system

Abstract

We provide the system. [Solution] A means of receiving input from the user and using the information of the observation site to obtain light pollution and weather conditions from an external database, A means for calculating the optimal timing and direction for astronomical observation based on acquired observation conditions, A means of automatically generating and providing telescope operation tutorials and suggestions for photography techniques to beginner users, A means for distributing the generated observation plan and operation tutorial to the user terminal, A means of receiving user feedback and improving the system's analysis model, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When conducting astronomical observations, a lot of specialized knowledge and preparations are required, such as the selection of the observation site, understanding of light pollution and weather conditions, and determination of appropriate observation timing. Therefore, it is a high barrier especially for beginners. Also, experience is required in the operation of telescopes and photography techniques, which is the reason why many new users are frustrated in astronomical observations. It is necessary to solve this problem so that more people can enjoy astronomical observations.

Means for Solving the Problems

[0005] This invention provides a system for supporting observations using astronomical telescopes that accurately grasps the observation site, light pollution, and weather conditions based on user input, and automatically generates an optimal observation plan according to the target object. Furthermore, it supports the observation experience for beginners who are unfamiliar with operating telescopes by providing easy-to-understand operation tutorials and automatically suggesting photography techniques. In addition, it aims for continuous system improvement by collecting user feedback and using it to improve the analysis model. This provides an environment in which even beginners can easily perform advanced astronomical observations.

[0006] "User input" refers to the act of a user providing information about astronomical observations to the system, including the object of observation, desired date and time, and specifications of the equipment to be used.

[0007] "Observation site information" refers to data about the location where astronomical observations are conducted, including geographical location information and the level of light pollution in that area.

[0008] An "external database" is an external information source that the system can access, and it stores data such as light pollution, weather, and celestial body positions.

[0009] "Observation conditions" are factors that should be considered when conducting astronomical observations, and include weather conditions, light pollution, observation time, and observation location.

[0010] An "operation tutorial" is a set of explanatory materials that provides instructions and guidance for users to correctly use a telescope and observation plan.

[0011] "Suggestions for photographic techniques" refers to recommendations that provide users with suggested techniques and methods for observing and photographing celestial bodies.

[0012] "Feedback" refers to evaluations, suggestions for improvement, and opinions on observations provided by users after using a system.

[0013] An "analytical model" is a mathematical model used by a system to perform calculations and predictions based on astronomical observation conditions and user feedback. [Brief explanation of the drawing]

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

Embodiments for Carrying out the Invention

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

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

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

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

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

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

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

[0022] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0035] This invention is designed as a system to support astronomical observation and is equipped with various functions to improve user convenience. The following describes in detail how the system operates.

[0036] The first step for the user is to input information, including specifying the object to observe and setting the observation location. The user enters the desired celestial object (e.g., Saturn), desired observation date and time, and the specifications of the telescope to be used into the system. The terminal receives this information and sends it to the server.

[0037] Based on the information received from the user, the server uses the location information of the observation site to retrieve light pollution and weather conditions from an external database. This prepares the server to determine the optimal conditions for observation. For example, by referring to a light pollution map of the observation area and the current weather conditions, it can identify the time when visibility is as good as possible.

[0038] Next, the server analyzes the acquired observation conditions and consults an astronomical database for the target celestial object. This allows it to calculate the optimal timing and direction for observation and automatically generate an observation schedule. For example, when observing Saturn, it determines the time and direction when Saturn is highest in the sky and light pollution is minimal.

[0039] For beginner users, the server generates even more detailed operation tutorials. These include instructions on how to set up the telescope, points to be aware of during observation, how to track celestial objects, and camera setup procedures. This makes it easy for even beginners to prepare for astronomical observation.

[0040] The server then delivers the generated observation plan and accompanying operation tutorial to the terminal. The terminal displays the received information on its user interface. For example, it may show a visualized light pollution map, estimated celestial object positions over time, and detailed operation guides.

[0041] Users perform observations according to the provided observation plan and tutorial. After the observation, users can send feedback to the server. This feedback is reflected in the system's analysis model and used for future improvements. Specifically, this includes improving the tutorials provided based on user experience and improving the accuracy of the observation plan.

[0042] This system efficiently and effectively supports astronomical observation, making it possible for beginners in particular to enjoy observation without requiring a high level of expertise. With such preparation and support, users can easily conduct high-quality astronomical observations.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The user enters the celestial object they want to observe, their desired date and time, observation location, and the specifications of the telescope they will use into the terminal. The terminal receives this information and sends it to the server.

[0046] Step 2:

[0047] Based on the location information of the observation site received from the user, the server accesses an external database to obtain data on light pollution levels and weather conditions (temperature, humidity, weather, etc.).

[0048] Step 3:

[0049] The server uses the input data on the object to be observed to calculate the most suitable date, time, and direction for observation. In doing so, it refers to a database of celestial body positions to determine the appropriate time slot.

[0050] Step 4:

[0051] The server generates user tutorials for beginners, including instructions on setting up the telescope, selecting shooting modes, and tracking celestial objects.

[0052] Step 5:

[0053] The server sends the optimized observation plan and generated operation tutorial to the terminal.

[0054] Step 6:

[0055] The terminal displays the received observation plan and tutorial in its user interface, allowing the user to proceed with observation preparations.

[0056] Step 7:

[0057] Users conduct actual observations according to the provided information and send their results and impressions as feedback to the server via their device.

[0058] Step 8:

[0059] The server analyzes the feedback received from users and uses it to improve system performance and refine the next observation plan.

[0060] (Example 1)

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

[0062] For beginners conducting astronomical observations, analyzing observation conditions, determining the optimal timing, and operating observation equipment can be difficult, making efficient observation challenging. Furthermore, there is a need to incorporate observation experience into the system and provide observation guidance tailored to individual users. This means users can obtain a high-quality observation experience, while the system must be continuously improved using individual feedback.

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

[0064] This invention includes a server that receives information from the user and uses location information to acquire light environment and weather conditions from an external recording device; a server that calculates the optimal time and direction for astronomical observation based on the acquired environmental conditions; and a server that automatically generates and provides instructions for operating observation equipment and imaging techniques for beginners. This makes it easy for beginners to perform astronomical observations, and the system can be improved based on user feedback to provide more personalized instructions and plans.

[0065] A "user device" is a terminal used by a user to access a system and input information, and includes devices such as personal computers and smartphones.

[0066] A "server" is a computing device that receives information sent from users, acquires and analyzes optical environment and weather conditions, and generates and provides operational guidance and observation plans.

[0067] An "external recording device" refers to an external database or cloud service that provides data on the light environment and weather conditions necessary for astronomical observation.

[0068] "Light environment" refers to data indicating the level of light pollution at the observation site, and is an environmental condition that affects the clarity of visibility during nighttime observations.

[0069] "Meteorological conditions" refer to information about weather and atmospheric conditions during astronomical observations, and are factors that affect the accuracy of observations.

[0070] "Observation equipment" refers to instruments used to observe celestial bodies, including telescopes and cameras.

[0071] "Operational guidance" refers to specific instructions and guides provided to users regarding the initial setup and usage of observation equipment, as well as precautions to take during observation.

[0072] "Environmental conditions" refer to factors that affect astronomical observations, including both light conditions and weather conditions.

[0073] "Time and direction" refers to information indicating the time of day and direction in which an object to be observed is most easily visible during astronomical observations.

[0074] "Evaluation" refers to feedback that users provide to the system after observation, and this information contributes to improving the observation experience and the system itself.

[0075] This invention is a system for users to efficiently perform astronomical observations. Based on information entered by the user, this system provides optimal observation conditions and includes features to support observations, particularly for beginners.

[0076] Users utilize devices such as smartphones and personal computers. These devices access the system through a browser or a dedicated application. In this environment, users can input information such as the celestial object to be observed, the location of the observation site, the desired date and time, and the specifications of the observation equipment to be used.

[0077] The terminal transmits the entered information to the server via the internet. Upon receiving the information, the server uses an external recording device to obtain the light environment and weather conditions of the observation site. Commonly used external databases include APIs that provide weather information and light pollution map databases.

[0078] The server analyzes the acquired data and calculates the optimal time and direction for astronomical observation based on environmental conditions. This calculation utilizes astronomical computation libraries and other resources. Furthermore, the server uses a generative AI model to automatically generate instructions for operating observation equipment tailored to the user's knowledge level. This provides specific guidance to novice users on how to set up their telescopes and points to be aware of during observations.

[0079] The generated observation plan and operational instructions are delivered from the server to the terminal. The terminal visually displays this information to the user to support understanding and implementation. For example, information such as "The optimal time for observation is from 9 PM to 11 PM, and the observation target is located in the southeast direction" may be displayed.

[0080] Users perform observations according to the provided information. After the observations, they can send feedback to the server via their terminal. This feedback is reflected in the system's analysis model, contributing to more accurate observation planning and personalized operational guidance.

[0081] A possible example of a prompt message would be: "For astronomical observation, please tell me the best time and location to observe Saturn from Tokyo. I would like to observe it on November 3, 2023 at 8 PM, and I will be using telescope option B."

[0082] This system allows users to effectively enjoy astronomical observation even without advanced expertise, and the system is constantly being improved through continuous feedback.

[0083] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0084] Step 1:

[0085] The user inputs the celestial object to be observed, the observation location, the desired date and time, and the specifications of the observation equipment to be used, using the terminal's user interface. The information entered here serves as the basis for subsequent processing, determining the observation conditions.

[0086] Step 2:

[0087] The terminal sends user-entered information to the server via the HTTP protocol. Efficient data transfer is achieved by serializing the input data, converting it to a format suitable for the communication protocol, and sending it to the server.

[0088] Step 3:

[0089] The server analyzes the received observation data and acquires data on the light environment and meteorological conditions of the observation site via an external recording device. The input is the user's observation data, and the output is the latest environmental data of the observation site. An API call is made to receive data in JSON format.

[0090] Step 4:

[0091] The server analyzes the acquired environmental data and uses an astronomical computing library to calculate the optimal time and direction for observation. The input is light environment and meteorological data, and the output is optimal observation schedule information and direction. Here, the server performs time calculations to identify the time period when light pollution is minimized.

[0092] Step 5:

[0093] The server uses a generative AI model to automatically generate operating instructions for observation equipment for novice users. The inputs are the observation conditions and the user's skill level, and the output is the instruction content. Here, the generative AI model dynamically creates specific operating steps according to the observation conditions.

[0094] Step 6:

[0095] The server sends the generated observation plan and operational instructions to the terminal. Here, the data is formatted into a user-friendly format such as HTML or PDF. The input is observation information and instruction data, and the output is instruction information presented to the user.

