The ground space in urban areas is crowded, and the congestion in tourist facilities and restaurants is increasing. Especially in areas with a large number of visitors, this congestion is reducing the convenience for local residents and tourists. In addition, the problem is that the provided tourist experience is limited. It is necessary to activate the tourism industry by providing new space utilization and special experiences.

Means for Solving the Problems

[0006] An "unused space" is a space that is not currently being used commercially or publicly, and for which new uses are being explored.

[0007] A "meal experience" is a series of activities that involve physiological and psychological satisfaction derived from eating and drinking.

[0008] "Location information management means" refers to a technology or device that measures and maintains the geographical location of a specific object or space.

[0009] "Control means" refers to techniques or devices used to adjust or stabilize the operation of equipment or systems for a specific purpose.

[0010] "Reservation method" refers to a technology or technique for securing a place or time for use in advance.

[0011] "Monitoring means" refers to technologies or devices used to continuously observe specific conditions or situations in order to ensure safety and efficiency.

[0012] A "system" refers to a functional collection of interconnected elements that combine to achieve a specific purpose. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2]It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] [[ID=​​​​​​​​​​​​​​​​​​​​​​​​​​First, the terms used in the following description will be explained.

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

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

[0018] In the following embodiments, the storage with a reference numeral is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

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

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

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

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0030] As shown in Figure 2, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention is implemented as a system for providing a new tourism experience utilizing the air. Specific embodiments of each element are described below.

[0035] This system allows users to book aerial restaurants through a dedicated application and provides integrated services including location information management, device control, reservation management, and monitoring.

[0036] 1. Location information management

[0037] The server manages the drone's precise location information and sets the route from the departure point to the destination. It monitors the location in real time and constantly ensures safety during flight. Predictive algorithms are used to calculate the optimal flight route based on weather conditions and traffic conditions.

[0038] 2. Device Control

[0039] The server sends control signals to the drone instructing it to fly steadily. These control signals include altitude, speed, and route changes. This allows the drone to safely navigate its target path.

[0040] 3. Reservation Management

[0041] The user accesses the reservation screen using their device and selects their desired date, time, and menu. The server receives the reservation information and registers it in the database. Based on this, it automatically adjusts the availability of drones and seats and sends a reservation confirmation notification to the user's device.

[0042] 4. Monitoring

[0043] The server monitors the safety and comfort of users while they are on board through various sensors mounted on the drone. It monitors seat movement, air pressure, temperature, etc., and instantly issues an alert if any abnormality occurs. To ensure user safety, it coordinates with ground staff to enable a rapid response.

[0044] Specific example

[0045] If a user wishes to make a Sunday lunch reservation, they open the reservation screen in the dedicated app. After selecting their desired menu and entering their preferred time, the device sends this information to the server. The server checks the drone's availability and flight route, and confirms the reservation. On the day of the reservation, the user gathers at the designated departure point and boards the drone. The server monitors the flight in real time, ensuring a safe dining experience.

[0046] Thus, the present invention allows users to enjoy an unparalleled aerial sightseeing experience and effectively alleviates congestion on the ground.

[0047] The following describes the processing flow.

[0048] Step 1:

[0049] The user launches the app on their device and logs in by entering their registered email address and password on the login screen. The device sends this information to the server, which verifies it against the information in the database. If authentication is successful, the server displays the user's dashboard on the device.

[0050] Step 2:

[0051] The user selects a reservation option from the dashboard and enters their desired date, time, and meal menu. The terminal sends the selected reservation information to the server. The server checks the availability of drones and seats in its database and determines if a reservation is possible.

[0052] Step 3:

[0053] If the server determines that a reservation is available, it prompts the user to confirm the reservation. The user confirms the reservation on their device and presses the approve button. The device then sends the approved reservation information back to the server. The server confirms the reservation and sends a reservation completion notification to the device.

[0054] Step 4:

[0055] On the day of the reservation, the server retrieves real-time weather data to confirm flight safety. If the weather is good, preparations for drone takeoff begin. The server sends the flight path and takeoff instructions to the drone.

[0056] Step 5:

[0057] Once the user arrives at the designated departure point, they use a terminal to confirm their boarding. The terminal sends boarding information to the server, and once boarding is confirmed, the server instructs the drone to depart.

[0058] Step 6:

[0059] During flight, the server receives data from the drone's sensors and monitors user safety in real time. If an anomaly is detected, the server issues an alert and communicates the situation to ground staff.

[0060] Step 7:

[0061] When the user finishes their meal and the scheduled time arrives, the server notifies the drone of the return route. Once the drone safely lands at the starting point, the server sends a notification to the terminal that the experience has ended.

[0062] Step 8:

[0063] After the experience ends, the server sends a feedback questionnaire to the user's device. The user enters their evaluation of the experience, and the device sends this back to the server. The server stores the feedback in a database and uses it to improve the service.

[0064] (Example 1)

[0065] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0066] When providing dining experiences that utilize unused spaces, it is necessary to ensure the safety and comfort of users while simultaneously managing reservations efficiently and setting up optimized travel routes. However, conventional technologies have found it difficult to satisfy these requirements at the same time. This invention aims to solve these problems and provide users with a new aerial dining experience.

[0067] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0068] In this invention, the server includes location information management means for managing dining experiences provided in unused spaces, control means for stable control of target devices, and reservation means for accepting user reservations. This enables users to safely and efficiently enjoy new tourism experiences.

[0069] A "location information management system" is a system for determining the location of a target device and setting and managing the optimal movement route in order to provide a dining experience in an unused space.

[0070] A "control means" is a system that has the function of generating and transmitting control signals necessary to operate the target device safely and stably.

[0071] A "reservation system" is a system that has the function of recording and managing information when users reserve services or experiences in advance.

[0072] A "monitoring system" is a system that collects various types of information in real time and has the necessary functions to ensure user safety and the normal operation of equipment.

[0073] An "input method" is an interface that allows users to input information regarding travel and dining experience reservations via a terminal and send it to the server.

[0074] A "flight planning system" is a system that uses a predictive algorithm to formulate a plan for the target device to travel along the optimal path.

[0075] To implement the invention, the server constitutes a system with diverse functions. The server uses location information management means to precisely manage location information for providing a dining experience through unused airspace, and sets the route from the drone's departure point to its destination. The server uses a prediction algorithm to analyze weather conditions and traffic conditions and calculate the optimal flight route. Specifically, it uses a weather API to obtain the latest data and reflects it in the flight route in real time.

[0076] Simultaneously, the server uses control mechanisms to generate control signals necessary to maintain stable flight for the drone, sending instructions including altitude and speed adjustments and route changes. This allows the drone to navigate the target path safely and efficiently. This process ensures user safety while providing an exciting aerial dining experience.

[0077] The reservation system provides users with access to the reservation screen for the sky restaurant using their devices. Users select their desired date, time, and menu on the screen and send the reservation information from their device to the server. The server processes the reservation information in real time and registers it in the database. This process automatically adjusts the reservation status, and a reservation confirmation notification is sent to the device within seconds.

[0078] Furthermore, the server uses monitoring devices to collect data in real time from various sensors mounted on the drone, maintaining user safety and comfort. The data obtained from each measuring instrument is also shared with ground staff, and any abnormalities are quickly notified.

[0079] For example, if a user wants to make a weekend lunch reservation, they would use a specific mobile application to select the menu and date / time. The server would then check drone availability and flight route planning in real time and confirm the reservation. After that, the server would make any necessary adjustments to the environment during the flight.

[0080] An example of a prompt to input into the generating AI model is, "Please describe in detail each function of the system to maximize the enjoyment of the aerial dining experience." The intention is that this will convey the overall picture of the invention to the user and lead to a deeper understanding.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] The user activates the terminal and accesses the reservation application. The user enters their desired date and time and menu selection, and the terminal sends this information to the server. The entered data is then provided to the server as the reservation details.

[0084] Step 2:

[0085] The server analyzes the reservation information received from the terminal. Based on the input information, the server registers the reservation in the database. In this process, the server also checks the current availability and schedule of drones to determine if it is possible to accommodate the request. As a result, a status indicating whether or not the reservation can be made is output.

[0086] Step 3:

[0087] The server develops a flight plan once the booking is approved. The server retrieves the latest weather data from a weather API and uses a forecasting algorithm to calculate the optimal flight route. The inputs are current weather conditions and departure and arrival points, while the output is a detailed flight schedule to instruct the drone.

[0088] Step 4:

[0089] After the server completes the booking process and flight planning, it sends a booking confirmation to the terminal. The terminal receives the confirmation information from the server and displays it to the user. The displayed information includes booking details such as the departure point and time, and the selected menu.

[0090] Step 5:

[0091] Users gather at the departure point at the designated date and time and perform a final check-in using a terminal. The terminal sends the check-in information to the server for final confirmation of the reservation. In this step, the check-in information is input, and the check-in status, which is compiled by the server, is output.

[0092] Step 6:

[0093] The server collects and monitors real-time data from sensors mounted on the drone. Information such as temperature, air pressure, and seat movement is used as input, and the server analyzes this data to detect any abnormalities. The output is either a continuous operation command if everything is normal, or an alert if an abnormality is detected.

[0094] (Application Example 1)

[0095] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0096] In recent years, there has been growing interest in providing new experiences that utilize untapped spaces. However, experiences, especially those taking place in the air, often lack sufficient safety and real-time management, and may not be able to effectively notify users of their delivery. Furthermore, various challenges exist, such as the increasing difficulty of optimizing travel routes and aggregating and analyzing safety information using multiple measuring instruments, depending on the scale of the project.

[0097] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0098] In this invention, the server includes location information management means for managing the dining experience provided in unused space, control means for safely and stably delivering food to an aerial transport device, reservation means for managing reservations made by users, monitoring means for collecting various information in real time and ensuring safety, and delivery completion notification means for sending notifications to user terminals. This enables the safe and comfortable provision of a new aerial experience to users, while simultaneously improving the quality of the experience through efficient notifications and route optimization.

[0099] "Unused space" refers to space that does not serve its intended purpose through conventional use, or is simply not being used.

[0100] "Location information management means for managing the dining experience" refers to technical means used to determine the precise location of the dining space and set the optimal travel route.

[0101] An "aerial transport device" refers to a device for moving goods or services through the air, and in this invention, it specifically refers to a device for delivering food.

[0102] "Control means" refers to technical means that provide signals or instructions to ensure the stable and safe operation of equipment or machinery.

[0103] "Reservation management methods" refer to methods and systems for receiving and managing users' reservation information.

[0104] "Monitoring measures" refer to technical means used to ensure security by collecting various types of information in real time and analyzing the data.

[0105] A "delivery completion notification system" is a system that has the function of informing the user that the delivery of goods has been completed.

[0106] This system is designed to provide a safe and efficient aerial experience utilizing untapped space. The server manages location information and controls aerial transport devices to oversee the dining experience. Specifically, it uses GPS data and weather information to calculate the optimal route and sends control signals to aerial transport devices such as drones. A prediction algorithm using Python is implemented in this process.

[0107] The user's device functions as a reservation tool, providing an interface for selecting the desired date, time, and menu. Reservation information is stored in the cloud and managed in real-time in conjunction with drone availability. This part is implemented using a mobile application built with React Native and Flutter®.

[0108] To ensure user safety, the server uses monitoring tools to analyze information from various sensors mounted on the drone. This includes data from temperature, barometric pressure, and acceleration sensors, which are processed through software that enhances safety.

[0109] For example, if a family planning a picnic in a park uses the app to order food, the server will fly a drone along the optimal route and safely deliver the food to the user's designated pickup area. The entire process is seamless, allowing users to enjoy a new experience with peace of mind.

[0110] An example of a prompt to input into the generating AI model is: "Please describe the user experience of an aerial delivery system app. Specifically, please explain the steps involved in placing an order and how the drone delivers the food."

[0111] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0112] Step 1:

[0113] The terminal accepts reservations for meals from the user. When the user selects the date, time, and menu through the app interface, that information is sent from the terminal to the cloud server. The input is the user's selection information, and the output is the reservation data stored in the cloud.

[0114] Step 2:

[0115] The server checks drone availability and flight zones based on the received reservation data. Specifically, it retrieves reservation information from a database and uses Python to determine the optimal drone and flight route. The input is reservation data, and the output is the drone selection result.

[0116] Step 3:

[0117] The server collects weather and GPS data in real time and instructs the drone on a safe flight path. This involves using an algorithm to calculate the optimal path based on input data from sensors and transmitting it to the drone as a control signal. The input is sensor and position data, and the output is the control signal.

[0118] Step 4:

[0119] The server sends a notification to the user's device to confirm the reservation and inform them of the scheduled delivery time. The notification includes a reservation confirmation message and is displayed on the device's user interface as a status check for the user. The input is the drone's flight plan, and the output is the notification message to the user.