[0096] Step 7:

[0097] Users conduct astronomical observations according to the observation plan and operating instructions displayed on the terminal. This section provides detailed instructions on how users specifically set up their observation equipment and proceed with their observations.

[0098] Step 8:

[0099] After completing their observations, users send feedback to the server via their terminal. The input is the observation experience and evaluation, and the output is feedback information for improvement. This allows the system's analysis model to be continuously updated, and improvements are made based on user feedback.

[0100] (Application Example 1)

[0101] 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."

[0102] Enjoying the process of observing phenomena often requires specialized knowledge and experience, which can be a significant hurdle, especially for beginners. Furthermore, it's difficult to create optimal conditions for observation, and results are frequently affected by changes in weather and environmental conditions. Additionally, there's a lack of methods to maximize the learning and educational benefits of observation, highlighting the need for personalized guidance tailored to each user.

[0103] 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.

[0104] In this invention, the server includes means for receiving instructions from the user and obtaining environmental and weather conditions from external sources using information about the evaluation site; means for calculating the optimal time and direction for observing phenomena based on the obtained conditions; means for automatically generating and providing instructions on how to operate the device and suggestions on how to take photographs to novice users; and means for providing personalized experience guides using information terminals. This reduces the technical burden on the user and makes it possible to provide a high-quality observation experience and learning effect.

[0105] A "user" refers to the entity that uses the system to observe phenomena.

[0106] An "evaluation point" refers to a specific geographical location where the phenomenon is observed.

[0107] "Environmental conditions" refer to ambient brightness and other properties that affect the visibility of the object being observed.

[0108] "Weather conditions" refer to the meteorological conditions at the time of observation, such as precipitation, cloud cover, and wind speed.

[0109] "External information sources" refer to external databases or sources that provide data on environmental and weather conditions.

[0110] "Phenomenon observation" refers to the act or process of observing a specific natural phenomenon.

[0111] "Timing and direction" refers to parameters that indicate the optimal date, time, and direction for observing the phenomenon.

[0112] "Apparatus" refers to observational instruments and equipment used to observe phenomena.

[0113] "Operating procedure instructions" refers to information that explains how to use the device.

[0114] "Photography method" refers to the procedures and techniques for taking photographs to record observations of phenomena.

[0115] "Automatic generation" refers to a process in which a system generates information based on statistical models or rules without requiring manual intervention.

[0116] An "information terminal" refers to an electronic device used by a user to receive information.

[0117] An "experience guide" refers to the guidance and support information provided to enhance the user's observation experience.

[0118] The system implementing this invention mainly consists of a server and a user information terminal. The following describes how each component functions.

[0119] The server first receives information sent by the user, including the evaluation location, the phenomenon to be observed, and the desired observation date and time. The server uses this information to obtain the relevant environmental and weather conditions from external sources. This process involves using an API (e.g., the OpenWeatherMap API) to retrieve weather data.

[0120] Next, the server uses an AI algorithm to calculate the optimal time and direction for observing the phenomenon, based on the acquired weather and environmental conditions. This uses a machine learning model based on TENSORFLOW®. This model derives the most suitable date, time, and direction to minimize the effects of light pollution.

[0121] Furthermore, the server automatically generates operating instructions and shooting methods according to the user's skill level and delivers them to the user's information terminal. For beginners, the instructions are particularly concise and easy to understand. In this process, natural language processing using Python is employed to generate content tailored to the user.

[0122] The information terminal displays detailed observation plans and operating procedure instructions to the user. This includes visualized data and real-time advice. Furthermore, the experience guide function allows for the display of information about the observation target using AR technology. Integration with the Google® Maps API assists in visualizing observation locations.

[0123] After conducting actual observations, users send feedback about their results and experiences to the system. This feedback is analyzed using a generative AI model and used to personalize future operating instructions and observation plans.

[0124] For example, if a user plans to observe Saturn at a specific location, the system will calculate the optimal observation time for that location and use Google Maps to show the direction from the user's current location. Furthermore, it can provide points to be aware of during observation and instructions on how to properly set up the camera, using natural language processing with Python. An example of a prompt would be, "Please tell me the best time and place to observe Saturn under conditions with minimal light pollution."

[0125] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0126] Step 1:

[0127] The user inputs the evaluation location, the phenomenon to be observed, and the desired observation date and time via an information terminal. These inputs are prepared as a dataset to be sent to the server. The server receives this dataset and holds it for processing in the next step.

[0128] Step 2:

[0129] The server uses the received information about the evaluation location to obtain environmental and weather conditions from an external source (e.g., the OpenWeatherMap API). The server sends an API request and receives light pollution and weather data as a response. Based on this data, observation conditions are constructed.

[0130] Step 3:

[0131] Based on the acquired environmental and weather conditions, the server uses an AI algorithm to calculate the optimal time and direction for observing the phenomenon. A model using TensorFlow estimates the required date, time, and direction. This output is compiled into a list as part of the observation plan.

[0132] Step 4:

[0133] The server generates operating instructions and shooting methods based on the user's skill level. Using natural language processing techniques with Python, prompts are provided to a generation AI model, which then generates appropriate explanations. These explanations are then incorporated into the overall observation plan.

[0134] Step 5:

[0135] The generated observation plan and explanation are delivered from the server to the information terminal. The terminal displays this information on the user interface and visualizes the guidance data using AR technology as needed. This allows the user to intuitively grasp the details of the observation.

[0136] Step 6:

[0137] After observation, the user enters feedback using an information terminal. This feedback data is sent to the server. The server stores this data and analyzes it using a generative AI model to personalize the next observation plan and explanation. This process ensures continuous improvement of the system.

[0138] 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.

[0139] This invention is a system designed to assist users performing astronomical observations. It includes functions to analyze user actions and emotional data, and to provide personalized operation tutorials and shooting suggestions. The specific operation of the system is described below.

[0140] First, the user inputs the celestial object they want to observe, their desired observation date and time, observation location, and the specifications of the telescope they will use into the terminal. The terminal receives this information and sends it to the server. In addition, the terminal uses a built-in emotion engine to recognize the user's emotional state in real time. This emotional data can be acquired through user interaction and biosensor data (e.g., voice tone, emotion analysis through facial recognition).

[0141] Based on the observation site information received from the user, the server retrieves relevant light pollution and weather condition data from an external database. Using this data, it calculates the optimal observation time and direction for the target celestial object and creates an observation plan.

[0142] The server further analyzes the user's emotional state as recognized by the emotion engine and generates an operation tutorial based on that. For example, if the user is showing anxiety or confusion, the tutorial will provide more detailed explanations and additional visual support. Conversely, if the user is showing enjoyment or interest, it can suggest challenging operations or experimental tasks.

[0143] The observation plan and operation tutorial generated in this way are delivered from the server to the terminal. The terminal displays the received information through the user interface. Specific examples include the date, time, and location of celestial objects, weather information, visuals regarding light pollution, and operation procedures and advice tailored to the user's emotional state.

[0144] After the observation period ends, users provide feedback through their devices. This feedback is analyzed by the server and used to improve the system's analysis model. Emotional data from the emotion engine is also accumulated, contributing to improved interaction accuracy and the provision of more personalized services in the future.

[0145] Thus, the present invention constructs a system that provides users with a comfortable and effective astronomical observation experience, and realizes a mechanism that can be applied to a wide range of users, from beginners to experienced observers.

[0146] The following describes the processing flow.

[0147] Step 1:

[0148] The user inputs the celestial object they want to observe, their desired date and time, observation location, and the specifications of the telescope they will use into the terminal. The terminal receives this information and sends it to the server. At the same time, the terminal activates an emotion engine and collects the user's emotion data.

[0149] Step 2:

[0150] Based on the observation location and astronomical information received from the user, the server accesses external light pollution and weather databases to obtain the light pollution level and weather conditions (temperature, humidity, and weather) for the relevant area.

[0151] Step 3:

[0152] The server analyzes the acquired data to determine the optimal observation timing and direction for the target celestial object. It then constructs an observation plan by referring to the celestial object's ephemeris data (celestial object position information).

[0153] Step 4:

[0154] The server customizes the user tutorial based on the user's emotions analyzed by the emotion engine. For example, if the user indicates stress, it adds supportive and detailed explanations and relaxation-promoting advice.

[0155] Step 5:

[0156] The server sends an optimized observation plan and a personalized operation tutorial to the terminal.

[0157] Step 6:

[0158] The terminal displays the transmitted observation plan and tutorial in its user interface. This includes a map of celestial body positions, observation conditions, and specific operating procedures and precautions.

[0159] Step 7:

[0160] Users conduct astronomical observations using the provided observation plan and tutorials as a guide. The emotion engine continues to monitor the user's emotions and adjusts interactions as needed.

[0161] Step 8:

[0162] After the observation period ends, users provide feedback through their devices, sharing their impressions and experiences. This feedback, including emotional data, is received by the server.

[0163] Step 9:

[0164] The server analyzes the collected feedback and sentiment data, updates the system's analysis model, and uses it as training data for the sentiment engine. This improves the service provided to users in the future.

[0165] (Example 2)

[0166] 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".

[0167] Conventional astronomical observation systems lacked detailed operational guidance for beginners and were inadequate in automatically generating observation plans based on observation conditions and environments. Furthermore, they did not incorporate user-centric interaction, making it difficult to provide an observation experience optimized for each individual.

[0168] 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.

[0169] In this invention, the server includes means for receiving information from the user and obtaining environmental and meteorological conditions from an external database using observation site data; means for calculating the optimal time and direction for astronomical observation based on the obtained environmental conditions; and means for recognizing the user's emotional state and automatically generating and providing telescope operation instructions and shooting methods accordingly. This makes it possible to provide observation plans and support optimized for each individual user and improve the astronomical observation experience.

[0170] "Means of receiving information from users" refers to the function by which the system acquires information such as observation targets, date and time, observation location, and equipment specifications entered by the user via a terminal.

[0171] "Means for obtaining environmental and meteorological conditions from an external database using data from observation sites" refers to a function that obtains light pollution, weather, and other environmental conditions for a designated observation point from an external database.

[0172] "Means for calculating the optimal time and direction for astronomical observation based on acquired environmental conditions" refers to a function that analyzes acquired environmental data to calculate the date, time, and direction at which the target celestial object can be best observed.

[0173] "A means of recognizing the user's emotional state and automatically generating and providing telescope operation guides and shooting methods accordingly" refers to a function that analyzes the user's emotions in real time and generates and provides customized operation guides and shooting advice tailored to that state.

[0174] "Means for distributing generated observation plans and operation manuals to user devices" refers to a function that sends the observation schedule and operation guide generated by the server to the user's terminal for display.