[0120] Step 5:

[0121] Once the drone takes off, the server monitors its location and status in real time. The server periodically collects data from the sensors to check for any abnormalities. The input is the drone's sensor data, and the output is the monitoring information.

[0122] Step 6:

[0123] After safe delivery by drone is complete, the server sends a delivery completion notification to the terminal. This informs the user that their food has arrived, and a delivery completion message is displayed on the terminal. The input is the delivery completion status, and the output is the completion notification to the user.

[0124] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0125] This invention is a system that recognizes the user's emotions in real time during an aerial dining experience and optimizes the experience based on those emotions. Specific embodiments for carrying out the invention are described below.

[0126] In addition to location information management, device control, reservation management, and monitoring, this system incorporates an emotion engine that recognizes user emotions, thereby further improving the user experience.

[0127] 1. Location information management

[0128] The server manages the real-time positioning of drones that provide dining spaces. Using high-precision positioning technology, it adjusts the drones to navigate safely and efficiently and reach the designated area.

[0129] 2. Device Control

[0130] The server transmits signals to control the drone's flight path and maintain optimal flight conditions to provide a safe and comfortable dining experience.

[0131] 3. Reservation Management

[0132] Users make reservations using a dedicated app, and the server receives this information and records it in a database. Based on the reservation status, the system adjusts the availability of drones and seats to provide the optimal schedule.

[0133] 4. Monitoring

[0134] The server monitors the safety of users and equipment through sensors mounted on each drone. In the event of an anomaly, it quickly notifies staff and takes necessary measures.

[0135] 5. Emotion recognition

[0136] The emotion engine analyzes data such as voice, facial expressions, and gestures acquired from the user to determine their emotional state in real time. Based on the determined emotion, the server adjusts music, lighting, service content, and other elements to enhance the user's comfort.

[0137] Specific example

[0138] If a user desires a romantic aerial dinner at sunset on a clear day, they can book the service. During the flight, the emotion engine detects the user's smile and relaxed posture, and the server adjusts the music and lighting to warmer tones. Conversely, if tension or anxiety is detected, the server works with staff to take swift action to improve the situation.

[0139] This invention provides a service that combines advanced emotion recognition, enabling it to maximize user satisfaction. This approach delivers a customized experience tailored to each individual user, differentiating it from other services.

[0140] The following describes the processing flow.

[0141] Step 1:

[0142] The user launches the app on their device, enters their authentication information on the login screen, and logs in. The device sends the entered information to the server, which authenticates it and displays the dashboard.

[0143] Step 2:

[0144] The user selects a reservation menu on the dashboard. They enter their desired date, time, and meal menu into their device and send the reservation information to the server. The server records the received reservation information in its database.

[0145] Step 3:

[0146] The server checks drone availability based on reservation information and determines whether a reservation is possible. If available, the server sends a reservation notification to the terminal, and the user confirms the reservation.

[0147] Step 4:

[0148] After the reservation is confirmed, the server will determine the feasibility of flight based on the weather information for the day. If the weather is good, it will set the drone flight schedule.

[0149] Step 5:

[0150] On the day of departure, the user arrives at the designated departure point. The terminal sends boarding confirmation information to the server, and once boarding is confirmed, the server instructs the drone to begin flight.

[0151] Step 6:

[0152] The emotion engine is mounted on the drone and collects the user's facial expressions and voice data in real time. This data is used to determine the user's emotions and is sent to a server.

[0153] Step 7:

[0154] The server analyzes emotional data and dynamically adjusts music and environmental settings according to the user's emotional state. For example, if relaxation is detected, it selects soothing music and adjusts the environment accordingly.

[0155] Step 8:

[0156] After the experience ends, the drone returns to its starting point and lands. The server sends a notification to the device that the experience has ended and requests feedback from the user through a survey. The user enters their feedback, and the device sends it to the server.

[0157] This entire process allows the system to provide a unique aerial experience tailored to each individual user, thereby improving user satisfaction.

[0158] (Example 2)

[0159] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0160] In the modern era, there is a demand for the effective use of space and the maximization of individual user experiences. In particular, in aerial dining experiences, ensuring safety while optimizing the experience based on user emotions is crucial. However, conventional systems have struggled to simultaneously meet these requirements. Therefore, the present invention aims to provide a new method for making dining experiences in unused spaces safer and more personalized.

[0161] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0162] In this invention, the server includes location information management means for managing the dining experience provided in unused space, control means for safely and stably controlling the target equipment, reservation means for managing reservations made by users, monitoring means for aggregating and analyzing user safety information via multiple measuring devices to ensure safety, and emotion analysis means for identifying the emotional state of users and optimizing the service. This makes it possible to provide a customized experience tailored to each individual user and maximize their satisfaction.

[0163] "Unused space" refers to areas that are not being utilized for their traditional purposes and are places that can be used for new services or activities.

[0164] "Managing the dining experience" refers to the overall operation and coordination of the dining services provided to customers, and includes processes such as reservation management, space control, and safety assurance.

[0165] "Location information management means" refers to a technical method or system for determining the precise location of devices and users within a space and adjusting their location as needed.

[0166] "Control means" refers to technologies or mechanisms for managing and adjusting the operation of equipment or systems in order to achieve safe and stable operation.

[0167] A "reservation method" refers to a method or system for users to apply for a service in advance and manage the available dates, times, and conditions.

[0168] "Monitoring measures" refer to technologies or processes used to check the situation in real time and detect anomalies in order to ensure the safety of equipment and users.

[0169] "Emotion analysis means" refers to a technology or mechanism for identifying emotions from a user's voice, facial expressions, gestures, etc., and adjusting services based on the results.

[0170] This invention relates to a system for managing and providing dining experiences in underutilized spaces. Specific embodiments for carrying out this invention are described below.

[0171] First, the server uses location management systems to track the position of aerial devices such as drones in real time. The server uses GPS and other high-precision location technologies to determine the device's position and enable precise navigation.

[0172] Next, the server manages the device's movement through control mechanisms. The server uses a flight control system to adjust the device's trajectory and speed, ensuring a safe and comfortable dining experience. The server also dynamically optimizes the device's operating conditions according to weather and aerial conditions.

[0173] Users can make reservations for dining experiences using a dedicated application on their devices. As a reservation method, the server receives reservation information and stores it in a database, effectively managing available resources and providing the optimal schedule.

[0174] Furthermore, each drone is equipped with multiple sensors, and the server aggregates the data obtained from these sensors to ensure safety through monitoring. If an anomaly is detected, the server immediately notifies the staff and takes the necessary countermeasures.

[0175] Regarding emotion analysis, emotion analysis tools are used to analyze the user's voice, facial expressions, and gestures in real time. Based on the results of the emotion analysis, the server adjusts music, lighting, and other service elements to provide a personalized and comfortable experience.

[0176] For example, if a user desires a romantic dinner at sunset on a sunny day, they can book through a dedicated app, and the experience will be tailored to their preferences. If the emotion analysis system detects a smile from the passenger, the server will adjust the lighting to a warmer tone and play appropriate music. In this way, the experience is optimized according to the user's emotions.

[0177] An example of a prompt using a generative AI model is: "Design a system that adjusts music and lighting based on the user's emotions during an aerial dinner experience. How will the emotion data be acquired and analyzed?"

[0178] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0179] Step 1:

[0180] Users make reservations using a dedicated application via their device. The information entered includes the desired date and time, the type of experience, and the number of participants. The device sends this information to a server, which records the received reservation information in a database. This updates the reservation list and optimizes the available resources.

[0181] Step 2:

[0182] The server obtains the drone's location information from GPS using a location information management system. The input is the current location of each drone, and the server processes this location information to calculate the drone's real-time flight path. As output, a safe flight route is generated and sent to the drone. This allows the drone to smoothly reach the designated area.

[0183] Step 3:

[0184] The server controls the drone's equipment via control devices. Inputs include the drone's flight conditions and weather data. The server analyzes this data, generates output such as motor speed and altitude adjustments, and transmits them to the drone. This process ensures safe drone flight and a comfortable user experience.

[0185] Step 4:

[0186] The server aggregates data from sensors mounted on the drone as a monitoring tool to ensure safety. Sensor data, including acceleration, temperature, and vibration, is used as input. The server analyzes this data and, if an anomaly is detected, generates a warning and notifies staff. This enables a rapid response and ensures the safety of users.

[0187] Step 5:

[0188] The server uses emotion analysis tools to analyze the user's emotional data in real time. User voice, facial expressions, and gestures are used as input. This data is analyzed using a generative AI model, and the user's emotional state is generated as output. Based on the determined emotion, the server outputs instructions to adjust lighting, music, and service content, and sends them to the device. This improves user comfort and optimizes the individual experience.

[0189] (Application Example 2)

[0190] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0191] When providing experiences using untapped spaces, it is essential to recognize users' emotions in real time and optimize the experience based on those emotions. This is necessary to provide personalized experiences that maximize user satisfaction and differentiate the service from others.

[0192] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0193] In this invention, the server includes location information management means for managing the user experience provided in unused space, control means for safely and stably controlling the target device, and emotion recognition means for analyzing emotion data acquired from the user and dynamically adjusting the experience content. This enables dynamic experience customization in accordance with the user's emotions.

[0194] "Unused space" refers to specific areas or locations that are not used for their usual purposes, and is a space that is utilized to provide new forms of user experiences.

[0195] "Location information management means" refers to technical means for managing and controlling the location of equipment and devices so that the experiences and services provided are carried out in the appropriate locations.

[0196] "Control means" refers to technical means that monitor the operation of a target device and make adjustments or give instructions as needed in order to ensure safe and stable operation.

[0197] A "reservation method" refers to a technical means that allows users to reserve or register for a service at a specific time and place in advance.

[0198] "Monitoring measures" are technical means that constitute part of a system for collecting and analyzing various types of information in order to ensure the safety of users and equipment.

[0199] "Emotion recognition means" are technical methods for analyzing a user's emotions and optimizing the services and experiences provided to match the user's current emotional state.

[0200] "Emotional data" refers to information that indicates the user's emotional state, and includes data obtained from voice, facial expressions, gestures, etc.

[0201] This invention is a system that provides a user experience in unused spaces and optimizes the experience through emotion recognition. Its components include location information management means, control means, reservation means, monitoring means, and emotion recognition means.

[0202] The server controls drones and other flying devices to provide experiences in untapped spaces, and uses location management means to deliver services safely and appropriately. This involves the use of GPS and other high-precision location technologies.

[0203] Users make reservations for experiences using their smartphones, and this information is sent to the server via the reservation system. The server records the reservation information in a database and creates an appropriate experience schedule.

[0204] The monitoring system ensures safety by collecting data in real time through sensors built into the device. If an anomaly is detected, an alert is issued quickly.

[0205] The emotion recognition system analyzes emotional data (voice, facial expressions, gestures, etc.) acquired from the user, and the server dynamically adjusts music, lighting, and other experience elements. This allows the user to receive an optimal experience tailored to their emotions at that time.

[0206] For example, if a user is seeking a relaxing environment, music and lighting that enhance relaxation will be selected based on emotional data. An example of a related prompt would be, "If the user desires a relaxing environment and this state is detected, suggest appropriate music and beverages."

[0207] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0208] Step 1:

[0209] Users book aerial experiences using their smartphones. The booking information (date, time, location, and desired experience) entered via the device is sent to the server. The server receives this information and records it in its database. This creates the user's booking schedule.

[0210] Step 2:

[0211] The server manages the drone's location based on reservation information. The server processes GPS data and calculates the optimal flight route. The drone moves according to instructions from the server to reach the designated location. This ensures that the defined experience space is maintained.

[0212] Step 3:

[0213] Various sensors mounted on the drone collect environmental and safety data in real time. This data is sent to a server, which analyzes it and monitors for any anomalies. If an anomaly is detected, an alert is immediately generated, enabling a swift response.

[0214] Step 4:

[0215] The server uses emotion recognition to receive voice, facial, and gesture data from the user. The server then uses a generative AI model to analyze this input data and determine the user's emotional state. For example, it can assess the user's stress level based on changes in voice tone and facial expressions.

[0216] Step 5:

[0217] Based on the user's emotional state, the server adjusts the music and lighting settings. The server recommends optimal settings using prompts, and the environmental elements within the drone are dynamically changed according to these instructions. This allows the user to experience something that matches their current emotions.

[0218] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0219] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0220] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0221] [Second Embodiment]

[0222] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0223] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0224] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0225] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0226] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0227] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0228] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0229] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0230] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0231] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0232] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0233] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0234] This invention is implemented as a system for providing a new tourism experience utilizing the air. Specific embodiments of each element are described below.

[0235] This system allows users to book aerial restaurants through a dedicated application and provides integrated services including location information management, device control, reservation management, and monitoring.

[0236] 1. Location information management

[0237] The server manages the drone's precise location information and sets the route from the departure point to the destination. It monitors the location in real time and constantly ensures safety during flight. Predictive algorithms are used to calculate the optimal flight route based on weather conditions and traffic conditions.

[0238] 2. Device Control

[0239] The server sends control signals to the drone instructing it to fly steadily. These control signals include altitude, speed, and route changes. This allows the drone to safely navigate its target path.

[0240] 3. Reservation Management

[0241] The user accesses the reservation screen using their device and selects their desired date, time, and menu. The server receives the reservation information and registers it in the database. Based on this, it automatically adjusts the availability of drones and seats and sends a reservation confirmation notification to the user's device.

[0242] 4. Monitoring

[0243] The server monitors the safety and comfort of users while they are on board through various sensors mounted on the drone. It monitors seat movement, air pressure, temperature, etc., and instantly issues an alert if any abnormality occurs. To ensure user safety, it coordinates with ground staff to enable a rapid response.

[0244] Specific example

[0245] If a user wishes to make a Sunday lunch reservation, they open the reservation screen in the dedicated app. After selecting their desired menu and entering their preferred time, the device sends this information to the server. The server checks the drone's availability and flight route, and confirms the reservation. On the day of the reservation, the user gathers at the designated departure point and boards the drone. The server monitors the flight in real time, ensuring a safe dining experience.

[0246] Thus, the present invention allows users to enjoy an unparalleled aerial sightseeing experience and effectively alleviates congestion on the ground.

[0247] The following describes the processing flow.

[0248] Step 1:

[0249] The user launches the app on their device and logs in by entering their registered email address and password on the login screen. The device sends this information to the server, which verifies it against the information in the database. If authentication is successful, the server displays the user's dashboard on the device.

[0250] Step 2:

[0251] The user selects a reservation option from the dashboard and enters their desired date, time, and meal menu. The terminal sends the selected reservation information to the server. The server checks the availability of drones and seats in its database and determines if a reservation is possible.

[0252] Step 3:

[0253] If the server determines that a reservation is available, it prompts the user to confirm the reservation. The user confirms the reservation on their device and presses the approve button. The device then sends the approved reservation information back to the server. The server confirms the reservation and sends a reservation completion notification to the device.

[0254] Step 4:

[0255] On the day of the reservation, the server retrieves real-time weather data to confirm flight safety. If the weather is good, preparations for drone takeoff begin. The server sends the flight path and takeoff instructions to the drone.

[0256] Step 5:

[0257] Once the user arrives at the designated departure point, they use a terminal to confirm their boarding. The terminal sends boarding information to the server, and once boarding is confirmed, the server instructs the drone to depart.

[0258] Step 6:

[0259] During flight, the server receives data from the drone's sensors and monitors user safety in real time. If an anomaly is detected, the server issues an alert and communicates the situation to ground staff.

[0260] Step 7:

[0261] When the user finishes their meal and the scheduled time arrives, the server notifies the drone of the return route. Once the drone safely lands at the starting point, the server sends a notification to the terminal that the experience has ended.

[0262] Step 8:

[0263] After the experience ends, the server sends a feedback questionnaire to the user's device. The user enters their evaluation of the experience, and the device sends this back to the server. The server stores the feedback in a database and uses it to improve the service.

[0264] (Example 1)

[0265] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0266] When providing dining experiences that utilize unused spaces, it is necessary to ensure the safety and comfort of users while simultaneously managing reservations efficiently and setting up optimized travel routes. However, conventional technologies have found it difficult to satisfy these requirements at the same time. This invention aims to solve these problems and provide users with a new aerial dining experience.

[0267] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0268] In this invention, the server includes location information management means for managing dining experiences provided in unused spaces, control means for stable control of target devices, and reservation means for accepting user reservations. This enables users to safely and efficiently enjoy new tourism experiences.

[0269] A "location information management system" is a system for determining the location of a target device and setting and managing the optimal movement route in order to provide a dining experience in an unused space.

[0270] A "control means" is a system that has the function of generating and transmitting control signals necessary to operate the target device safely and stably.

[0271] A "reservation system" is a system that has the function of recording and managing information when users reserve services or experiences in advance.

[0272] A "monitoring system" is a system that collects various types of information in real time and has the necessary functions to ensure user safety and the normal operation of equipment.

[0273] An "input method" is an interface that allows users to input information regarding travel and dining experience reservations via a terminal and send it to the server.

[0274] A "flight planning system" is a system that uses a predictive algorithm to formulate a plan for the target device to travel along the optimal path.

[0275] To implement the invention, the server constitutes a system with diverse functions. The server uses location information management means to precisely manage location information for providing a dining experience through unused airspace, and sets the route from the drone's departure point to its destination. The server uses a prediction algorithm to analyze weather conditions and traffic conditions and calculate the optimal flight route. Specifically, it uses a weather API to obtain the latest data and reflects it in the flight route in real time.

[0276] Simultaneously, the server uses control mechanisms to generate control signals necessary to maintain stable flight for the drone, sending instructions including altitude and speed adjustments and route changes. This allows the drone to navigate the target path safely and efficiently. This process ensures user safety while providing an exciting aerial dining experience.

[0277] The reservation system provides users with access to the reservation screen for the sky restaurant using their devices. Users select their desired date, time, and menu on the screen and send the reservation information from their device to the server. The server processes the reservation information in real time and registers it in the database. This process automatically adjusts the reservation status, and a reservation confirmation notification is sent to the device within seconds.

[0278] Furthermore, the server uses monitoring devices to collect data in real time from various sensors mounted on the drone, maintaining user safety and comfort. The data obtained from each measuring instrument is also shared with ground staff, and any abnormalities are quickly notified.

[0279] For example, if a user wants to make a weekend lunch reservation, they would use a specific mobile application to select the menu and date / time. The server would then check drone availability and flight route planning in real time and confirm the reservation. After that, the server would make any necessary adjustments to the environment during the flight.

[0280] As an example of a prompt sentence to be input into the generative AI model, there is one such as "Please explain in detail each function of the system for maximizing the enjoyment of the in-air dining experience." Through this, the overall picture of the invention is conveyed to the user, intending to obtain a deeper understanding.

[0281] The flow of the specific process in Example 1 will be described using FIG. 11.

[0282] Step 1:

[0283] The user starts up the terminal and accesses the reservation application. What the user inputs is the desired date and time and menu selection, and the terminal sends this information to the server. The input data is provided to the server as the reservation details.

[0284] Step 2:

[0285] The server analyzes the reservation information received from the terminal. Based on the input information, the server registers the reservation in the database. In this process, the server also checks the current availability and schedule of the drone and determines whether it can handle it. As a result, the status of whether the reservation can be made is output.

[0286] Step 3:

[0287] When the reservation is approved, the server formulates a flight plan. The server obtains the latest weather data from the weather API and calculates the optimal flight route using a prediction algorithm. The inputs are the current weather conditions and the departure and arrival locations, and the output is the detailed flight schedule for instructing the drone.

[0288] Step 4:

[0289] After the reservation process and flight plan are completed, the server sends a reservation confirmation to the terminal. The terminal receives the confirmation information from the server and displays it to the user. What is displayed is the details of the reservation, including the departure location and time, the selected menu, etc.

[0290] Step 5:

[0291] Users gather at the departure point at the designated date and time and perform a final check-in using a terminal. The terminal sends the check-in information to the server for final confirmation of the reservation. In this step, the check-in information is input, and the check-in status, which is compiled by the server, is output.

[0292] Step 6:

[0293] The server collects and monitors real-time data from sensors mounted on the drone. Information such as temperature, air pressure, and seat movement is used as input, and the server analyzes this data to detect any abnormalities. The output is either a continuous operation command if everything is normal, or an alert if an abnormality is detected.

[0294] (Application Example 1)

[0295] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0296] In recent years, there has been growing interest in providing new experiences that utilize untapped spaces. However, experiences, especially those taking place in the air, often lack sufficient safety and real-time management, and may not be able to effectively notify users of their delivery. Furthermore, various challenges exist, such as the increasing difficulty of optimizing travel routes and aggregating and analyzing safety information using multiple measuring instruments, depending on the scale of the project.

[0297] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0298] In this invention, the server includes location information management means for managing the dining experience provided in unused space, control means for safely and stably delivering food to an aerial transport device, reservation means for managing reservations made by users, monitoring means for collecting various information in real time and ensuring safety, and delivery completion notification means for sending notifications to user terminals. This enables the safe and comfortable provision of a new aerial experience to users, while simultaneously improving the quality of the experience through efficient notifications and route optimization.

[0299] "Unused space" refers to space that does not serve its intended purpose through conventional use, or is simply not being used.

[0300] "Location information management means for managing the dining experience" refers to technical means used to determine the precise location of the dining space and set the optimal travel route.

[0301] An "aerial transport device" refers to a device for moving goods or services through the air, and in this invention, it specifically refers to a device for delivering food.

[0302] "Control means" refers to technical means that provide signals or instructions to ensure the stable and safe operation of equipment or machinery.

[0303] "Reservation management methods" refer to methods and systems for receiving and managing users' reservation information.

[0304] "Monitoring measures" refer to technical means used to ensure security by collecting various types of information in real time and analyzing the data.

[0305] A "delivery completion notification system" is a system that has the function of informing the user that the delivery of goods has been completed.

[0306] This system is designed to provide a safe and efficient aerial experience by making use of unused space. The server manages the dining experience by handling location information and controlling aerial transportation devices. Specifically, it calculates an optimal route by leveraging GPS data and weather information, and transmits control signals to aerial transportation devices such as drones. In this process, a prediction algorithm using Python is implemented.

[0307] The user's terminal functions as a reservation means and provides an interface for the user to select the date, time, and menu they desire. The reservation information is stored on the cloud and managed in real-time in coordination with the availability status of the drones. This part is realized by a mobile application using React Native or Flutter.

[0308] To ensure the safety of users, the server uses monitoring means to analyze information from various sensors installed on the drones. This includes data from temperature sensors, pressure sensors, and acceleration sensors, which enhance safety through software for sensor signal processing.

[0309] As a specific example, when a family planning a picnic in the park uses the app to reserve food, the server makes the drone fly along an optimal route and safely delivers the food to the user-designated pickup area. The entire process is seamless, and users can enjoy the new experience with confidence.

[0310] An example of a prompt sentence to input into the generative AI model is: "Please explain the user experience of the aerial delivery system app. Specifically, please tell me at what steps the order is placed and how the drone delivers the food."

[0311] The flow of the specific process in Application Example 1 will be described using Figure 12.

[0312] Step 1:

[0313] The terminal accepts reservations for meals from the user. When the user selects the date, time, and menu through the app interface, that information is sent from the terminal to the cloud server. The input is the user's selection information, and the output is the reservation data stored in the cloud.

[0314] Step 2:

[0315] The server checks drone availability and flight zones based on the received reservation data. Specifically, it retrieves reservation information from a database and uses Python to determine the optimal drone and flight route. The input is reservation data, and the output is the drone selection result.

[0316] Step 3:

[0317] The server collects weather and GPS data in real time and instructs the drone on a safe flight path. This involves using an algorithm to calculate the optimal path based on input data from sensors and transmitting it to the drone as a control signal. The input is sensor and position data, and the output is the control signal.

[0318] Step 4:

[0319] The server sends a notification to the user's device to confirm the reservation and inform them of the scheduled delivery time. The notification includes a reservation confirmation message and is displayed on the device's user interface as a status check for the user. The input is the drone's flight plan, and the output is the notification message to the user.

[0320] Step 5:

[0321] Once the drone takes off, the server monitors its location and status in real time. The server periodically collects data from the sensors to check for any abnormalities. The input is the drone's sensor data, and the output is the monitoring information.

[0322] Step 6:

[0323] After safe delivery by drone is complete, the server sends a delivery completion notification to the terminal. This informs the user that their food has arrived, and a delivery completion message is displayed on the terminal. The input is the delivery completion status, and the output is the completion notification to the user.

[0324] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0325] This invention is a system that recognizes the user's emotions in real time during an aerial dining experience and optimizes the experience based on those emotions. Specific embodiments for carrying out the invention are described below.

[0326] In addition to location information management, device control, reservation management, and monitoring, this system incorporates an emotion engine that recognizes user emotions, thereby further improving the user experience.

[0327] 1. Location information management

[0328] The server manages the real-time positioning of drones that provide dining spaces. Using high-precision positioning technology, it adjusts the drones to navigate safely and efficiently and reach the designated area.

[0329] 2. Device Control

[0330] The server transmits signals to control the drone's flight path and maintain optimal flight conditions to provide a safe and comfortable dining experience.