[0175] "A means of receiving user feedback after observations are completed and improving the system's analysis model" refers to a function that receives user feedback after observations are completed and incorporates it into the analysis model to improve the system.

[0176] This invention is a system for supporting astronomical observation, aiming to streamline user operation and provide a personalized observation experience. This system automatically generates an optimal observation plan and operation tutorial based on user input information. Specific embodiments of this invention are described below.

[0177] The user inputs details of the celestial object to be observed, the desired observation date and time, the observation location, and the telescope to be used into the terminal. The terminal is equipped with an interface for managing the input information, which enhances user convenience.

[0178] This device uses a built-in emotion recognition engine to evaluate the user's emotional state in real time during input. This engine understands the user's state by analyzing voice tone and using facial recognition technology. The data collected by the device is sent to the server in an encoded form.

[0179] The server analyzes the acquired data and retrieves light pollution and weather data relevant to the observation site from an external database. This database includes information sources such as weather forecast APIs and light pollution maps. The server uses this data to calculate the optimal time and direction for observation.

[0180] Furthermore, the server utilizes a generative AI model to create personalized tutorials based on the user's emotional state. For example, if a user shows confusion, the tutorial will include detailed step-by-step instructions and image-based support information.

[0181] The generated observation plan and tutorial are delivered from the server to the terminal. The terminal receives them and displays them on the user interface. For example, if a user enters the prompt "I want to know what celestial objects will be visible in the direction of Mt. Fuji tonight. Since it's a new moon, the stars should be clearly visible," the system analyzes this and provides an appropriate observation plan and tutorial.

[0182] After the observation is complete, the user enters feedback about the observation experience via a terminal. This feedback is analyzed on the server and used to adjust the system's analysis model and improve the individual user experience. The accumulated data contributes to improving the accuracy of future observations.

[0183] Thus, this system allows users to enjoy a comfortable and efficient astronomical observation experience. This invention caters to a wide range of users, from beginners to experienced observers, and provides services that meet their specific needs.

[0184] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0185] Step 1:

[0186] The user inputs the celestial object they wish to observe, their desired observation date and time, observation location, and the specifications of the telescope they will use into the terminal. This input information is used as basic data for creating the observation plan. Specifically, the user fills in the information into a form in a dedicated application on the terminal, and this registers the details in the user interface.

[0187] Step 2:

[0188] The device acquires the user's emotional state in real time, along with the input information, using its built-in emotion recognition engine. Specifically, it utilizes a voice tone sensor and a facial recognition camera to extract emotional data from the user's voice tone and facial expressions. After this data is analyzed, it is ready to be sent to the server.

[0189] Step 3:

[0190] The terminal sends collected user input information and emotional state data to the server. This data is encrypted using a communication protocol and securely transferred to the server. The output here is a comprehensive user dataset for the server to use for analysis.

[0191] Step 4:

[0192] The server uses the received observation data to access an external database and retrieve light pollution data and weather conditions for the relevant observation site. This information is obtained via an API and serves as input data necessary for evaluating observation conditions. Using this data, the optimal time and direction for observation are calculated.

[0193] Step 5:

[0194] The server utilizes a generative AI model to automatically generate operation tutorials based on user sentiment data. Specifically, if the user expresses anxiety, it creates detailed operation instructions; if they express enjoyment, it offers challenging suggestions. The final output is a customized operation guide.

[0195] Step 6:

[0196] The server delivers the created observation plan and operation tutorial to the terminal. The terminal receives this and displays it on the user interface, providing information to the user. Specifically, the screen displays the optimal date, time, direction, and operating procedures for astronomical observation.

[0197] Step 7:

[0198] After the observation is complete, the user enters feedback on the observation via a terminal. This feedback is sent from the terminal to the server and used to improve the system's analysis model. The accumulated data will contribute to future personalized suggestions and accuracy improvements.

[0199] (Application Example 2)

[0200] 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".

[0201] Conventional astronomical observation systems have difficulty dynamically changing content to suit users' interests and skill levels, and also have limited means of sharing observation experiences with others in real time. Therefore, there is a need for a system that can improve the quality of the observation experience and accommodate a wider range of users.

[0202] 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.

[0203] In this invention, the server includes means for receiving input from the user and obtaining light pollution and weather conditions from an external database using information about the observation site; means for calculating the optimal timing and direction for astronomical observation based on the obtained observation conditions; means for sharing the observation status in real time via a communication network; means for analyzing the user's emotional data and dynamically changing the content during observation; means for distributing the generated observation plan and operation tutorial to the user's information processing device; and means for receiving feedback from the user and improving the system's analysis model. This enables the provision of personalized observation guides in real time, enriching the observation experience and allowing for sharing among users.

[0204] A "user" is someone who inputs data to use the system for astronomical observation.

[0205] "Observation site" refers to the location where the user intends to conduct astronomical observations, and includes information such as its geographical location and surrounding environmental conditions.

[0206] "Light pollution" refers to artificial light that interferes with astronomical observations at observation sites and is a major factor that significantly affects observation conditions.

[0207] "Weather conditions" refers to meteorological information that affects astronomical observations, such as the weather at the observation site, wind speed, and humidity.

[0208] An "external database" is an external information storage device that the system accesses to obtain information about light pollution and weather conditions.

[0209] "Observation conditions" is a general term for information regarding the environment, time, and location necessary for astronomical observation, including light pollution and weather conditions.

[0210] "Means of sharing in real time" refers to methods for instantly sharing observations with other users via a communication network.

[0211] "Emotional data" refers to data that indicates the user's psychological state, and is information obtained through voice tone and facial expression analysis.

[0212] "Dynamically changing content" refers to the act of optimizing the observation guides and information provided in real time based on user sentiment data.

[0213] An "information processing device," also known as a user terminal, is an electronic device that has the function of receiving and displaying observation plans and operation tutorials.

[0214] "Feedback" refers to information about impressions and suggestions for improvement provided by users after completing their observation experience, and contributes to improving the system's analysis model.

[0215] This invention provides a system for making astronomical observation a personalized and enriching experience. The system optimizes observation conditions based on user input and provides observation guidance and experience based on that information. The interactive interaction between the server, terminal, and user enhances the effectiveness of the observation.

[0216] The server receives information about the observation location and date / time entered by the user, accesses external light pollution and weather condition databases, and collects this data. Based on the collected data, it calculates the optimal observation timing and direction for astronomical observation. Based on the calculation results, it generates an observation plan and provides it to the user.

[0217] The device receives observation plans and operation tutorials, which are displayed via a user interface. During this process, the device uses voice tone and facial recognition technology to collect user emotion data. Specifically, it uses emotion recognition APIs (e.g., Microsoft® Azure® Emotion API) to evaluate the user's psychological state.

[0218] Users can share their observations with other users in real time via their devices. To achieve this, real-time streaming technologies (e.g., WebRTC) are used to share the observation experience with others over a communication network. Through this sharing function, astronomical observation is expanded beyond a personal experience into shareable content.

[0219] For example, when observing the Perseid meteor shower with family in the summer, the user might prompt, "Generate a guide for observing the Perseid meteor shower." Based on the proposed observation plan, the system uses the user's emotional data and real-time feedback to adjust the guidance during the observation, enhancing the observation experience.

[0220] This system will make astronomical observation more accessible and provide personalized services to individual users. User feedback will be used to improve the system and further enhance the quality of the observation experience in the future.

[0221] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0222] Step 1:

[0223] The user enters information into the terminal, including the celestial object they wish to observe, the date and time, the observation location, and the optical instruments they will use. This input data is sent to the server. Based on this information, the server accesses an external database to obtain light pollution and weather conditions, and collects the necessary environmental data.

[0224] Step 2:

[0225] The server uses acquired weather data and light pollution information to calculate the optimal observation time and direction for astronomical observation. Known models and algorithms from the database are applied to the calculation. The calculation results are generated as an observation plan and sent to the terminal.

[0226] Step 3:

[0227] The terminal displays the observation plan received from the server through the user interface. The terminal analyzes the user's voice tone and facial expressions using an emotion recognition API through interaction with the user and collects the user's emotional data.

[0228] Step 4:

[0229] The server receives emotional data from the terminal. The analyzed emotional data is used to adjust the guide content provided during observation. If the user shows signs of anxiety, dynamic content changes are made, such as providing detailed explanations or visual support.

[0230] Step 5:

[0231] Users share their observation experience with other users by utilizing real-time streaming technology via their devices during observation. In this process, the devices encode video data and transmit it over the network.

[0232] Step 6:

[0233] Once the observation is complete, the user sends feedback to the server via their device. The server analyzes the feedback and stores it in a database for future system improvements. Emotional data is also stored in the same way and used to improve personalized services.

[0234] 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.

[0235] 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.

[0236] 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.

[0237] [Second Embodiment]

[0238] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0239] 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.

[0240] 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).

[0241] 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.

[0242] 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.

[0243] 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).

[0244] 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.

[0245] 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.

[0246] 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.

[0247] 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.

[0248] 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.

[0249] 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".

[0250] This invention is designed as a system to support astronomical observation and is equipped with various functions to improve user convenience. The following describes in detail how the system operates.

[0251] The first step for the user is to input information, including specifying the object to observe and setting the observation location. The user enters the desired celestial object (e.g., Saturn), desired observation date and time, and the specifications of the telescope to be used into the system. The terminal receives this information and sends it to the server.

[0252] Based on the information received from the user, the server uses the location information of the observation site to retrieve light pollution and weather conditions from an external database. This prepares the server to determine the optimal conditions for observation. For example, by referring to a light pollution map of the observation area and the current weather conditions, it can identify the time when visibility is as good as possible.

[0253] Next, the server analyzes the acquired observation conditions and consults an astronomical database for the target celestial object. This allows it to calculate the optimal timing and direction for observation and automatically generate an observation schedule. For example, when observing Saturn, it determines the time and direction when Saturn is highest in the sky and light pollution is minimal.

[0254] For beginner users, the server generates even more detailed operation tutorials. These include instructions on how to set up the telescope, points to be aware of during observation, how to track celestial objects, and camera setup procedures. This makes it easy for even beginners to prepare for astronomical observation.

[0255] The server then delivers the generated observation plan and accompanying operation tutorial to the terminal. The terminal displays the received information on its user interface. For example, it may show a visualized light pollution map, estimated celestial object positions over time, and detailed operation guides.

[0256] Users perform observations according to the provided observation plan and tutorial. After the observation, users can send feedback to the server. This feedback is reflected in the system's analysis model and used for future improvements. Specifically, this includes improving the tutorials provided based on user experience and improving the accuracy of the observation plan.