[0331] 3. Reservation Management

[0332] Users make reservations using a dedicated app, and the server receives this information and records it in a database. Based on the reservation status, the system adjusts the availability of drones and seats to provide the optimal schedule.

[0333] 4. Monitoring

[0334] The server monitors the safety of users and equipment through sensors mounted on each drone. In the event of an anomaly, it quickly notifies staff and takes necessary measures.

[0335] 5. Emotion recognition

[0336] The emotion engine analyzes data such as voice, facial expressions, and gestures acquired from the user to determine their emotional state in real time. Based on the determined emotion, the server adjusts music, lighting, service content, and other elements to enhance the user's comfort.

[0337] Specific example

[0338] If a user desires a romantic aerial dinner at sunset on a clear day, they can book the service. During the flight, the emotion engine detects the user's smile and relaxed posture, and the server adjusts the music and lighting to warmer tones. Conversely, if tension or anxiety is detected, the server works with staff to take swift action to improve the situation.

[0339] This invention provides a service that combines advanced emotion recognition, enabling it to maximize user satisfaction. This approach delivers a customized experience tailored to each individual user, differentiating it from other services.

[0340] The following describes the processing flow.

[0341] Step 1:

[0342] The user launches the app on their device, enters their authentication information on the login screen, and logs in. The device sends the entered information to the server, which authenticates it and displays the dashboard.

[0343] Step 2:

[0344] The user selects a reservation menu on the dashboard. They enter their desired date, time, and meal menu into their device and send the reservation information to the server. The server records the received reservation information in its database.

[0345] Step 3:

[0346] The server checks drone availability based on reservation information and determines whether a reservation is possible. If available, the server sends a reservation notification to the terminal, and the user confirms the reservation.

[0347] Step 4:

[0348] After the reservation is confirmed, the server will determine the feasibility of flight based on the weather information for the day. If the weather is good, it will set the drone flight schedule.

[0349] Step 5:

[0350] On the day of departure, the user arrives at the designated departure point. The terminal sends boarding confirmation information to the server, and once boarding is confirmed, the server instructs the drone to begin flight.

[0351] Step 6:

[0352] The emotion engine is mounted on the drone and collects the user's facial expressions and voice data in real time. This data is used to determine the user's emotions and is sent to a server.

[0353] Step 7:

[0354] The server analyzes emotional data and dynamically adjusts music and environmental settings according to the user's emotional state. For example, if relaxation is detected, it selects soothing music and adjusts the environment accordingly.

[0355] Step 8:

[0356] After the experience ends, the drone returns to its starting point and lands. The server sends a notification to the device that the experience has ended and requests feedback from the user through a survey. The user enters their feedback, and the device sends it to the server.

[0357] This entire process allows the system to provide a unique aerial experience tailored to each individual user, thereby improving user satisfaction.

[0358] (Example 2)

[0359] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0360] In the modern era, there is a demand for the effective use of space and the maximization of individual user experiences. In particular, in aerial dining experiences, ensuring safety while optimizing the experience based on user emotions is crucial. However, conventional systems have struggled to simultaneously meet these requirements. Therefore, the present invention aims to provide a new method for making dining experiences in unused spaces safer and more personalized.

[0361] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0362] In this invention, the server includes location information management means for managing the dining experience provided in unused space, control means for safely and stably controlling the target equipment, reservation means for managing reservations made by users, monitoring means for aggregating and analyzing user safety information via multiple measuring devices to ensure safety, and emotion analysis means for identifying the emotional state of users and optimizing the service. This makes it possible to provide a customized experience tailored to each individual user and maximize their satisfaction.

[0363] "Unused space" refers to areas that are not being utilized for their traditional purposes and are places that can be used for new services or activities.

[0364] "Managing the dining experience" refers to the overall operation and coordination of the dining services provided to customers, and includes processes such as reservation management, space control, and safety assurance.

[0365] "Location information management means" refers to a technical method or system for determining the precise location of devices and users within a space and adjusting their location as needed.

[0366] "Control means" refers to technologies or mechanisms for managing and adjusting the operation of equipment or systems in order to achieve safe and stable operation.

[0367] A "reservation method" refers to a method or system for users to apply for a service in advance and manage the available dates, times, and conditions.

[0368] "Monitoring measures" refer to technologies or processes used to check the situation in real time and detect anomalies in order to ensure the safety of equipment and users.

[0369] "Emotion analysis means" refers to a technology or mechanism for identifying emotions from a user's voice, facial expressions, gestures, etc., and adjusting services based on the results.

[0370] This invention relates to a system for managing and providing dining experiences in underutilized spaces. Specific embodiments for carrying out this invention are described below.

[0371] First, the server uses location management systems to track the position of aerial devices such as drones in real time. The server uses GPS and other high-precision location technologies to determine the device's position and enable precise navigation.

[0372] Next, the server manages the device's movement through control mechanisms. The server uses a flight control system to adjust the device's trajectory and speed, ensuring a safe and comfortable dining experience. The server also dynamically optimizes the device's operating conditions according to weather and aerial conditions.

[0373] Users can make reservations for dining experiences using a dedicated application on their devices. As a reservation method, the server receives reservation information and stores it in a database, effectively managing available resources and providing the optimal schedule.

[0374] Furthermore, each drone is equipped with multiple sensors, and the server aggregates the data obtained from these sensors to ensure safety through monitoring. If an anomaly is detected, the server immediately notifies the staff and takes the necessary countermeasures.

[0375] Regarding emotion analysis, emotion analysis tools are used to analyze the user's voice, facial expressions, and gestures in real time. Based on the results of the emotion analysis, the server adjusts music, lighting, and other service elements to provide a personalized and comfortable experience.

[0376] For example, if a user desires a romantic dinner at sunset on a sunny day, they can book through a dedicated app, and the experience will be tailored to their preferences. If the emotion analysis system detects a smile from the passenger, the server will adjust the lighting to a warmer tone and play appropriate music. In this way, the experience is optimized according to the user's emotions.

[0377] An example of a prompt using a generative AI model is: "Design a system that adjusts music and lighting based on the user's emotions during an aerial dinner experience. How will the emotion data be acquired and analyzed?"

[0378] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0379] Step 1:

[0380] Users make reservations using a dedicated application via their device. The information entered includes the desired date and time, the type of experience, and the number of participants. The device sends this information to a server, which records the received reservation information in a database. This updates the reservation list and optimizes the available resources.

[0381] Step 2:

[0382] The server obtains the drone's location information from GPS using a location information management system. The input is the current location of each drone, and the server processes this location information to calculate the drone's real-time flight path. As output, a safe flight route is generated and sent to the drone. This allows the drone to smoothly reach the designated area.

[0383] Step 3:

[0384] The server controls the drone's equipment via control devices. Inputs include the drone's flight conditions and weather data. The server analyzes this data, generates output such as motor speed and altitude adjustments, and transmits them to the drone. This process ensures safe drone flight and a comfortable user experience.

[0385] Step 4:

[0386] The server aggregates data from sensors mounted on the drone as a monitoring tool to ensure safety. Sensor data, including acceleration, temperature, and vibration, is used as input. The server analyzes this data and, if an anomaly is detected, generates a warning and notifies staff. This enables a rapid response and ensures the safety of users.

[0387] Step 5:

[0388] The server uses emotion analysis tools to analyze the user's emotional data in real time. User voice, facial expressions, and gestures are used as input. This data is analyzed using a generative AI model, and the user's emotional state is generated as output. Based on the determined emotion, the server outputs instructions to adjust lighting, music, and service content, and sends them to the device. This improves user comfort and optimizes the individual experience.

[0389] (Application Example 2)

[0390] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0391] When providing experiences using untapped spaces, it is essential to recognize users' emotions in real time and optimize the experience based on those emotions. This is necessary to provide personalized experiences that maximize user satisfaction and differentiate the service from others.

[0392] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0393] In this invention, the server includes location information management means for managing the user experience provided in unused space, control means for safely and stably controlling the target device, and emotion recognition means for analyzing emotion data acquired from the user and dynamically adjusting the experience content. This enables dynamic experience customization in accordance with the user's emotions.

[0394] "Unused space" refers to specific areas or locations that are not used for their usual purposes, and is a space that is utilized to provide new forms of user experiences.

[0395] "Location information management means" refers to technical means for managing and controlling the location of equipment and devices so that the experiences and services provided are carried out in the appropriate locations.

[0396] "Control means" refers to technical means that monitor the operation of a target device and make adjustments or give instructions as needed in order to ensure safe and stable operation.

[0397] A "reservation method" refers to a technical means that allows users to reserve or register for a service at a specific time and place in advance.

[0398] "Monitoring measures" are technical means that constitute part of a system for collecting and analyzing various types of information in order to ensure the safety of users and equipment.

[0399] "Emotion recognition means" are technical methods for analyzing a user's emotions and optimizing the services and experiences provided to match the user's current emotional state.

[0400] "Emotional data" refers to information that indicates the user's emotional state, and includes data obtained from voice, facial expressions, gestures, etc.

[0401] This invention is a system that provides a user experience in unused spaces and optimizes the experience through emotion recognition. Its components include location information management means, control means, reservation means, monitoring means, and emotion recognition means.

[0402] The server controls drones and other flying devices to provide experiences in untapped spaces, and uses location management means to deliver services safely and appropriately. This involves the use of GPS and other high-precision location technologies.

[0403] Users make reservations for experiences using their smartphones, and this information is sent to the server via the reservation system. The server records the reservation information in a database and creates an appropriate experience schedule.

[0404] The monitoring system ensures safety by collecting data in real time through sensors built into the device. If an anomaly is detected, an alert is issued quickly.

[0405] The emotion recognition system analyzes emotional data (voice, facial expressions, gestures, etc.) acquired from the user, and the server dynamically adjusts music, lighting, and other experience elements. This allows the user to receive an optimal experience tailored to their emotions at that time.

[0406] For example, if a user is seeking a relaxing environment, music and lighting that enhance relaxation will be selected based on emotional data. An example of a related prompt would be, "If the user desires a relaxing environment and this state is detected, suggest appropriate music and beverages."

[0407] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0408] Step 1:

[0409] Users book aerial experiences using their smartphones. The booking information (date, time, location, and desired experience) entered via the device is sent to the server. The server receives this information and records it in its database. This creates the user's booking schedule.

[0410] Step 2:

[0411] The server manages the drone's location based on reservation information. The server processes GPS data and calculates the optimal flight route. The drone moves according to instructions from the server to reach the designated location. This ensures that the defined experience space is maintained.

[0412] Step 3:

[0413] Various sensors mounted on the drone collect environmental and safety data in real time. This data is sent to a server, which analyzes it and monitors for any anomalies. If an anomaly is detected, an alert is immediately generated, enabling a swift response.

[0414] Step 4:

[0415] The server uses emotion recognition to receive voice, facial, and gesture data from the user. The server then uses a generative AI model to analyze this input data and determine the user's emotional state. For example, it can assess the user's stress level based on changes in voice tone and facial expressions.

[0416] Step 5:

[0417] Based on the user's emotional state, the server adjusts the music and lighting settings. The server recommends optimal settings using prompts, and the environmental elements within the drone are dynamically changed according to these instructions. This allows the user to experience something that matches their current emotions.

[0418] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0419] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0420] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0421] [Third Embodiment]

[0422] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0423] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0424] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0425] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0426] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0427] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0428] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0429] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0430] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0431] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0432] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0433] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0434] This invention is implemented as a system for providing a new tourism experience utilizing the air. Specific embodiments of each element are described below.

[0435] This system allows users to book aerial restaurants through a dedicated application and provides integrated services including location information management, device control, reservation management, and monitoring.

[0436] 1. Location information management

[0437] The server manages the drone's precise location information and sets the route from the departure point to the destination. It monitors the location in real time and constantly ensures safety during flight. Predictive algorithms are used to calculate the optimal flight route based on weather conditions and traffic conditions.

[0438] 2. Device Control

[0439] The server sends control signals to the drone instructing it to fly steadily. These control signals include altitude, speed, and route changes. This allows the drone to safely navigate its target path.

[0440] 3. Reservation Management

[0441] The user accesses the reservation screen using their device and selects their desired date, time, and menu. The server receives the reservation information and registers it in the database. Based on this, it automatically adjusts the availability of drones and seats and sends a reservation confirmation notification to the user's device.

[0442] 4. Monitoring

[0443] The server monitors the safety and comfort of users while they are on board through various sensors mounted on the drone. It monitors seat movement, air pressure, temperature, etc., and instantly issues an alert if any abnormality occurs. To ensure user safety, it coordinates with ground staff to enable a rapid response.

[0444] Specific example

[0445] If a user wishes to make a Sunday lunch reservation, they open the reservation screen in the dedicated app. After selecting their desired menu and entering their preferred time, the device sends this information to the server. The server checks the drone's availability and flight route, and confirms the reservation. On the day of the reservation, the user gathers at the designated departure point and boards the drone. The server monitors the flight in real time, ensuring a safe dining experience.

[0446] Thus, the present invention allows users to enjoy an unparalleled aerial sightseeing experience and effectively alleviates congestion on the ground.

[0447] The following describes the processing flow.

[0448] Step 1:

[0449] The user launches the app on their device and logs in by entering their registered email address and password on the login screen. The device sends this information to the server, which verifies it against the information in the database. If authentication is successful, the server displays the user's dashboard on the device.

[0450] Step 2:

[0451] The user selects a reservation option from the dashboard and enters their desired date, time, and meal menu. The terminal sends the selected reservation information to the server. The server checks the availability of drones and seats in its database and determines if a reservation is possible.

[0452] Step 3:

[0453] If the server determines that a reservation is available, it prompts the user to confirm the reservation. The user confirms the reservation on their device and presses the approve button. The device then sends the approved reservation information back to the server. The server confirms the reservation and sends a reservation completion notification to the device.

[0454] Step 4:

[0455] On the day of the reservation, the server retrieves real-time weather data to confirm flight safety. If the weather is good, preparations for drone takeoff begin. The server sends the flight path and takeoff instructions to the drone.

[0456] Step 5:

[0457] Once the user arrives at the designated departure point, they use a terminal to confirm their boarding. The terminal sends boarding information to the server, and once boarding is confirmed, the server instructs the drone to depart.

[0458] Step 6:

[0459] During flight, the server receives data from the drone's sensors and monitors user safety in real time. If an anomaly is detected, the server issues an alert and communicates the situation to ground staff.

[0460] Step 7:

[0461] When the user finishes their meal and the scheduled time arrives, the server notifies the drone of the return route. Once the drone safely lands at the starting point, the server sends a notification to the terminal that the experience has ended.

[0462] Step 8:

[0463] After the experience ends, the server sends a feedback questionnaire to the user's device. The user enters their evaluation of the experience, and the device sends this back to the server. The server stores the feedback in a database and uses it to improve the service.

[0464] (Example 1)

[0465] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0466] When providing dining experiences that utilize unused spaces, it is necessary to ensure the safety and comfort of users while simultaneously managing reservations efficiently and setting up optimized travel routes. However, conventional technologies have found it difficult to satisfy these requirements at the same time. This invention aims to solve these problems and provide users with a new aerial dining experience.

[0467] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0468] In this invention, the server includes location information management means for managing dining experiences provided in unused spaces, control means for stable control of target devices, and reservation means for accepting user reservations. This enables users to safely and efficiently enjoy new tourism experiences.

[0469] A "location information management system" is a system for determining the location of a target device and setting and managing the optimal movement route in order to provide a dining experience in an unused space.

[0470] A "control means" is a system that has the function of generating and transmitting control signals necessary to operate the target device safely and stably.

[0471] A "reservation system" is a system that has the function of recording and managing information when users reserve services or experiences in advance.

[0472] A "monitoring system" is a system that collects various types of information in real time and has the necessary functions to ensure user safety and the normal operation of equipment.

[0473] An "input method" is an interface that allows users to input information regarding travel and dining experience reservations via a terminal and send it to the server.

[0474] A "flight planning system" is a system that uses a predictive algorithm to formulate a plan for the target device to travel along the optimal path.

[0475] To implement the invention, the server constitutes a system with diverse functions. The server uses location information management means to precisely manage location information for providing a dining experience through unused airspace, and sets the route from the drone's departure point to its destination. The server uses a prediction algorithm to analyze weather conditions and traffic conditions and calculate the optimal flight route. Specifically, it uses a weather API to obtain the latest data and reflects it in the flight route in real time.

[0476] Simultaneously, the server uses control mechanisms to generate control signals necessary to maintain stable flight for the drone, sending instructions including altitude and speed adjustments and route changes. This allows the drone to navigate the target path safely and efficiently. This process ensures user safety while providing an exciting aerial dining experience.

[0477] The reservation system provides users with access to the reservation screen for the sky restaurant using their devices. Users select their desired date, time, and menu on the screen and send the reservation information from their device to the server. The server processes the reservation information in real time and registers it in the database. This process automatically adjusts the reservation status, and a reservation confirmation notification is sent to the device within seconds.

[0478] Furthermore, the server uses monitoring devices to collect data in real time from various sensors mounted on the drone, maintaining user safety and comfort. The data obtained from each measuring instrument is also shared with ground staff, and any abnormalities are quickly notified.

[0479] For example, if a user wants to make a weekend lunch reservation, they would use a specific mobile application to select the menu and date / time. The server would then check drone availability and flight route planning in real time and confirm the reservation. After that, the server would make any necessary adjustments to the environment during the flight.

[0480] An example of a prompt to input into the generating AI model is, "Please describe in detail each function of the system to maximize the enjoyment of the aerial dining experience." The intention is that this will convey the overall picture of the invention to the user and lead to a deeper understanding.

[0481] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0482] Step 1:

[0483] The user activates the terminal and accesses the reservation application. The user enters their desired date and time and menu selection, and the terminal sends this information to the server. The entered data is then provided to the server as the reservation details.

[0484] Step 2:

[0485] The server analyzes the reservation information received from the terminal. Based on the input information, the server registers the reservation in the database. In this process, the server also checks the current availability and schedule of drones to determine if it is possible to accommodate the request. As a result, a status indicating whether or not the reservation can be made is output.

[0486] Step 3:

[0487] The server develops a flight plan once the booking is approved. The server retrieves the latest weather data from a weather API and uses a forecasting algorithm to calculate the optimal flight route. The inputs are current weather conditions and departure and arrival points, while the output is a detailed flight schedule to instruct the drone.

[0488] Step 4:

[0489] After the server completes the booking process and flight planning, it sends a booking confirmation to the terminal. The terminal receives the confirmation information from the server and displays it to the user. The displayed information includes booking details such as the departure point and time, and the selected menu.

[0490] Step 5:

[0491] Users gather at the departure point at the designated date and time and perform a final check-in using a terminal. The terminal sends the check-in information to the server for final confirmation of the reservation. In this step, the check-in information is input, and the check-in status, which is compiled by the server, is output.

[0492] Step 6:

[0493] The server collects and monitors real-time data from sensors mounted on the drone. Information such as temperature, air pressure, and seat movement is used as input, and the server analyzes this data to detect any abnormalities. The output is either a continuous operation command if everything is normal, or an alert if an abnormality is detected.

[0494] (Application Example 1)

[0495] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0496] In recent years, there has been growing interest in providing new experiences that utilize untapped spaces. However, experiences, especially those taking place in the air, often lack sufficient safety and real-time management, and may not be able to effectively notify users of their delivery. Furthermore, various challenges exist, such as the increasing difficulty of optimizing travel routes and aggregating and analyzing safety information using multiple measuring instruments, depending on the scale of the project.

[0497] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0498] In this invention, the server includes location information management means for managing the dining experience provided in unused space, control means for safely and stably delivering food to an aerial transport device, reservation means for managing reservations made by users, monitoring means for collecting various information in real time and ensuring safety, and delivery completion notification means for sending notifications to user terminals. This enables the safe and comfortable provision of a new aerial experience to users, while simultaneously improving the quality of the experience through efficient notifications and route optimization.

[0499] "Unused space" refers to space that does not serve its intended purpose through conventional use, or is simply not being used.

[0500] "Location information management means for managing the dining experience" refers to technical means used to determine the precise location of the dining space and set the optimal travel route.

[0501] An "aerial transport device" refers to a device for moving goods or services through the air, and in this invention, it specifically refers to a device for delivering food.

[0502] "Control means" refers to technical means that provide signals or instructions to ensure the stable and safe operation of equipment or machinery.

[0503] "Reservation management methods" refer to methods and systems for receiving and managing users' reservation information.

[0504] "Monitoring measures" refer to technical means used to ensure security by collecting various types of information in real time and analyzing the data.

[0505] A "delivery completion notification system" is a system that has the function of informing the user that the delivery of goods has been completed.

[0506] This system is designed to provide a safe and efficient aerial experience utilizing untapped space. The server manages location information and controls aerial transport devices to oversee the dining experience. Specifically, it uses GPS data and weather information to calculate the optimal route and sends control signals to aerial transport devices such as drones. A prediction algorithm using Python is implemented in this process.

[0507] The user's device functions as a reservation tool, providing an interface for selecting the desired date, time, and menu. Reservation information is stored in the cloud and managed in real-time in conjunction with drone availability. This part is implemented using a mobile application built with React Native and Flutter.

[0508] To ensure user safety, the server uses monitoring tools to analyze information from various sensors mounted on the drone. This includes data from temperature, barometric pressure, and acceleration sensors, which are processed through software that enhances safety.

[0509] For example, if a family planning a picnic in a park uses the app to order food, the server will fly a drone along the optimal route and safely deliver the food to the user's designated pickup area. The entire process is seamless, allowing users to enjoy a new experience with peace of mind.

[0510] An example of a prompt to input into the generating AI model is: "Please describe the user experience of an aerial delivery system app. Specifically, please explain the steps involved in placing an order and how the drone delivers the food."

[0511] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0512] Step 1:

[0513] The terminal accepts reservations for meals from the user. When the user selects the date, time, and menu through the app interface, that information is sent from the terminal to the cloud server. The input is the user's selection information, and the output is the reservation data stored in the cloud.

[0514] Step 2:

[0515] The server checks drone availability and flight zones based on the received reservation data. Specifically, it retrieves reservation information from a database and uses Python to determine the optimal drone and flight route. The input is reservation data, and the output is the drone selection result.

[0516] Step 3:

[0517] The server collects weather and GPS data in real time and instructs the drone on a safe flight path. This involves using an algorithm to calculate the optimal path based on input data from sensors and transmitting it to the drone as a control signal. The input is sensor and position data, and the output is the control signal.

[0518] Step 4:

[0519] The server sends a notification to the user's device to confirm the reservation and inform them of the scheduled delivery time. The notification includes a reservation confirmation message and is displayed on the device's user interface as a status check for the user. The input is the drone's flight plan, and the output is the notification message to the user.

[0520] Step 5:

[0521] Once the drone takes off, the server monitors its location and status in real time. The server periodically collects data from the sensors to check for any abnormalities. The input is the drone's sensor data, and the output is the monitoring information.

[0522] Step 6:

[0523] After safe delivery by drone is complete, the server sends a delivery completion notification to the terminal. This informs the user that their food has arrived, and a delivery completion message is displayed on the terminal. The input is the delivery completion status, and the output is the completion notification to the user.

[0524] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0525] This invention is a system that recognizes the user's emotions in real time during an aerial dining experience and optimizes the experience based on those emotions. Specific embodiments for carrying out the invention are described below.

[0526] In addition to location information management, device control, reservation management, and monitoring, this system incorporates an emotion engine that recognizes user emotions, thereby further improving the user experience.

[0527] 1. Location information management

[0528] The server manages the real-time positioning of drones that provide dining spaces. Using high-precision positioning technology, it adjusts the drones to navigate safely and efficiently and reach the designated area.

[0529] 2. Device Control

[0530] The server transmits signals to control the drone's flight path and maintain optimal flight conditions to provide a safe and comfortable dining experience.

[0531] 3. Reservation Management

[0532] Users make reservations using a dedicated app, and the server receives this information and records it in a database. Based on the reservation status, the system adjusts the availability of drones and seats to provide the optimal schedule.

[0533] 4. Monitoring

[0534] The server monitors the safety of users and equipment through sensors mounted on each drone. In the event of an anomaly, it quickly notifies staff and takes necessary measures.

[0535] 5. Emotion recognition

[0536] The emotion engine analyzes data such as voice, facial expressions, and gestures acquired from the user to determine their emotional state in real time. Based on the determined emotion, the server adjusts music, lighting, service content, and other elements to enhance the user's comfort.

[0537] Specific example

[0538] If a user desires a romantic aerial dinner at sunset on a clear day, they can book the service. During the flight, the emotion engine detects the user's smile and relaxed posture, and the server adjusts the music and lighting to warmer tones. Conversely, if tension or anxiety is detected, the server works with staff to take swift action to improve the situation.

[0539] This invention provides a service that combines advanced emotion recognition, enabling it to maximize user satisfaction. This approach delivers a customized experience tailored to each individual user, differentiating it from other services.

[0540] The following describes the processing flow.

[0541] Step 1:

[0542] The user launches the app on their device, enters their authentication information on the login screen, and logs in. The device sends the entered information to the server, which authenticates it and displays the dashboard.

[0543] Step 2:

[0544] The user selects a reservation menu on the dashboard. They enter their desired date, time, and meal menu into their device and send the reservation information to the server. The server records the received reservation information in its database.