[0257] This system efficiently and effectively supports astronomical observation, making it possible for beginners in particular to enjoy observation without requiring a high level of expertise. With such preparation and support, users can easily conduct high-quality astronomical observations.

[0258] The following describes the processing flow.

[0259] Step 1:

[0260] The user enters the celestial object they want to observe, their desired date and time, observation location, and the specifications of the telescope they will use into the terminal. The terminal receives this information and sends it to the server.

[0261] Step 2:

[0262] Based on the location information of the observation site received from the user, the server accesses an external database to obtain data on light pollution levels and weather conditions (temperature, humidity, weather, etc.).

[0263] Step 3:

[0264] The server uses the input data on the object to be observed to calculate the most suitable date, time, and direction for observation. In doing so, it refers to a database of celestial body positions to determine the appropriate time slot.

[0265] Step 4:

[0266] The server generates user tutorials for beginners, including instructions on setting up the telescope, selecting shooting modes, and tracking celestial objects.

[0267] Step 5:

[0268] The server sends the optimized observation plan and generated operation tutorial to the terminal.

[0269] Step 6:

[0270] The terminal displays the received observation plan and tutorial in its user interface, allowing the user to proceed with observation preparations.

[0271] Step 7:

[0272] Users conduct actual observations according to the provided information and send their results and impressions as feedback to the server via their device.

[0273] Step 8:

[0274] The server analyzes the feedback received from users and uses it to improve system performance and refine the next observation plan.

[0275] (Example 1)

[0276] 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."

[0277] For beginners conducting astronomical observations, analyzing observation conditions, determining the optimal timing, and operating observation equipment can be difficult, making efficient observation challenging. Furthermore, there is a need to incorporate observation experience into the system and provide observation guidance tailored to individual users. This means users can obtain a high-quality observation experience, while the system must be continuously improved using individual feedback.

[0278] 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.

[0279] This invention includes a server that receives information from the user and uses location information to acquire light environment and weather conditions from an external recording device; a server that calculates the optimal time and direction for astronomical observation based on the acquired environmental conditions; and a server that automatically generates and provides instructions for operating observation equipment and imaging techniques for beginners. This makes it easy for beginners to perform astronomical observations, and the system can be improved based on user feedback to provide more personalized instructions and plans.

[0280] The "user device" is a terminal for a user to access the system and input information, including devices such as personal computers and smartphones.

[0281] The "server" is a computing device that receives information sent from a user, obtains, analyzes the optical environment and meteorological conditions, and further generates and provides operation guidance and observation plans.

[0282] The "external recording device" refers to an external database or cloud service that provides data on the optical environment and meteorological conditions necessary for astronomical observations.

[0283] The "optical environment" is data indicating the light pollution level at the observation site, and is an environmental condition that affects the clarity of the field of view in night observations.

[0284] The "meteorological conditions" are information regarding the weather and atmospheric conditions during astronomical observations, and are factors that affect the observation accuracy.

[0285] The "observation device" is a device used to observe celestial bodies, including devices such as telescopes and cameras.

[0286] The "operation guidance" is specific guidance and advice provided to the user regarding the initial settings, usage methods, and precautions during observations of the observation device.

[0287] The "environmental conditions" are conditions that include both the optical environment and meteorological conditions as factors affecting astronomical observations.

[0288] The "time and direction" is information indicating the time period when the observation target is most visible and the direction at that time in astronomical observations.

[0289] The "evaluation" is feedback given by the user to the system after observations, and is information that contributes to the improvement of the observation experience and the system.

[0290] This invention is a system for users to efficiently perform astronomical observations. Based on information entered by the user, this system provides optimal observation conditions and includes features to support observations, particularly for beginners.

[0291] Users utilize devices such as smartphones and personal computers. These devices access the system through a browser or a dedicated application. In this environment, users can input information such as the celestial object to be observed, the location of the observation site, the desired date and time, and the specifications of the observation equipment to be used.

[0292] The terminal transmits the entered information to the server via the internet. Upon receiving the information, the server uses an external recording device to obtain the light environment and weather conditions of the observation site. Commonly used external databases include APIs that provide weather information and light pollution map databases.

[0293] The server analyzes the acquired data and calculates the optimal time and direction for astronomical observation based on environmental conditions. This calculation utilizes astronomical computation libraries and other resources. Furthermore, the server uses a generative AI model to automatically generate instructions for operating observation equipment tailored to the user's knowledge level. This provides specific guidance to novice users on how to set up their telescopes and points to be aware of during observations.

[0294] The generated observation plan and operational instructions are delivered from the server to the terminal. The terminal visually displays this information to the user to support understanding and implementation. For example, information such as "The optimal time for observation is from 9 PM to 11 PM, and the observation target is located in the southeast direction" may be displayed.

[0295] Users perform observations according to the provided information. After the observations, they can send feedback to the server via their terminal. This feedback is reflected in the system's analysis model, contributing to more accurate observation planning and personalized operational guidance.

[0296] A possible example of a prompt message would be: "For astronomical observation, please tell me the best time and location to observe Saturn from Tokyo. I would like to observe it on November 3, 2023 at 8 PM, and I will be using telescope option B."

[0297] This system allows users to effectively enjoy astronomical observation even without advanced expertise, and the system is constantly being improved through continuous feedback.

[0298] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0299] Step 1:

[0300] The user inputs the celestial object to be observed, the observation location, the desired date and time, and the specifications of the observation equipment to be used, using the terminal's user interface. The information entered here serves as the basis for subsequent processing, determining the observation conditions.

[0301] Step 2:

[0302] The terminal sends user-entered information to the server via the HTTP protocol. Efficient data transfer is achieved by serializing the input data, converting it to a format suitable for the communication protocol, and sending it to the server.

[0303] Step 3:

[0304] The server analyzes the received observation data and acquires data on the light environment and meteorological conditions of the observation site via an external recording device. The input is the user's observation data, and the output is the latest environmental data of the observation site. An API call is made to receive data in JSON format.

[0305] Step 4:

[0306] The server analyzes the acquired environmental condition data and calculates the optimal time and azimuth for observation using an astronomical calculation library. The input is light environment and meteorological data, and the output is the optimal observation schedule information and azimuth. Here, the server performs time calculation to identify the time zone with the minimum light pollution.

[0307] Step 5:

[0308] The server automatically generates operation guidance for the observation device for novice users using a generation AI model. The input is the observation conditions and the user's operation level, and the output is the guidance content. Here, the generation AI model dynamically creates specific operation steps according to the observation conditions.

[0309] Step 6:

[0310] The server sends the generated observation plan and operation guidance to the terminal. Here, the data is formatted into a user-friendly visual form such as HTML or PDF. The input is the observation information and guidance data, and the output is the instruction information presented to the user.

[0311] Step 7:

[0312] The user conducts celestial body observation according to the observation plan and operation guidance displayed on the terminal. Here, details of how the user specifically sets the observation device and proceeds with the observation are shown.

[0313] Step 8:

[0314] After the observation, the user sends feedback to the server through the terminal. The input is the observation experience and evaluation, and the output is the feedback information for improvement. As a result, the analysis model of the system is continuously updated, and improvements based on user feedback are made.

[0315] (Application Example 1)

[0316] 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."

[0317] Enjoying the process of observing phenomena often requires specialized knowledge and experience, which can be a significant hurdle, especially for beginners. Furthermore, it's difficult to create optimal conditions for observation, and results are frequently affected by changes in weather and environmental conditions. Additionally, there's a lack of methods to maximize the learning and educational benefits of observation, highlighting the need for personalized guidance tailored to each user.

[0318] 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.

[0319] In this invention, the server includes means for receiving instructions from the user and obtaining environmental and weather conditions from external sources using information about the evaluation site; means for calculating the optimal time and direction for observing phenomena based on the obtained conditions; means for automatically generating and providing instructions on how to operate the device and suggestions on how to take photographs to novice users; and means for providing personalized experience guides using information terminals. This reduces the technical burden on the user and makes it possible to provide a high-quality observation experience and learning effect.

[0320] A "user" refers to the entity that uses the system to observe phenomena.

[0321] An "evaluation point" refers to a specific geographical location where the phenomenon is observed.

[0322] "Environmental conditions" refer to ambient brightness and other properties that affect the visibility of the object being observed.

[0323] "Weather conditions" refer to the meteorological conditions at the time of observation, such as precipitation, cloud cover, and wind speed.

[0324] "External information sources" refer to external databases or sources that provide data on environmental and weather conditions.

[0325] "Phenomenon observation" refers to the act or process of observing a specific natural phenomenon.

[0326] "Timing and direction" refers to parameters that indicate the optimal date, time, and direction for observing the phenomenon.

[0327] "Apparatus" refers to observational instruments and equipment used to observe phenomena.

[0328] "Operating procedure instructions" refers to information that explains how to use the device.

[0329] "Photography method" refers to the procedures and techniques for taking photographs to record observations of phenomena.

[0330] "Automatic generation" refers to a process in which a system generates information based on statistical models or rules without requiring manual intervention.

[0331] An "information terminal" refers to an electronic device used by a user to receive information.

[0332] An "experience guide" refers to the guidance and support information provided to enhance the user's observation experience.

[0333] The system implementing this invention mainly consists of a server and a user information terminal. The following describes how each component functions.

[0334] The server first receives information sent by the user, including the evaluation location, the phenomenon to be observed, and the desired observation date and time. The server uses this information to obtain the relevant environmental and weather conditions from external sources. This process involves using an API (e.g., the OpenWeatherMap API) to retrieve weather data.

[0335] Next, the server uses an AI algorithm to calculate the optimal time and direction for observing the phenomenon, based on the acquired weather and environmental conditions. This uses a machine learning model based on TensorFlow. This model derives the most suitable date, time, and direction to minimize the effects of light pollution.

[0336] Furthermore, the server automatically generates operating instructions and shooting methods according to the user's skill level and delivers them to the user's information terminal. For beginners, the instructions are particularly concise and easy to understand. In this process, natural language processing using Python is employed to generate content tailored to the user.

[0337] The information terminal displays detailed observation plans and operating procedure instructions to the user. This includes visualized data and real-time advice. Furthermore, the experience guide function allows for the display of information about the observation target using AR technology. Integration with the Google Maps API assists in visualizing observation locations.

[0338] After conducting actual observations, users send feedback about their results and experiences to the system. This feedback is analyzed using a generative AI model and used to personalize future operating instructions and observation plans.

[0339] For example, if a user plans to observe Saturn at a specific location, the system will calculate the optimal observation time for that location and use Google Maps to show the direction from the user's current location. Furthermore, it can provide points to be aware of during observation and instructions on how to properly set up the camera, using natural language processing with Python. An example of a prompt would be, "Please tell me the best time and place to observe Saturn under conditions with minimal light pollution."

[0340] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0341] Step 1:

[0342] The user inputs the evaluation location, the phenomenon to be observed, and the desired observation date and time via an information terminal. These inputs are prepared as a dataset to be sent to the server. The server receives this dataset and holds it for processing in the next step.

[0343] Step 2:

[0344] The server uses the received information about the evaluation location to obtain environmental and weather conditions from an external source (e.g., the OpenWeatherMap API). The server sends an API request and receives light pollution and weather data as a response. Based on this data, observation conditions are constructed.

[0345] Step 3:

[0346] Based on the acquired environmental and weather conditions, the server uses an AI algorithm to calculate the optimal time and direction for observing the phenomenon. A model using TensorFlow estimates the required date, time, and direction. This output is compiled into a list as part of the observation plan.

[0347] Step 4:

[0348] The server generates operating instructions and shooting methods based on the user's skill level. Using natural language processing techniques with Python, prompts are provided to a generation AI model, which then generates appropriate explanations. These explanations are then incorporated into the overall observation plan.

[0349] Step 5:

[0350] The generated observation plan and explanation are delivered from the server to the information terminal. The terminal displays this information on the user interface and visualizes the guidance data using AR technology as needed. This allows the user to intuitively grasp the details of the observation.

[0351] Step 6:

[0352] After observation, the user enters feedback using an information terminal. This feedback data is sent to the server. The server stores this data and analyzes it using a generative AI model to personalize the next observation plan and explanation. This process ensures continuous improvement of the system.

[0353] 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.

[0354] This invention is a system designed to assist users performing astronomical observations. It includes functions to analyze user actions and emotional data, and to provide personalized operation tutorials and shooting suggestions. The specific operation of the system is described below.

[0355] First, the user inputs the celestial object they want to observe, their desired observation date and time, observation location, and the specifications of the telescope they will use into the terminal. The terminal receives this information and sends it to the server. In addition, the terminal uses a built-in emotion engine to recognize the user's emotional state in real time. This emotional data can be acquired through user interaction and biosensor data (e.g., voice tone, emotion analysis through facial recognition).

[0356] Based on the observation site information received from the user, the server retrieves relevant light pollution and weather condition data from an external database. Using this data, it calculates the optimal observation time and direction for the target celestial object and creates an observation plan.

[0357] The server further analyzes the user's emotional state as recognized by the emotion engine and generates an operation tutorial based on that. For example, if the user is showing anxiety or confusion, the tutorial will provide more detailed explanations and additional visual support. Conversely, if the user is showing enjoyment or interest, it can suggest challenging operations or experimental tasks.

[0358] The observation plan and operation tutorial generated in this way are delivered from the server to the terminal. The terminal displays the received information through the user interface. Specific examples include the date, time, and location of celestial objects, weather information, visuals regarding light pollution, and operation procedures and advice tailored to the user's emotional state.

[0359] After the observation period ends, users provide feedback through their devices. This feedback is analyzed by the server and used to improve the system's analysis model. Emotional data from the emotion engine is also accumulated, contributing to improved interaction accuracy and the provision of more personalized services in the future.

[0360] Thus, the present invention constructs a system that provides users with a comfortable and effective astronomical observation experience, and realizes a mechanism that can be applied to a wide range of users, from beginners to experienced observers.

[0361] The following describes the processing flow.

[0362] Step 1:

[0363] The user inputs the celestial object they want to observe, their desired date and time, observation location, and the specifications of the telescope they will use into the terminal. The terminal receives this information and sends it to the server. At the same time, the terminal activates an emotion engine and collects the user's emotion data.

[0364] Step 2:

[0365] Based on the observation location and astronomical information received from the user, the server accesses external light pollution and weather databases to obtain the light pollution level and weather conditions (temperature, humidity, and weather) for the relevant area.

[0366] Step 3:

[0367] The server analyzes the acquired data to determine the optimal observation timing and direction for the target celestial object. It then constructs an observation plan by referring to the celestial object's ephemeris data (celestial object position information).

[0368] Step 4:

[0369] The server customizes the user tutorial based on the user's emotions analyzed by the emotion engine. For example, if the user indicates stress, it adds supportive and detailed explanations and relaxation-promoting advice.

[0370] Step 5:

[0371] The server sends an optimized observation plan and a personalized operation tutorial to the terminal.

[0372] Step 6:

[0373] The terminal displays the transmitted observation plan and tutorial in its user interface. This includes a map of celestial body positions, observation conditions, and specific operating procedures and precautions.

[0374] Step 7:

[0375] Users conduct astronomical observations using the provided observation plan and tutorials as a guide. The emotion engine continues to monitor the user's emotions and adjusts interactions as needed.

[0376] Step 8:

[0377] After the observation period ends, users provide feedback through their devices, sharing their impressions and experiences. This feedback, including emotional data, is received by the server.

[0378] Step 9:

[0379] The server analyzes the collected feedback and sentiment data, updates the system's analysis model, and uses it as training data for the sentiment engine. This improves the service provided to users in the future.

[0380] (Example 2)

[0381] 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".

[0382] Conventional astronomical observation systems lacked detailed operational guidance for beginners and were inadequate in automatically generating observation plans based on observation conditions and environments. Furthermore, they did not incorporate user-centric interaction, making it difficult to provide an observation experience optimized for each individual.

[0383] 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.

[0384] In this invention, the server includes means for receiving information from the user and obtaining environmental and meteorological conditions from an external database using observation site data; means for calculating the optimal time and direction for astronomical observation based on the obtained environmental conditions; and means for recognizing the user's emotional state and automatically generating and providing telescope operation instructions and shooting methods accordingly. This makes it possible to provide observation plans and support optimized for each individual user and improve the astronomical observation experience.

[0385] "Means of receiving information from users" refers to the function by which the system acquires information such as observation targets, date and time, observation location, and equipment specifications entered by the user via a terminal.

[0386] "Means for obtaining environmental and meteorological conditions from an external database using data from observation sites" refers to a function that obtains light pollution, weather, and other environmental conditions for a designated observation point from an external database.

[0387] "Means for calculating the optimal time and direction for astronomical observation based on acquired environmental conditions" refers to a function that analyzes acquired environmental data to calculate the date, time, and direction at which the target celestial object can be best observed.

[0388] "A means of recognizing the user's emotional state and automatically generating and providing telescope operation guides and shooting methods accordingly" refers to a function that analyzes the user's emotions in real time and generates and provides customized operation guides and shooting advice tailored to that state.

[0389] "Means for distributing generated observation plans and operation manuals to user devices" refers to a function that sends the observation schedule and operation guide generated by the server to the user's terminal for display.

[0390] "A means of receiving user feedback after observations are completed and improving the system's analysis model" refers to a function that receives user feedback after observations are completed and incorporates it into the analysis model to improve the system.

[0391] This invention is a system for supporting astronomical observation, aiming to streamline user operation and provide a personalized observation experience. This system automatically generates an optimal observation plan and operation tutorial based on user input information. Specific embodiments of this invention are described below.

[0392] The user inputs details of the celestial object to be observed, the desired observation date and time, the observation location, and the telescope to be used into the terminal. The terminal is equipped with an interface for managing the input information, which enhances user convenience.

[0393] This device uses a built-in emotion recognition engine to evaluate the user's emotional state in real time during input. This engine understands the user's state by analyzing voice tone and using facial recognition technology. The data collected by the device is sent to the server in an encoded form.

[0394] The server analyzes the acquired data and retrieves light pollution and weather data relevant to the observation site from an external database. This database includes information sources such as weather forecast APIs and light pollution maps. The server uses this data to calculate the optimal time and direction for observation.

[0395] Furthermore, the server utilizes a generative AI model to create personalized tutorials based on the user's emotional state. For example, if a user shows confusion, the tutorial will include detailed step-by-step instructions and image-based support information.

[0396] The generated observation plan and tutorial are delivered from the server to the terminal. The terminal receives them and displays them on the user interface. For example, if a user enters the prompt "I want to know what celestial objects will be visible in the direction of Mt. Fuji tonight. Since it's a new moon, the stars should be clearly visible," the system analyzes this and provides an appropriate observation plan and tutorial.

[0397] After the observation is complete, the user enters feedback about the observation experience via a terminal. This feedback is analyzed on the server and used to adjust the system's analysis model and improve the individual user experience. The accumulated data contributes to improving the accuracy of future observations.

[0398] Thus, this system allows users to enjoy a comfortable and efficient astronomical observation experience. This invention caters to a wide range of users, from beginners to experienced observers, and provides services that meet their specific needs.

[0399] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0400] Step 1:

[0401] The user inputs the celestial object they wish to observe, their desired observation date and time, observation location, and the specifications of the telescope they will use into the terminal. This input information is used as basic data for creating the observation plan. Specifically, the user fills in the information into a form in a dedicated application on the terminal, and this registers the details in the user interface.

[0402] Step 2:

[0403] The device acquires the user's emotional state in real time, along with the input information, using its built-in emotion recognition engine. Specifically, it utilizes a voice tone sensor and a facial recognition camera to extract emotional data from the user's voice tone and facial expressions. After this data is analyzed, it is ready to be sent to the server.

[0404] Step 3:

[0405] The terminal sends collected user input information and emotional state data to the server. This data is encrypted using a communication protocol and securely transferred to the server. The output here is a comprehensive user dataset for the server to use for analysis.

[0406] Step 4:

[0407] The server uses the received observation data to access an external database and retrieve light pollution data and weather conditions for the relevant observation site. This information is obtained via an API and serves as input data necessary for evaluating observation conditions. Using this data, the optimal time and direction for observation are calculated.

[0408] Step 5:

[0409] The server utilizes a generative AI model to automatically generate operation tutorials based on user sentiment data. Specifically, if the user expresses anxiety, it creates detailed operation instructions; if they express enjoyment, it offers challenging suggestions. The final output is a customized operation guide.

[0410] Step 6:

[0411] The server delivers the created observation plan and operation tutorial to the terminal. The terminal receives this and displays it on the user interface, providing information to the user. Specifically, the screen displays the optimal date, time, direction, and operating procedures for astronomical observation.

[0412] Step 7:

[0413] After the observation is complete, the user enters feedback on the observation via a terminal. This feedback is sent from the terminal to the server and used to improve the system's analysis model. The accumulated data will contribute to future personalized suggestions and accuracy improvements.

[0414] (Application Example 2)

[0415] 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."