[0545] Step 3:

[0546] The server checks drone availability based on reservation information and determines whether a reservation is possible. If available, the server sends a reservation notification to the terminal, and the user confirms the reservation.

[0547] Step 4:

[0548] After the reservation is confirmed, the server will determine the feasibility of flight based on the weather information for the day. If the weather is good, it will set the drone flight schedule.

[0549] Step 5:

[0550] On the day of departure, the user arrives at the designated departure point. The terminal sends boarding confirmation information to the server, and once boarding is confirmed, the server instructs the drone to begin flight.

[0551] Step 6:

[0552] The emotion engine is mounted on the drone and collects the user's facial expressions and voice data in real time. This data is used to determine the user's emotions and is sent to a server.

[0553] Step 7:

[0554] The server analyzes emotional data and dynamically adjusts music and environmental settings according to the user's emotional state. For example, if relaxation is detected, it selects soothing music and adjusts the environment accordingly.

[0555] Step 8:

[0556] After the experience ends, the drone returns to its starting point and lands. The server sends a notification to the device that the experience has ended and requests feedback from the user through a survey. The user enters their feedback, and the device sends it to the server.

[0557] This entire process allows the system to provide a unique aerial experience tailored to each individual user, thereby improving user satisfaction.

[0558] (Example 2)

[0559] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0560] In the modern era, there is a demand for the effective use of space and the maximization of individual user experiences. In particular, in aerial dining experiences, ensuring safety while optimizing the experience based on user emotions is crucial. However, conventional systems have struggled to simultaneously meet these requirements. Therefore, the present invention aims to provide a new method for making dining experiences in unused spaces safer and more personalized.

[0561] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0562] In this invention, the server includes location information management means for managing the dining experience provided in unused space, control means for safely and stably controlling the target equipment, reservation means for managing reservations made by users, monitoring means for aggregating and analyzing user safety information via multiple measuring devices to ensure safety, and emotion analysis means for identifying the emotional state of users and optimizing the service. This makes it possible to provide a customized experience tailored to each individual user and maximize their satisfaction.

[0563] "Unused space" refers to areas that are not being utilized for their traditional purposes and are places that can be used for new services or activities.

[0564] "Managing the dining experience" refers to the overall operation and coordination of the dining services provided to customers, and includes processes such as reservation management, space control, and safety assurance.

[0565] "Location information management means" refers to a technical method or system for determining the precise location of devices and users within a space and adjusting their location as needed.

[0566] "Control means" refers to technologies or mechanisms for managing and adjusting the operation of equipment or systems in order to achieve safe and stable operation.

[0567] A "reservation method" refers to a method or system for users to apply for a service in advance and manage the available dates, times, and conditions.

[0568] "Monitoring measures" refer to technologies or processes used to check the situation in real time and detect anomalies in order to ensure the safety of equipment and users.

[0569] "Emotion analysis means" refers to a technology or mechanism for identifying emotions from a user's voice, facial expressions, gestures, etc., and adjusting services based on the results.

[0570] This invention relates to a system for managing and providing dining experiences in underutilized spaces. Specific embodiments for carrying out this invention are described below.

[0571] First, the server uses location management systems to track the position of aerial devices such as drones in real time. The server uses GPS and other high-precision location technologies to determine the device's position and enable precise navigation.

[0572] Next, the server manages the device's movement through control mechanisms. The server uses a flight control system to adjust the device's trajectory and speed, ensuring a safe and comfortable dining experience. The server also dynamically optimizes the device's operating conditions according to weather and aerial conditions.

[0573] Users can make reservations for dining experiences using a dedicated application on their devices. As a reservation method, the server receives reservation information and stores it in a database, effectively managing available resources and providing the optimal schedule.

[0574] Furthermore, each drone is equipped with multiple sensors, and the server aggregates the data obtained from these sensors to ensure safety through monitoring. If an anomaly is detected, the server immediately notifies the staff and takes the necessary countermeasures.

[0575] Regarding emotion analysis, emotion analysis tools are used to analyze the user's voice, facial expressions, and gestures in real time. Based on the results of the emotion analysis, the server adjusts music, lighting, and other service elements to provide a personalized and comfortable experience.

[0576] For example, if a user desires a romantic dinner at sunset on a sunny day, they can book through a dedicated app, and the experience will be tailored to their preferences. If the emotion analysis system detects a smile from the passenger, the server will adjust the lighting to a warmer tone and play appropriate music. In this way, the experience is optimized according to the user's emotions.

[0577] An example of a prompt using a generative AI model is: "Design a system that adjusts music and lighting based on the user's emotions during an aerial dinner experience. How will the emotion data be acquired and analyzed?"

[0578] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0579] Step 1:

[0580] Users make reservations using a dedicated application via their device. The information entered includes the desired date and time, the type of experience, and the number of participants. The device sends this information to a server, which records the received reservation information in a database. This updates the reservation list and optimizes the available resources.

[0581] Step 2:

[0582] The server obtains the drone's location information from GPS using a location information management system. The input is the current location of each drone, and the server processes this location information to calculate the drone's real-time flight path. As output, a safe flight route is generated and sent to the drone. This allows the drone to smoothly reach the designated area.

[0583] Step 3:

[0584] The server controls the drone's equipment via control devices. Inputs include the drone's flight conditions and weather data. The server analyzes this data, generates output such as motor speed and altitude adjustments, and transmits them to the drone. This process ensures safe drone flight and a comfortable user experience.

[0585] Step 4:

[0586] The server aggregates data from sensors mounted on the drone as a monitoring tool to ensure safety. Sensor data, including acceleration, temperature, and vibration, is used as input. The server analyzes this data and, if an anomaly is detected, generates a warning and notifies staff. This enables a rapid response and ensures the safety of users.

[0587] Step 5:

[0588] The server uses emotion analysis tools to analyze the user's emotional data in real time. User voice, facial expressions, and gestures are used as input. This data is analyzed using a generative AI model, and the user's emotional state is generated as output. Based on the determined emotion, the server outputs instructions to adjust lighting, music, and service content, and sends them to the device. This improves user comfort and optimizes the individual experience.

[0589] (Application Example 2)

[0590] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0591] When providing experiences using untapped spaces, it is essential to recognize users' emotions in real time and optimize the experience based on those emotions. This is necessary to provide personalized experiences that maximize user satisfaction and differentiate the service from others.

[0592] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0593] In this invention, the server includes location information management means for managing the user experience provided in unused space, control means for safely and stably controlling the target device, and emotion recognition means for analyzing emotion data acquired from the user and dynamically adjusting the experience content. This enables dynamic experience customization in accordance with the user's emotions.

[0594] "Unused space" refers to specific areas or locations that are not used for their usual purposes, and is a space that is utilized to provide new forms of user experiences.

[0595] "Location information management means" refers to technical means for managing and controlling the location of equipment and devices so that the experiences and services provided are carried out in the appropriate locations.

[0596] "Control means" refers to technical means that monitor the operation of a target device and make adjustments or give instructions as needed in order to ensure safe and stable operation.

[0597] A "reservation method" refers to a technical means that allows users to reserve or register for a service at a specific time and place in advance.

[0598] "Monitoring measures" are technical means that constitute part of a system for collecting and analyzing various types of information in order to ensure the safety of users and equipment.

[0599] "Emotion recognition means" are technical methods for analyzing a user's emotions and optimizing the services and experiences provided to match the user's current emotional state.

[0600] "Emotional data" refers to information that indicates the user's emotional state, and includes data obtained from voice, facial expressions, gestures, etc.

[0601] This invention is a system that provides a user experience in unused spaces and optimizes the experience through emotion recognition. Its components include location information management means, control means, reservation means, monitoring means, and emotion recognition means.

[0602] The server controls drones and other flying devices to provide experiences in untapped spaces, and uses location management means to deliver services safely and appropriately. This involves the use of GPS and other high-precision location technologies.

[0603] Users make reservations for experiences using their smartphones, and this information is sent to the server via the reservation system. The server records the reservation information in a database and creates an appropriate experience schedule.

[0604] The monitoring system ensures safety by collecting data in real time through sensors built into the device. If an anomaly is detected, an alert is issued quickly.

[0605] The emotion recognition system analyzes emotional data (voice, facial expressions, gestures, etc.) acquired from the user, and the server dynamically adjusts music, lighting, and other experience elements. This allows the user to receive an optimal experience tailored to their emotions at that time.

[0606] For example, if a user is seeking a relaxing environment, music and lighting that enhance relaxation will be selected based on emotional data. An example of a related prompt would be, "If the user desires a relaxing environment and this state is detected, suggest appropriate music and beverages."

[0607] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0608] Step 1:

[0609] Users book aerial experiences using their smartphones. The booking information (date, time, location, and desired experience) entered via the device is sent to the server. The server receives this information and records it in its database. This creates the user's booking schedule.

[0610] Step 2:

[0611] The server manages the drone's location based on reservation information. The server processes GPS data and calculates the optimal flight route. The drone moves according to instructions from the server to reach the designated location. This ensures that the defined experience space is maintained.

[0612] Step 3:

[0613] Various sensors mounted on the drone collect environmental and safety data in real time. This data is sent to a server, which analyzes it and monitors for any anomalies. If an anomaly is detected, an alert is immediately generated, enabling a swift response.

[0614] Step 4:

[0615] The server uses emotion recognition to receive voice, facial, and gesture data from the user. The server then uses a generative AI model to analyze this input data and determine the user's emotional state. For example, it can assess the user's stress level based on changes in voice tone and facial expressions.

[0616] Step 5:

[0617] Based on the user's emotional state, the server adjusts the music and lighting settings. The server recommends optimal settings using prompts, and the environmental elements within the drone are dynamically changed according to these instructions. This allows the user to experience something that matches their current emotions.

[0618] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0619] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0620] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0621] [Fourth Embodiment]

[0622] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0623] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0624] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0625] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0626] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0627] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0628] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0629] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0630] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0631] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0632] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0633] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0634] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0635] This invention is implemented as a system for providing a new tourism experience utilizing the air. Specific embodiments of each element are described below.

[0636] This system allows users to book aerial restaurants through a dedicated application and provides integrated services including location information management, device control, reservation management, and monitoring.

[0637] 1. Location information management

[0638] The server manages the drone's precise location information and sets the route from the departure point to the destination. It monitors the location in real time and constantly ensures safety during flight. Predictive algorithms are used to calculate the optimal flight route based on weather conditions and traffic conditions.

[0639] 2. Device Control

[0640] The server sends control signals to the drone instructing it to fly steadily. These control signals include altitude, speed, and route changes. This allows the drone to safely navigate its target path.

[0641] 3. Reservation Management

[0642] The user accesses the reservation screen using their device and selects their desired date, time, and menu. The server receives the reservation information and registers it in the database. Based on this, it automatically adjusts the availability of drones and seats and sends a reservation confirmation notification to the user's device.

[0643] 4. Monitoring

[0644] The server monitors the safety and comfort of users while they are on board through various sensors mounted on the drone. It monitors seat movement, air pressure, temperature, etc., and instantly issues an alert if any abnormality occurs. To ensure user safety, it coordinates with ground staff to enable a rapid response.

[0645] Specific example

[0646] If a user wishes to make a Sunday lunch reservation, they open the reservation screen in the dedicated app. After selecting their desired menu and entering their preferred time, the device sends this information to the server. The server checks the drone's availability and flight route, and confirms the reservation. On the day of the reservation, the user gathers at the designated departure point and boards the drone. The server monitors the flight in real time, ensuring a safe dining experience.

[0647] Thus, the present invention allows users to enjoy an unparalleled aerial sightseeing experience and effectively alleviates congestion on the ground.

[0648] The following describes the processing flow.

[0649] Step 1:

[0650] The user launches the app on their device and logs in by entering their registered email address and password on the login screen. The device sends this information to the server, which verifies it against the information in the database. If authentication is successful, the server displays the user's dashboard on the device.

[0651] Step 2:

[0652] The user selects a reservation option from the dashboard and enters their desired date, time, and meal menu. The terminal sends the selected reservation information to the server. The server checks the availability of drones and seats in its database and determines if a reservation is possible.

[0653] Step 3:

[0654] If the server determines that a reservation is available, it prompts the user to confirm the reservation. The user confirms the reservation on their device and presses the approve button. The device then sends the approved reservation information back to the server. The server confirms the reservation and sends a reservation completion notification to the device.

[0655] Step 4:

[0656] On the day of the reservation, the server retrieves real-time weather data to confirm flight safety. If the weather is good, preparations for drone takeoff begin. The server sends the flight path and takeoff instructions to the drone.

[0657] Step 5:

[0658] Once the user arrives at the designated departure point, they use a terminal to confirm their boarding. The terminal sends boarding information to the server, and once boarding is confirmed, the server instructs the drone to depart.

[0659] Step 6:

[0660] During flight, the server receives data from the drone's sensors and monitors user safety in real time. If an anomaly is detected, the server issues an alert and communicates the situation to ground staff.

[0661] Step 7:

[0662] When the user finishes their meal and the scheduled time arrives, the server notifies the drone of the return route. Once the drone safely lands at the starting point, the server sends a notification to the terminal that the experience has ended.

[0663] Step 8:

[0664] After the experience ends, the server sends a feedback questionnaire to the user's device. The user enters their evaluation of the experience, and the device sends this back to the server. The server stores the feedback in a database and uses it to improve the service.

[0665] (Example 1)

[0666] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0667] When providing dining experiences that utilize unused spaces, it is necessary to ensure the safety and comfort of users while simultaneously managing reservations efficiently and setting up optimized travel routes. However, conventional technologies have found it difficult to satisfy these requirements at the same time. This invention aims to solve these problems and provide users with a new aerial dining experience.

[0668] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0669] In this invention, the server includes location information management means for managing dining experiences provided in unused spaces, control means for stable control of target devices, and reservation means for accepting user reservations. This enables users to safely and efficiently enjoy new tourism experiences.

[0670] A "location information management system" is a system for determining the location of a target device and setting and managing the optimal movement route in order to provide a dining experience in an unused space.

[0671] A "control means" is a system that has the function of generating and transmitting control signals necessary to operate the target device safely and stably.

[0672] A "reservation system" is a system that has the function of recording and managing information when users reserve services or experiences in advance.

[0673] A "monitoring system" is a system that collects various types of information in real time and has the necessary functions to ensure user safety and the normal operation of equipment.

[0674] An "input method" is an interface that allows users to input information regarding travel and dining experience reservations via a terminal and send it to the server.

[0675] A "flight planning system" is a system that uses a predictive algorithm to formulate a plan for the target device to travel along the optimal path.

[0676] To implement the invention, the server constitutes a system with diverse functions. The server uses location information management means to precisely manage location information for providing a dining experience through unused airspace, and sets the route from the drone's departure point to its destination. The server uses a prediction algorithm to analyze weather conditions and traffic conditions and calculate the optimal flight route. Specifically, it uses a weather API to obtain the latest data and reflects it in the flight route in real time.

[0677] Simultaneously, the server uses control mechanisms to generate control signals necessary to maintain stable flight for the drone, sending instructions including altitude and speed adjustments and route changes. This allows the drone to navigate the target path safely and efficiently. This process ensures user safety while providing an exciting aerial dining experience.

[0678] The reservation system provides users with access to the reservation screen for the sky restaurant using their devices. Users select their desired date, time, and menu on the screen and send the reservation information from their device to the server. The server processes the reservation information in real time and registers it in the database. This process automatically adjusts the reservation status, and a reservation confirmation notification is sent to the device within seconds.

[0679] Furthermore, the server uses monitoring devices to collect data in real time from various sensors mounted on the drone, maintaining user safety and comfort. The data obtained from each measuring instrument is also shared with ground staff, and any abnormalities are quickly notified.

[0680] For example, if a user wants to make a weekend lunch reservation, they would use a specific mobile application to select the menu and date / time. The server would then check drone availability and flight route planning in real time and confirm the reservation. After that, the server would make any necessary adjustments to the environment during the flight.

[0681] An example of a prompt to input into the generating AI model is, "Please describe in detail each function of the system to maximize the enjoyment of the aerial dining experience." The intention is that this will convey the overall picture of the invention to the user and lead to a deeper understanding.

[0682] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0683] Step 1:

[0684] The user activates the terminal and accesses the reservation application. The user enters their desired date and time and menu selection, and the terminal sends this information to the server. The entered data is then provided to the server as the reservation details.

[0685] Step 2:

[0686] The server analyzes the reservation information received from the terminal. Based on the input information, the server registers the reservation in the database. In this process, the server also checks the current availability and schedule of drones to determine if it is possible to accommodate the request. As a result, a status indicating whether or not the reservation can be made is output.

[0687] Step 3:

[0688] The server develops a flight plan once the booking is approved. The server retrieves the latest weather data from a weather API and uses a forecasting algorithm to calculate the optimal flight route. The inputs are current weather conditions and departure and arrival points, while the output is a detailed flight schedule to instruct the drone.

[0689] Step 4:

[0690] After the server completes the booking process and flight planning, it sends a booking confirmation to the terminal. The terminal receives the confirmation information from the server and displays it to the user. The displayed information includes booking details such as the departure point and time, and the selected menu.

[0691] Step 5:

[0692] Users gather at the departure point at the designated date and time and perform a final check-in using a terminal. The terminal sends the check-in information to the server for final confirmation of the reservation. In this step, the check-in information is input, and the check-in status, which is compiled by the server, is output.

[0693] Step 6:

[0694] The server collects and monitors real-time data from sensors mounted on the drone. Information such as temperature, air pressure, and seat movement is used as input, and the server analyzes this data to detect any abnormalities. The output is either a continuous operation command if everything is normal, or an alert if an abnormality is detected.

[0695] (Application Example 1)

[0696] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0697] In recent years, there has been growing interest in providing new experiences that utilize untapped spaces. However, experiences, especially those taking place in the air, often lack sufficient safety and real-time management, and may not be able to effectively notify users of their delivery. Furthermore, various challenges exist, such as the increasing difficulty of optimizing travel routes and aggregating and analyzing safety information using multiple measuring instruments, depending on the scale of the project.

[0698] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0699] In this invention, the server includes location information management means for managing the dining experience provided in unused space, control means for safely and stably delivering food to an aerial transport device, reservation means for managing reservations made by users, monitoring means for collecting various information in real time and ensuring safety, and delivery completion notification means for sending notifications to user terminals. This enables the safe and comfortable provision of a new aerial experience to users, while simultaneously improving the quality of the experience through efficient notifications and route optimization.

[0700] "Unused space" refers to space that does not serve its intended purpose through conventional use, or is simply not being used.

[0701] "Location information management means for managing the dining experience" refers to technical means used to determine the precise location of the dining space and set the optimal travel route.

[0702] An "aerial transport device" refers to a device for moving goods or services through the air, and in this invention, it specifically refers to a device for delivering food.

[0703] "Control means" refers to technical means that provide signals or instructions to ensure the stable and safe operation of equipment or machinery.

[0704] "Reservation management methods" refer to methods and systems for receiving and managing users' reservation information.

[0705] "Monitoring measures" refer to technical means used to ensure security by collecting various types of information in real time and analyzing the data.

[0706] A "delivery completion notification system" is a system that has the function of informing the user that the delivery of goods has been completed.

[0707] This system is designed to provide a safe and efficient aerial experience utilizing untapped space. The server manages location information and controls aerial transport devices to oversee the dining experience. Specifically, it uses GPS data and weather information to calculate the optimal route and sends control signals to aerial transport devices such as drones. A prediction algorithm using Python is implemented in this process.

[0708] The user's device functions as a reservation tool, providing an interface for selecting the desired date, time, and menu. Reservation information is stored in the cloud and managed in real-time in conjunction with drone availability. This part is implemented using a mobile application built with React Native and Flutter.

[0709] To ensure user safety, the server uses monitoring tools to analyze information from various sensors mounted on the drone. This includes data from temperature, barometric pressure, and acceleration sensors, which are processed through software that enhances safety.

[0710] For example, if a family planning a picnic in a park uses the app to order food, the server will fly a drone along the optimal route and safely deliver the food to the user's designated pickup area. The entire process is seamless, allowing users to enjoy a new experience with peace of mind.

[0711] An example of a prompt to input into the generating AI model is: "Please describe the user experience of an aerial delivery system app. Specifically, please explain the steps involved in placing an order and how the drone delivers the food."

[0712] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0713] Step 1:

[0714] The terminal accepts reservations for meals from the user. When the user selects the date, time, and menu through the app interface, that information is sent from the terminal to the cloud server. The input is the user's selection information, and the output is the reservation data stored in the cloud.

[0715] Step 2:

[0716] The server checks drone availability and flight zones based on the received reservation data. Specifically, it retrieves reservation information from a database and uses Python to determine the optimal drone and flight route. The input is reservation data, and the output is the drone selection result.

[0717] Step 3:

[0718] The server collects weather and GPS data in real time and instructs the drone on a safe flight path. This involves using an algorithm to calculate the optimal path based on input data from sensors and transmitting it to the drone as a control signal. The input is sensor and position data, and the output is the control signal.

[0719] Step 4:

[0720] The server sends a notification to the user's device to confirm the reservation and inform them of the scheduled delivery time. The notification includes a reservation confirmation message and is displayed on the device's user interface as a status check for the user. The input is the drone's flight plan, and the output is the notification message to the user.

[0721] Step 5:

[0722] Once the drone takes off, the server monitors its location and status in real time. The server periodically collects data from the sensors to check for any abnormalities. The input is the drone's sensor data, and the output is the monitoring information.

[0723] Step 6:

[0724] After safe delivery by drone is complete, the server sends a delivery completion notification to the terminal. This informs the user that their food has arrived, and a delivery completion message is displayed on the terminal. The input is the delivery completion status, and the output is the completion notification to the user.

[0725] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0726] This invention is a system that recognizes the user's emotions in real time during an aerial dining experience and optimizes the experience based on those emotions. Specific embodiments for carrying out the invention are described below.

[0727] In addition to location information management, device control, reservation management, and monitoring, this system incorporates an emotion engine that recognizes user emotions, thereby further improving the user experience.

[0728] 1. Location information management

[0729] The server manages the real-time positioning of drones that provide dining spaces. Using high-precision positioning technology, it adjusts the drones to navigate safely and efficiently and reach the designated area.

[0730] 2. Device Control

[0731] The server transmits signals to control the drone's flight path and maintain optimal flight conditions to provide a safe and comfortable dining experience.

[0732] 3. Reservation Management

[0733] Users make reservations using a dedicated app, and the server receives this information and records it in a database. Based on the reservation status, the system adjusts the availability of drones and seats to provide the optimal schedule.

[0734] 4. Monitoring

[0735] The server monitors the safety of users and equipment through sensors mounted on each drone. In the event of an anomaly, it quickly notifies staff and takes necessary measures.

[0736] 5. Emotion recognition

[0737] The emotion engine analyzes data such as voice, facial expressions, and gestures acquired from the user to determine their emotional state in real time. Based on the determined emotion, the server adjusts music, lighting, service content, and other elements to enhance the user's comfort.

[0738] Specific example

[0739] If a user desires a romantic aerial dinner at sunset on a clear day, they can book the service. During the flight, the emotion engine detects the user's smile and relaxed posture, and the server adjusts the music and lighting to warmer tones. Conversely, if tension or anxiety is detected, the server works with staff to take swift action to improve the situation.

[0740] This invention provides a service that combines advanced emotion recognition, enabling it to maximize user satisfaction. This approach delivers a customized experience tailored to each individual user, differentiating it from other services.

[0741] The following describes the processing flow.

[0742] Step 1:

[0743] The user launches the app on their device, enters their authentication information on the login screen, and logs in. The device sends the entered information to the server, which authenticates it and displays the dashboard.

[0744] Step 2:

[0745] The user selects a reservation menu on the dashboard. They enter their desired date, time, and meal menu into their device and send the reservation information to the server. The server records the received reservation information in its database.

[0746] Step 3:

[0747] The server checks drone availability based on reservation information and determines whether a reservation is possible. If available, the server sends a reservation notification to the terminal, and the user confirms the reservation.

[0748] Step 4:

[0749] After the reservation is confirmed, the server will determine the feasibility of flight based on the weather information for the day. If the weather is good, it will set the drone flight schedule.

[0750] Step 5:

[0751] On the day of departure, the user arrives at the designated departure point. The terminal sends boarding confirmation information to the server, and once boarding is confirmed, the server instructs the drone to begin flight.

[0752] Step 6:

[0753] The emotion engine is mounted on the drone and collects the user's facial expressions and voice data in real time. This data is used to determine the user's emotions and is sent to a server.

[0754] Step 7:

[0755] The server analyzes emotional data and dynamically adjusts music and environmental settings according to the user's emotional state. For example, if relaxation is detected, it selects soothing music and adjusts the environment accordingly.

[0756] Step 8:

[0757] After the experience ends, the drone returns to its starting point and lands. The server sends a notification to the device that the experience has ended and requests feedback from the user through a survey. The user enters their feedback, and the device sends it to the server.

[0758] This entire process allows the system to provide a unique aerial experience tailored to each individual user, thereby improving user satisfaction.