[0416] Conventional astronomical observation systems have difficulty dynamically changing content to suit users' interests and skill levels, and also have limited means of sharing observation experiences with others in real time. Therefore, there is a need for a system that can improve the quality of the observation experience and accommodate a wider range of users.

[0417] 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.

[0418] In this invention, the server includes means for receiving input from the user and obtaining light pollution and weather conditions from an external database using information about the observation site; means for calculating the optimal timing and direction for astronomical observation based on the obtained observation conditions; means for sharing the observation status in real time via a communication network; means for analyzing the user's emotional data and dynamically changing the content during observation; means for distributing the generated observation plan and operation tutorial to the user's information processing device; and means for receiving feedback from the user and improving the system's analysis model. This enables the provision of personalized observation guides in real time, enriching the observation experience and allowing for sharing among users.

[0419] A "user" is someone who inputs data to use the system for astronomical observation.

[0420] "Observation site" refers to the location where the user intends to conduct astronomical observations, and includes information such as its geographical location and surrounding environmental conditions.

[0421] "Light pollution" refers to artificial light that interferes with astronomical observations at observation sites and is a major factor that significantly affects observation conditions.

[0422] "Weather conditions" refers to meteorological information that affects astronomical observations, such as the weather at the observation site, wind speed, and humidity.

[0423] An "external database" is an external information storage device that the system accesses to obtain information about light pollution and weather conditions.

[0424] "Observation conditions" is a general term for information regarding the environment, time, and location necessary for astronomical observation, including light pollution and weather conditions.

[0425] "Means of sharing in real time" refers to methods for instantly sharing observations with other users via a communication network.

[0426] "Emotional data" refers to data that indicates the user's psychological state, and is information obtained through voice tone and facial expression analysis.

[0427] "Dynamically changing content" refers to the act of optimizing the observation guides and information provided in real time based on user sentiment data.

[0428] An "information processing device," also known as a user terminal, is an electronic device that has the function of receiving and displaying observation plans and operation tutorials.

[0429] "Feedback" refers to information about impressions and suggestions for improvement provided by users after completing their observation experience, and contributes to improving the system's analysis model.

[0430] This invention provides a system for making astronomical observation a personalized and enriching experience. The system optimizes observation conditions based on user input and provides observation guidance and experience based on that information. The interactive interaction between the server, terminal, and user enhances the effectiveness of the observation.

[0431] The server receives information about the observation location and date / time entered by the user, accesses external light pollution and weather condition databases, and collects this data. Based on the collected data, it calculates the optimal observation timing and direction for astronomical observation. Based on the calculation results, it generates an observation plan and provides it to the user.

[0432] The device receives observation plans and operation tutorials, which are displayed via a user interface. During this process, the device uses voice tone and facial recognition technology to collect user emotion data. Specifically, it utilizes an emotion recognition API (e.g., Microsoft Azure Emotion API) to evaluate the user's psychological state.

[0433] Users can share their observations with other users in real time via their devices. To achieve this, real-time streaming technologies (e.g., WebRTC) are used to share the observation experience with others over a communication network. Through this sharing function, astronomical observation is expanded beyond a personal experience into shareable content.

[0434] For example, when observing the Perseid meteor shower with family in the summer, the user might prompt, "Generate a guide for observing the Perseid meteor shower." Based on the proposed observation plan, the system uses the user's emotional data and real-time feedback to adjust the guidance during the observation, enhancing the observation experience.

[0435] This system will make astronomical observation more accessible and provide personalized services to individual users. User feedback will be used to improve the system and further enhance the quality of the observation experience in the future.

[0436] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0437] Step 1:

[0438] The user enters information into the terminal, including the celestial object they wish to observe, the date and time, the observation location, and the optical instruments they will use. This input data is sent to the server. Based on this information, the server accesses an external database to obtain light pollution and weather conditions, and collects the necessary environmental data.

[0439] Step 2:

[0440] The server uses acquired weather data and light pollution information to calculate the optimal observation time and direction for astronomical observation. Known models and algorithms from the database are applied to the calculation. The calculation results are generated as an observation plan and sent to the terminal.

[0441] Step 3:

[0442] The terminal displays the observation plan received from the server through the user interface. The terminal analyzes the user's voice tone and facial expressions using an emotion recognition API through interaction with the user and collects the user's emotional data.

[0443] Step 4:

[0444] The server receives emotional data from the terminal. The analyzed emotional data is used to adjust the guide content provided during observation. If the user shows signs of anxiety, dynamic content changes are made, such as providing detailed explanations or visual support.

[0445] Step 5:

[0446] Users share their observation experience with other users by utilizing real-time streaming technology via their devices during observation. In this process, the devices encode video data and transmit it over the network.

[0447] Step 6:

[0448] Once the observation is complete, the user sends feedback to the server via their device. The server analyzes the feedback and stores it in a database for future system improvements. Emotional data is also stored in the same way and used to improve personalized services.

[0449] 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.

[0450] 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.

[0451] 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.

[0452] [Third Embodiment]

[0453] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0454] 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.

[0455] 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).

[0456] 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.

[0457] 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.

[0458] 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).

[0459] 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.

[0460] 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.

[0461] 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.

[0462] 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.

[0463] 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.

[0464] 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".

[0465] This invention is designed as a system to support astronomical observation and is equipped with various functions to improve user convenience. The following describes in detail how the system operates.

[0466] The first step for the user is to input information, including specifying the object to observe and setting the observation location. The user enters the desired celestial object (e.g., Saturn), desired observation date and time, and the specifications of the telescope to be used into the system. The terminal receives this information and sends it to the server.

[0467] Based on the information received from the user, the server uses the location information of the observation site to retrieve light pollution and weather conditions from an external database. This prepares the server to determine the optimal conditions for observation. For example, by referring to a light pollution map of the observation area and the current weather conditions, it can identify the time when visibility is as good as possible.

[0468] Next, the server analyzes the acquired observation conditions and consults an astronomical database for the target celestial object. This allows it to calculate the optimal timing and direction for observation and automatically generate an observation schedule. For example, when observing Saturn, it determines the time and direction when Saturn is highest in the sky and light pollution is minimal.

[0469] For beginner users, the server generates even more detailed operation tutorials. These include instructions on how to set up the telescope, points to be aware of during observation, how to track celestial objects, and camera setup procedures. This makes it easy for even beginners to prepare for astronomical observation.

[0470] The server then delivers the generated observation plan and accompanying operation tutorial to the terminal. The terminal displays the received information on its user interface. For example, it may show a visualized light pollution map, estimated celestial object positions over time, and detailed operation guides.

[0471] Users perform observations according to the provided observation plan and tutorial. After the observation, users can send feedback to the server. This feedback is reflected in the system's analysis model and used for future improvements. Specifically, this includes improving the tutorials provided based on user experience and improving the accuracy of the observation plan.

[0472] This system efficiently and effectively supports astronomical observation, making it possible for beginners in particular to enjoy observation without requiring a high level of expertise. With such preparation and support, users can easily conduct high-quality astronomical observations.

[0473] The following describes the processing flow.

[0474] Step 1:

[0475] The user enters the celestial object they want to observe, their desired date and time, observation location, and the specifications of the telescope they will use into the terminal. The terminal receives this information and sends it to the server.

[0476] Step 2:

[0477] Based on the location information of the observation site received from the user, the server accesses an external database to obtain data on light pollution levels and weather conditions (temperature, humidity, weather, etc.).

[0478] Step 3:

[0479] The server uses the input data on the object to be observed to calculate the most suitable date, time, and direction for observation. In doing so, it refers to a database of celestial body positions to determine the appropriate time slot.

[0480] Step 4:

[0481] The server generates user tutorials for beginners, including instructions on setting up the telescope, selecting shooting modes, and tracking celestial objects.

[0482] Step 5:

[0483] The server sends the optimized observation plan and generated operation tutorial to the terminal.

[0484] Step 6:

[0485] The terminal displays the received observation plan and tutorial in its user interface, allowing the user to proceed with observation preparations.

[0486] Step 7:

[0487] Users conduct actual observations according to the provided information and send their results and impressions as feedback to the server via their device.

[0488] Step 8:

[0489] The server analyzes the feedback received from users and uses it to improve system performance and refine the next observation plan.

[0490] (Example 1)

[0491] 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."

[0492] For beginners conducting astronomical observations, analyzing observation conditions, determining the optimal timing, and operating observation equipment can be difficult, making efficient observation challenging. Furthermore, there is a need to incorporate observation experience into the system and provide observation guidance tailored to individual users. This means users can obtain a high-quality observation experience, while the system must be continuously improved using individual feedback.

[0493] 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.

[0494] This invention includes a server that receives information from the user and uses location information to acquire light environment and weather conditions from an external recording device; a server that calculates the optimal time and direction for astronomical observation based on the acquired environmental conditions; and a server that automatically generates and provides instructions for operating observation equipment and imaging techniques for beginners. This makes it easy for beginners to perform astronomical observations, and the system can be improved based on user feedback to provide more personalized instructions and plans.

[0495] A "user device" is a terminal used by a user to access a system and input information, and includes devices such as personal computers and smartphones.

[0496] A "server" is a computing device that receives information sent from users, acquires and analyzes optical environment and weather conditions, and generates and provides operational guidance and observation plans.

[0497] An "external recording device" refers to an external database or cloud service that provides data on the light environment and weather conditions necessary for astronomical observation.

[0498] "Light environment" refers to data indicating the level of light pollution at the observation site, and is an environmental condition that affects the clarity of visibility during nighttime observations.

[0499] "Meteorological conditions" refer to information about weather and atmospheric conditions during astronomical observations, and are factors that affect the accuracy of observations.

[0500] "Observation equipment" refers to instruments used to observe celestial bodies, including telescopes and cameras.

[0501] "Operational guidance" refers to specific instructions and guides provided to users regarding the initial setup and usage of observation equipment, as well as precautions to take during observation.

[0502] "Environmental conditions" refer to factors that affect astronomical observations, including both light conditions and weather conditions.

[0503] "Time and direction" refers to information indicating the time of day and direction in which an object to be observed is most easily visible during astronomical observations.

[0504] "Evaluation" refers to feedback that users provide to the system after observation, and this information contributes to improving the observation experience and the system itself.

[0505] This invention is a system for users to efficiently perform astronomical observations. Based on information entered by the user, this system provides optimal observation conditions and includes features to support observations, particularly for beginners.

[0506] Users utilize devices such as smartphones and personal computers. These devices access the system through a browser or a dedicated application. In this environment, users can input information such as the celestial object to be observed, the location of the observation site, the desired date and time, and the specifications of the observation equipment to be used.

[0507] The terminal transmits the entered information to the server via the internet. Upon receiving the information, the server uses an external recording device to obtain the light environment and weather conditions of the observation site. Commonly used external databases include APIs that provide weather information and light pollution map databases.

[0508] The server analyzes the acquired data and calculates the optimal time and direction for astronomical observation based on environmental conditions. This calculation utilizes astronomical computation libraries and other resources. Furthermore, the server uses a generative AI model to automatically generate instructions for operating observation equipment tailored to the user's knowledge level. This provides specific guidance to novice users on how to set up their telescopes and points to be aware of during observations.

[0509] The generated observation plan and operational instructions are delivered from the server to the terminal. The terminal visually displays this information to the user to support understanding and implementation. For example, information such as "The optimal time for observation is from 9 PM to 11 PM, and the observation target is located in the southeast direction" may be displayed.

[0510] Users perform observations according to the provided information. After the observations, they can send feedback to the server via their terminal. This feedback is reflected in the system's analysis model, contributing to more accurate observation planning and personalized operational guidance.

[0511] A possible example of a prompt message would be: "For astronomical observation, please tell me the best time and location to observe Saturn from Tokyo. I would like to observe it on November 3, 2023 at 8 PM, and I will be using telescope option B."

[0512] This system allows users to effectively enjoy astronomical observation even without advanced expertise, and the system is constantly being improved through continuous feedback.

[0513] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0514] Step 1:

[0515] The user inputs the celestial object to be observed, the observation location, the desired date and time, and the specifications of the observation equipment to be used, using the terminal's user interface. The information entered here serves as the basis for subsequent processing, determining the observation conditions.

[0516] Step 2:

[0517] The terminal sends user-entered information to the server via the HTTP protocol. Efficient data transfer is achieved by serializing the input data, converting it to a format suitable for the communication protocol, and sending it to the server.

[0518] Step 3:

[0519] The server analyzes the received observation data and acquires data on the light environment and meteorological conditions of the observation site via an external recording device. The input is the user's observation data, and the output is the latest environmental data of the observation site. An API call is made to receive data in JSON format.

[0520] Step 4:

[0521] The server analyzes the acquired environmental data and uses an astronomical computing library to calculate the optimal time and direction for observation. The input is light environment and meteorological data, and the output is optimal observation schedule information and direction. Here, the server performs time calculations to identify the time period when light pollution is minimized.

[0522] Step 5:

[0523] The server uses a generative AI model to automatically generate operating instructions for observation equipment for novice users. The inputs are the observation conditions and the user's skill level, and the output is the instruction content. Here, the generative AI model dynamically creates specific operating steps according to the observation conditions.

[0524] Step 6:

[0525] The server sends the generated observation plan and operational instructions to the terminal. Here, the data is formatted into a user-friendly format such as HTML or PDF. The input is observation information and instruction data, and the output is instruction information presented to the user.

[0526] Step 7:

[0527] Users conduct astronomical observations according to the observation plan and operating instructions displayed on the terminal. This section provides detailed instructions on how users specifically set up their observation equipment and proceed with their observations.

[0528] Step 8:

[0529] After completing their observations, users send feedback to the server via their terminal. The input is the observation experience and evaluation, and the output is feedback information for improvement. This allows the system's analysis model to be continuously updated, and improvements are made based on user feedback.

[0530] (Application Example 1)

[0531] 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."

[0532] Enjoying the process of observing phenomena often requires specialized knowledge and experience, which can be a significant hurdle, especially for beginners. Furthermore, it's difficult to create optimal conditions for observation, and results are frequently affected by changes in weather and environmental conditions. Additionally, there's a lack of methods to maximize the learning and educational benefits of observation, highlighting the need for personalized guidance tailored to each user.

[0533] 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.

[0534] In this invention, the server includes means for receiving instructions from the user and obtaining environmental and weather conditions from external sources using information about the evaluation site; means for calculating the optimal time and direction for observing phenomena based on the obtained conditions; means for automatically generating and providing instructions on how to operate the device and suggestions on how to take photographs to novice users; and means for providing personalized experience guides using information terminals. This reduces the technical burden on the user and makes it possible to provide a high-quality observation experience and learning effect.

[0535] A "user" refers to the entity that uses the system to observe phenomena.

[0536] An "evaluation point" refers to a specific geographical location where the phenomenon is observed.

[0537] "Environmental conditions" refer to ambient brightness and other properties that affect the visibility of the object being observed.

[0538] "Weather conditions" refer to the meteorological conditions at the time of observation, such as precipitation, cloud cover, and wind speed.

[0539] "External information sources" refer to external databases or sources that provide data on environmental and weather conditions.

[0540] "Phenomenon observation" refers to the act or process of observing a specific natural phenomenon.

[0541] "Timing and direction" refers to parameters that indicate the optimal date, time, and direction for observing the phenomenon.

[0542] "Apparatus" refers to observational instruments and equipment used to observe phenomena.

[0543] "Operating procedure instructions" refers to information that explains how to use the device.

[0544] "Photography method" refers to the procedures and techniques for taking photographs to record observations of phenomena.

[0545] "Automatic generation" refers to a process in which a system generates information based on statistical models or rules without requiring manual intervention.

[0546] An "information terminal" refers to an electronic device used by a user to receive information.

[0547] An "experience guide" refers to the guidance and support information provided to enhance the user's observation experience.

[0548] The system implementing this invention mainly consists of a server and a user information terminal. The following describes how each component functions.

[0549] The server first receives information sent by the user, including the evaluation location, the phenomenon to be observed, and the desired observation date and time. The server uses this information to obtain the relevant environmental and weather conditions from external sources. This process involves using an API (e.g., the OpenWeatherMap API) to retrieve weather data.

[0550] Next, the server uses an AI algorithm to calculate the optimal time and direction for observing the phenomenon, based on the acquired weather and environmental conditions. This uses a machine learning model based on TensorFlow. This model derives the most suitable date, time, and direction to minimize the effects of light pollution.

[0551] Furthermore, the server automatically generates operating instructions and shooting methods according to the user's skill level and delivers them to the user's information terminal. For beginners, the instructions are particularly concise and easy to understand. In this process, natural language processing using Python is employed to generate content tailored to the user.

[0552] The information terminal displays detailed observation plans and operating procedure instructions to the user. This includes visualized data and real-time advice. Furthermore, the experience guide function allows for the display of information about the observation target using AR technology. Integration with the Google Maps API assists in visualizing observation locations.

[0553] After conducting actual observations, users send feedback about their results and experiences to the system. This feedback is analyzed using a generative AI model and used to personalize future operating instructions and observation plans.

[0554] For example, if a user plans to observe Saturn at a specific location, the system will calculate the optimal observation time for that location and use Google Maps to show the direction from the user's current location. Furthermore, it can provide points to be aware of during observation and instructions on how to properly set up the camera, using natural language processing with Python. An example of a prompt would be, "Please tell me the best time and place to observe Saturn under conditions with minimal light pollution."

[0555] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0556] Step 1:

[0557] The user inputs the evaluation location, the phenomenon to be observed, and the desired observation date and time via an information terminal. These inputs are prepared as a dataset to be sent to the server. The server receives this dataset and holds it for processing in the next step.

[0558] Step 2:

[0559] The server uses the received information about the evaluation location to obtain environmental and weather conditions from an external source (e.g., the OpenWeatherMap API). The server sends an API request and receives light pollution and weather data as a response. Based on this data, observation conditions are constructed.

[0560] Step 3:

[0561] Based on the acquired environmental and weather conditions, the server uses an AI algorithm to calculate the optimal time and direction for observing the phenomenon. A model using TensorFlow estimates the required date, time, and direction. This output is compiled into a list as part of the observation plan.

[0562] Step 4:

[0563] The server generates operating instructions and shooting methods based on the user's skill level. Using natural language processing techniques with Python, prompts are provided to a generation AI model, which then generates appropriate explanations. These explanations are then incorporated into the overall observation plan.

[0564] Step 5:

[0565] The generated observation plan and explanation are delivered from the server to the information terminal. The terminal displays this information on the user interface and visualizes the guidance data using AR technology as needed. This allows the user to intuitively grasp the details of the observation.

[0566] Step 6:

[0567] After observation, the user enters feedback using an information terminal. This feedback data is sent to the server. The server stores this data and analyzes it using a generative AI model to personalize the next observation plan and explanation. This process ensures continuous improvement of the system.

[0568] 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.

[0569] This invention is a system designed to assist users performing astronomical observations. It includes functions to analyze user actions and emotional data, and to provide personalized operation tutorials and shooting suggestions. The specific operation of the system is described below.

[0570] First, the user inputs the celestial object they want to observe, their desired observation date and time, observation location, and the specifications of the telescope they will use into the terminal. The terminal receives this information and sends it to the server. In addition, the terminal uses a built-in emotion engine to recognize the user's emotional state in real time. This emotional data can be acquired through user interaction and biosensor data (e.g., voice tone, emotion analysis through facial recognition).

[0571] Based on the observation site information received from the user, the server retrieves relevant light pollution and weather condition data from an external database. Using this data, it calculates the optimal observation time and direction for the target celestial object and creates an observation plan.

[0572] The server further analyzes the user's emotional state as recognized by the emotion engine and generates an operation tutorial based on that. For example, if the user is showing anxiety or confusion, the tutorial will provide more detailed explanations and additional visual support. Conversely, if the user is showing enjoyment or interest, it can suggest challenging operations or experimental tasks.

[0573] The observation plan and operation tutorial generated in this way are delivered from the server to the terminal. The terminal displays the received information through the user interface. Specific examples include the date, time, and location of celestial objects, weather information, visuals regarding light pollution, and operation procedures and advice tailored to the user's emotional state.

[0574] After the observation period ends, users provide feedback through their devices. This feedback is analyzed by the server and used to improve the system's analysis model. Emotional data from the emotion engine is also accumulated, contributing to improved interaction accuracy and the provision of more personalized services in the future.

[0575] Thus, the present invention constructs a system that provides users with a comfortable and effective astronomical observation experience, and realizes a mechanism that can be applied to a wide range of users, from beginners to experienced observers.

[0576] The following describes the processing flow.

[0577] Step 1:

[0578] The user inputs the celestial object they want to observe, their desired date and time, observation location, and the specifications of the telescope they will use into the terminal. The terminal receives this information and sends it to the server. At the same time, the terminal activates an emotion engine and collects the user's emotion data.

[0579] Step 2:

[0580] Based on the observation location and astronomical information received from the user, the server accesses external light pollution and weather databases to obtain the light pollution level and weather conditions (temperature, humidity, and weather) for the relevant area.