[0759] (Example 2)

[0760] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0761] In the modern era, there is a demand for the effective use of space and the maximization of individual user experiences. In particular, in aerial dining experiences, ensuring safety while optimizing the experience based on user emotions is crucial. However, conventional systems have struggled to simultaneously meet these requirements. Therefore, the present invention aims to provide a new method for making dining experiences in unused spaces safer and more personalized.

[0762] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0763] In this invention, the server includes location information management means for managing the dining experience provided in unused space, control means for safely and stably controlling the target equipment, reservation means for managing reservations made by users, monitoring means for aggregating and analyzing user safety information via multiple measuring devices to ensure safety, and emotion analysis means for identifying the emotional state of users and optimizing the service. This makes it possible to provide a customized experience tailored to each individual user and maximize their satisfaction.

[0764] "Unused space" refers to areas that are not being utilized for their traditional purposes and are places that can be used for new services or activities.

[0765] "Managing the dining experience" refers to the overall operation and coordination of the dining services provided to customers, and includes processes such as reservation management, space control, and safety assurance.

[0766] "Location information management means" refers to a technical method or system for determining the precise location of devices and users within a space and adjusting their location as needed.

[0767] "Control means" refers to technologies or mechanisms for managing and adjusting the operation of equipment or systems in order to achieve safe and stable operation.

[0768] A "reservation method" refers to a method or system for users to apply for a service in advance and manage the available dates, times, and conditions.

[0769] "Monitoring measures" refer to technologies or processes used to check the situation in real time and detect anomalies in order to ensure the safety of equipment and users.

[0770] "Emotion analysis means" refers to a technology or mechanism for identifying emotions from a user's voice, facial expressions, gestures, etc., and adjusting services based on the results.

[0771] This invention relates to a system for managing and providing dining experiences in underutilized spaces. Specific embodiments for carrying out this invention are described below.

[0772] First, the server uses location management systems to track the position of aerial devices such as drones in real time. The server uses GPS and other high-precision location technologies to determine the device's position and enable precise navigation.

[0773] Next, the server manages the device's movement through control mechanisms. The server uses a flight control system to adjust the device's trajectory and speed, ensuring a safe and comfortable dining experience. The server also dynamically optimizes the device's operating conditions according to weather and aerial conditions.

[0774] Users can make reservations for dining experiences using a dedicated application on their devices. As a reservation method, the server receives reservation information and stores it in a database, effectively managing available resources and providing the optimal schedule.

[0775] Furthermore, each drone is equipped with multiple sensors, and the server aggregates the data obtained from these sensors to ensure safety through monitoring. If an anomaly is detected, the server immediately notifies the staff and takes the necessary countermeasures.

[0776] Regarding emotion analysis, emotion analysis tools are used to analyze the user's voice, facial expressions, and gestures in real time. Based on the results of the emotion analysis, the server adjusts music, lighting, and other service elements to provide a personalized and comfortable experience.

[0777] For example, if a user desires a romantic dinner at sunset on a sunny day, they can book through a dedicated app, and the experience will be tailored to their preferences. If the emotion analysis system detects a smile from the passenger, the server will adjust the lighting to a warmer tone and play appropriate music. In this way, the experience is optimized according to the user's emotions.

[0778] An example of a prompt using a generative AI model is: "Design a system that adjusts music and lighting based on the user's emotions during an aerial dinner experience. How will the emotion data be acquired and analyzed?"

[0779] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0780] Step 1:

[0781] Users make reservations using a dedicated application via their device. The information entered includes the desired date and time, the type of experience, and the number of participants. The device sends this information to a server, which records the received reservation information in a database. This updates the reservation list and optimizes the available resources.

[0782] Step 2:

[0783] The server obtains the drone's location information from GPS using a location information management system. The input is the current location of each drone, and the server processes this location information to calculate the drone's real-time flight path. As output, a safe flight route is generated and sent to the drone. This allows the drone to smoothly reach the designated area.

[0784] Step 3:

[0785] The server controls the drone's equipment via control devices. Inputs include the drone's flight conditions and weather data. The server analyzes this data, generates output such as motor speed and altitude adjustments, and transmits them to the drone. This process ensures safe drone flight and a comfortable user experience.

[0786] Step 4:

[0787] The server aggregates data from sensors mounted on the drone as a monitoring tool to ensure safety. Sensor data, including acceleration, temperature, and vibration, is used as input. The server analyzes this data and, if an anomaly is detected, generates a warning and notifies staff. This enables a rapid response and ensures the safety of users.

[0788] Step 5:

[0789] The server uses emotion analysis tools to analyze the user's emotional data in real time. User voice, facial expressions, and gestures are used as input. This data is analyzed using a generative AI model, and the user's emotional state is generated as output. Based on the determined emotion, the server outputs instructions to adjust lighting, music, and service content, and sends them to the device. This improves user comfort and optimizes the individual experience.

[0790] (Application Example 2)

[0791] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0792] When providing experiences using untapped spaces, it is essential to recognize users' emotions in real time and optimize the experience based on those emotions. This is necessary to provide personalized experiences that maximize user satisfaction and differentiate the service from others.

[0793] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0794] In this invention, the server includes location information management means for managing the user experience provided in unused space, control means for safely and stably controlling the target device, and emotion recognition means for analyzing emotion data acquired from the user and dynamically adjusting the experience content. This enables dynamic experience customization in accordance with the user's emotions.

[0795] "Unused space" refers to specific areas or locations that are not used for their usual purposes, and is a space that is utilized to provide new forms of user experiences.

[0796] "Location information management means" refers to technical means for managing and controlling the location of equipment and devices so that the experiences and services provided are carried out in the appropriate locations.

[0797] "Control means" refers to technical means that monitor the operation of a target device and make adjustments or give instructions as needed in order to ensure safe and stable operation.

[0798] A "reservation method" refers to a technical means that allows users to reserve or register for a service at a specific time and place in advance.

[0799] "Monitoring measures" are technical means that constitute part of a system for collecting and analyzing various types of information in order to ensure the safety of users and equipment.

[0800] "Emotion recognition means" are technical methods for analyzing a user's emotions and optimizing the services and experiences provided to match the user's current emotional state.

[0801] "Emotional data" refers to information that indicates the user's emotional state, and includes data obtained from voice, facial expressions, gestures, etc.

[0802] This invention is a system that provides a user experience in unused spaces and optimizes the experience through emotion recognition. Its components include location information management means, control means, reservation means, monitoring means, and emotion recognition means.

[0803] The server controls drones and other flying devices to provide experiences in untapped spaces, and uses location management means to deliver services safely and appropriately. This involves the use of GPS and other high-precision location technologies.

[0804] Users make reservations for experiences using their smartphones, and this information is sent to the server via the reservation system. The server records the reservation information in a database and creates an appropriate experience schedule.

[0805] The monitoring system ensures safety by collecting data in real time through sensors built into the device. If an anomaly is detected, an alert is issued quickly.

[0806] The emotion recognition system analyzes emotional data (voice, facial expressions, gestures, etc.) acquired from the user, and the server dynamically adjusts music, lighting, and other experience elements. This allows the user to receive an optimal experience tailored to their emotions at that time.

[0807] For example, if a user is seeking a relaxing environment, music and lighting that enhance relaxation will be selected based on emotional data. An example of a related prompt would be, "If the user desires a relaxing environment and this state is detected, suggest appropriate music and beverages."

[0808] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0809] Step 1:

[0810] Users book aerial experiences using their smartphones. The booking information (date, time, location, and desired experience) entered via the device is sent to the server. The server receives this information and records it in its database. This creates the user's booking schedule.

[0811] Step 2:

[0812] The server manages the drone's location based on reservation information. The server processes GPS data and calculates the optimal flight route. The drone moves according to instructions from the server to reach the designated location. This ensures that the defined experience space is maintained.

[0813] Step 3:

[0814] Various sensors mounted on the drone collect environmental and safety data in real time. This data is sent to a server, which analyzes it and monitors for any anomalies. If an anomaly is detected, an alert is immediately generated, enabling a swift response.

[0815] Step 4:

[0816] The server uses emotion recognition to receive voice, facial, and gesture data from the user. The server then uses a generative AI model to analyze this input data and determine the user's emotional state. For example, it can assess the user's stress level based on changes in voice tone and facial expressions.

[0817] Step 5:

[0818] Based on the user's emotional state, the server adjusts the music and lighting settings. The server recommends optimal settings using prompts, and the environmental elements within the drone are dynamically changed according to these instructions. This allows the user to experience something that matches their current emotions.

[0819] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0820] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0821] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0822] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0823] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0824] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0825] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0826] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0827] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0828] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0829] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0830] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0831] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0832] 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.

[0833] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0834] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0835] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0836] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0837] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0838] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0839] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0840] The following is further disclosed regarding the embodiments described above.

[0841] (Claim 1)

[0842] A location information management system for managing dining experiences provided in unused spaces,

[0843] A control means for safely and stably controlling the target device,

[0844] A reservation method that allows users to manage their reservations,

[0845] A monitoring system to collect various types of information in real time and ensure safety,

[0846] A system that includes this.

[0847] (Claim 2)

[0848] The system according to claim 1, wherein the location information management means includes an algorithm for optimizing the movement path of the provided space.

[0849] (Claim 3)

[0850] The system according to claim 1, wherein the monitoring means aggregates and analyzes user safety information via a plurality of measuring instruments.

[0851] "Example 1"

[0852] (Claim 1)

[0853] A location information management system for managing dining experiences provided in unused spaces,

[0854] A control means for safely and stably controlling the target device,

[0855] A reservation method that allows users to manage their reservations,

[0856] A monitoring system to collect various types of information in real time and ensure safety,

[0857] An input method for users to make reservations for transportation via a terminal,

[0858] A flight planning means that optimizes the flight path using a predictive algorithm on a server,

[0859] A system that includes this.

[0860] (Claim 2)

[0861] The system according to claim 1, wherein the location information management means updates route information in real time using an algorithm that optimizes the movement route of the provided space.

[0862] (Claim 3)

[0863] The system according to claim 1, wherein the monitoring means adjusts the control signal based on environmental data collected via a plurality of measuring instruments.

[0864] "Application Example 1"

[0865] (Claim 1)

[0866] A location information management system for managing dining experiences provided in unused spaces,

[0867] A control means for safely and stably providing food to an aerial conveying device,

[0868] A reservation method that allows users to manage their reservations,

[0869] A monitoring system to collect various types of information in real time and ensure safety,

[0870] A delivery completion notification method that sends a notification to the user's terminal,

[0871] A system that includes this.

[0872] (Claim 2)

[0873] The system according to claim 1, wherein the position information management means includes an algorithm for optimizing the movement path of aerial transport.

[0874] (Claim 3)

[0875] The system according to claim 1, wherein the monitoring means aggregates and analyzes user safety information via multiple measuring instruments and enables notification on the user terminal.

[0876] "Example 2 of combining an emotion engine"

[0877] (Claim 1)

[0878] A location information management system for managing dining experiences provided in unused spaces,

[0879] A control means for safely and stably controlling the target equipment,

[0880] A reservation method for managing reservations made by users,

[0881] A monitoring system that aggregates and analyzes user safety information via multiple measuring instruments to ensure safety,

[0882] A means for analyzing emotions to identify the emotional state of users and optimize services,

[0883] A system that includes this.

[0884] (Claim 2)

[0885] The system according to claim 1, wherein the location information management means includes an algorithm for optimizing movement paths in a provided space and is adjusted to provide individualized user experiences.

[0886] (Claim 3)

[0887] The system according to claim 1, wherein the emotion analysis means is used to analyze voice data and visual gesture data and to adjust environmental conditions.

[0888] "Application example 2 when combining with an emotional engine"

[0889] (Claim 1)

[0890] A location information management system for managing the user experience provided in unused spaces,

[0891] A control means for safely and stably controlling the target device,

[0892] A reservation method that allows users to manage their reservations,

[0893] A monitoring system to collect various types of information in real time and ensure safety,

[0894] An emotion recognition method that analyzes emotional data obtained from users and dynamically adjusts the experience content,

[0895] A system that includes this.

[0896] (Claim 2)

[0897] The system according to claim 1, wherein the location information management means includes an algorithm for optimizing movement paths in the provided space, and further performs experience optimization based on emotional data.

[0898] (Claim 3)

[0899] The system according to claim 1, wherein the monitoring means aggregates and analyzes user safety information and emotional information via a plurality of measuring instruments. [Explanation of Symbols]

[0900] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A location information management system for managing dining experiences provided in unused spaces, A control means for safely and stably controlling the target device, A reservation method that allows users to manage their reservations, A monitoring system to collect various types of information in real time and ensure safety, A system that includes this.

2. The system according to claim 1, wherein the location information management means includes an algorithm for optimizing the movement path of the provided space.

3. The system according to claim 1, wherein the monitoring means aggregates and analyzes user safety information via a plurality of measuring instruments.

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