[0581] Step 3:

[0582] The server analyzes the acquired data to determine the optimal observation timing and direction for the target celestial object. It then constructs an observation plan by referring to the celestial object's ephemeris data (celestial object position information).

[0583] Step 4:

[0584] The server customizes the user tutorial based on the user's emotions analyzed by the emotion engine. For example, if the user indicates stress, it adds supportive and detailed explanations and relaxation-promoting advice.

[0585] Step 5:

[0586] The server sends an optimized observation plan and a personalized operation tutorial to the terminal.

[0587] Step 6:

[0588] The terminal displays the transmitted observation plan and tutorial in its user interface. This includes a map of celestial body positions, observation conditions, and specific operating procedures and precautions.

[0589] Step 7:

[0590] Users conduct astronomical observations using the provided observation plan and tutorials as a guide. The emotion engine continues to monitor the user's emotions and adjusts interactions as needed.

[0591] Step 8:

[0592] After the observation period ends, users provide feedback through their devices, sharing their impressions and experiences. This feedback, including emotional data, is received by the server.

[0593] Step 9:

[0594] The server analyzes the collected feedback and sentiment data, updates the system's analysis model, and uses it as training data for the sentiment engine. This improves the service provided to users in the future.

[0595] (Example 2)

[0596] 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."

[0597] Conventional astronomical observation systems lacked detailed operational guidance for beginners and were inadequate in automatically generating observation plans based on observation conditions and environments. Furthermore, they did not incorporate user-centric interaction, making it difficult to provide an observation experience optimized for each individual.

[0598] 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.

[0599] In this invention, the server includes means for receiving information from the user and obtaining environmental and meteorological conditions from an external database using observation site data; means for calculating the optimal time and direction for astronomical observation based on the obtained environmental conditions; and means for recognizing the user's emotional state and automatically generating and providing telescope operation instructions and shooting methods accordingly. This makes it possible to provide observation plans and support optimized for each individual user and improve the astronomical observation experience.

[0600] "Means of receiving information from users" refers to the function by which the system acquires information such as observation targets, date and time, observation location, and equipment specifications entered by the user via a terminal.

[0601] "Means for obtaining environmental and meteorological conditions from an external database using data from observation sites" refers to a function that obtains light pollution, weather, and other environmental conditions for a designated observation point from an external database.

[0602] "Means for calculating the optimal time and direction for astronomical observation based on acquired environmental conditions" refers to a function that analyzes acquired environmental data to calculate the date, time, and direction at which the target celestial object can be best observed.

[0603] "A means of recognizing the user's emotional state and automatically generating and providing telescope operation guides and shooting methods accordingly" refers to a function that analyzes the user's emotions in real time and generates and provides customized operation guides and shooting advice tailored to that state.

[0604] "Means for distributing generated observation plans and operation manuals to user devices" refers to a function that sends the observation schedule and operation guide generated by the server to the user's terminal for display.

[0605] "A means of receiving user feedback after observations are completed and improving the system's analysis model" refers to a function that receives user feedback after observations are completed and incorporates it into the analysis model to improve the system.

[0606] This invention is a system for supporting astronomical observation, aiming to streamline user operation and provide a personalized observation experience. This system automatically generates an optimal observation plan and operation tutorial based on user input information. Specific embodiments of this invention are described below.

[0607] The user inputs details of the celestial object to be observed, the desired observation date and time, the observation location, and the telescope to be used into the terminal. The terminal is equipped with an interface for managing the input information, which enhances user convenience.

[0608] This device uses a built-in emotion recognition engine to evaluate the user's emotional state in real time during input. This engine understands the user's state by analyzing voice tone and using facial recognition technology. The data collected by the device is sent to the server in an encoded form.

[0609] The server analyzes the acquired data and retrieves light pollution and weather data relevant to the observation site from an external database. This database includes information sources such as weather forecast APIs and light pollution maps. The server uses this data to calculate the optimal time and direction for observation.

[0610] Furthermore, the server utilizes a generative AI model to create personalized tutorials based on the user's emotional state. For example, if a user shows confusion, the tutorial will include detailed step-by-step instructions and image-based support information.

[0611] The generated observation plan and tutorial are delivered from the server to the terminal. The terminal receives them and displays them on the user interface. For example, if a user enters the prompt "I want to know what celestial objects will be visible in the direction of Mt. Fuji tonight. Since it's a new moon, the stars should be clearly visible," the system analyzes this and provides an appropriate observation plan and tutorial.

[0612] After the observation is complete, the user enters feedback about the observation experience via a terminal. This feedback is analyzed on the server and used to adjust the system's analysis model and improve the individual user experience. The accumulated data contributes to improving the accuracy of future observations.

[0613] Thus, this system allows users to enjoy a comfortable and efficient astronomical observation experience. This invention caters to a wide range of users, from beginners to experienced observers, and provides services that meet their specific needs.

[0614] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0615] Step 1:

[0616] The user inputs the celestial object they wish to observe, their desired observation date and time, observation location, and the specifications of the telescope they will use into the terminal. This input information is used as basic data for creating the observation plan. Specifically, the user fills in the information into a form in a dedicated application on the terminal, and this registers the details in the user interface.

[0617] Step 2:

[0618] The device acquires the user's emotional state in real time, along with the input information, using its built-in emotion recognition engine. Specifically, it utilizes a voice tone sensor and a facial recognition camera to extract emotional data from the user's voice tone and facial expressions. After this data is analyzed, it is ready to be sent to the server.

[0619] Step 3:

[0620] The terminal sends collected user input information and emotional state data to the server. This data is encrypted using a communication protocol and securely transferred to the server. The output here is a comprehensive user dataset for the server to use for analysis.

[0621] Step 4:

[0622] The server uses the received observation data to access an external database and retrieve light pollution data and weather conditions for the relevant observation site. This information is obtained via an API and serves as input data necessary for evaluating observation conditions. Using this data, the optimal time and direction for observation are calculated.

[0623] Step 5:

[0624] The server utilizes a generative AI model to automatically generate operation tutorials based on user sentiment data. Specifically, if the user expresses anxiety, it creates detailed operation instructions; if they express enjoyment, it offers challenging suggestions. The final output is a customized operation guide.

[0625] Step 6:

[0626] The server delivers the created observation plan and operation tutorial to the terminal. The terminal receives this and displays it on the user interface, providing information to the user. Specifically, the screen displays the optimal date, time, direction, and operating procedures for astronomical observation.

[0627] Step 7:

[0628] After the observation is complete, the user enters feedback on the observation via a terminal. This feedback is sent from the terminal to the server and used to improve the system's analysis model. The accumulated data will contribute to future personalized suggestions and accuracy improvements.

[0629] (Application Example 2)

[0630] 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."

[0631] Conventional astronomical observation systems have difficulty dynamically changing content to suit users' interests and skill levels, and also have limited means of sharing observation experiences with others in real time. Therefore, there is a need for a system that can improve the quality of the observation experience and accommodate a wider range of users.

[0632] 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.

[0633] In this invention, the server includes means for receiving input from the user and obtaining light pollution and weather conditions from an external database using information about the observation site; means for calculating the optimal timing and direction for astronomical observation based on the obtained observation conditions; means for sharing the observation status in real time via a communication network; means for analyzing the user's emotional data and dynamically changing the content during observation; means for distributing the generated observation plan and operation tutorial to the user's information processing device; and means for receiving feedback from the user and improving the system's analysis model. This enables the provision of personalized observation guides in real time, enriching the observation experience and allowing for sharing among users.

[0634] A "user" is someone who inputs data to use the system for astronomical observation.

[0635] "Observation site" refers to the location where the user intends to conduct astronomical observations, and includes information such as its geographical location and surrounding environmental conditions.

[0636] "Light pollution" refers to artificial light that interferes with astronomical observations at observation sites and is a major factor that significantly affects observation conditions.

[0637] "Weather conditions" refers to meteorological information that affects astronomical observations, such as the weather at the observation site, wind speed, and humidity.

[0638] An "external database" is an external information storage device that the system accesses to obtain information about light pollution and weather conditions.

[0639] "Observation conditions" is a general term for information regarding the environment, time, and location necessary for astronomical observation, including light pollution and weather conditions.

[0640] "Means of sharing in real time" refers to methods for instantly sharing observations with other users via a communication network.

[0641] "Emotional data" refers to data that indicates the user's psychological state, and is information obtained through voice tone and facial expression analysis.

[0642] "Dynamically changing content" refers to the act of optimizing the observation guides and information provided in real time based on user sentiment data.

[0643] An "information processing device," also known as a user terminal, is an electronic device that has the function of receiving and displaying observation plans and operation tutorials.

[0644] "Feedback" refers to information about impressions and suggestions for improvement provided by users after completing their observation experience, and contributes to improving the system's analysis model.

[0645] This invention provides a system for making astronomical observation a personalized and enriching experience. The system optimizes observation conditions based on user input and provides observation guidance and experience based on that information. The interactive interaction between the server, terminal, and user enhances the effectiveness of the observation.

[0646] The server receives information about the observation location and date / time entered by the user, accesses external light pollution and weather condition databases, and collects this data. Based on the collected data, it calculates the optimal observation timing and direction for astronomical observation. Based on the calculation results, it generates an observation plan and provides it to the user.

[0647] The device receives observation plans and operation tutorials, which are displayed via a user interface. During this process, the device uses voice tone and facial recognition technology to collect user emotion data. Specifically, it utilizes an emotion recognition API (e.g., Microsoft Azure Emotion API) to evaluate the user's psychological state.

[0648] Users can share their observations with other users in real time via their devices. To achieve this, real-time streaming technologies (e.g., WebRTC) are used to share the observation experience with others over a communication network. Through this sharing function, astronomical observation is expanded beyond a personal experience into shareable content.

[0649] For example, when observing the Perseid meteor shower with family in the summer, the user might prompt, "Generate a guide for observing the Perseid meteor shower." Based on the proposed observation plan, the system uses the user's emotional data and real-time feedback to adjust the guidance during the observation, enhancing the observation experience.

[0650] This system will make astronomical observation more accessible and provide personalized services to individual users. User feedback will be used to improve the system and further enhance the quality of the observation experience in the future.

[0651] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0652] Step 1:

[0653] The user enters information into the terminal, including the celestial object they wish to observe, the date and time, the observation location, and the optical instruments they will use. This input data is sent to the server. Based on this information, the server accesses an external database to obtain light pollution and weather conditions, and collects the necessary environmental data.

[0654] Step 2:

[0655] The server uses acquired weather data and light pollution information to calculate the optimal observation time and direction for astronomical observation. Known models and algorithms from the database are applied to the calculation. The calculation results are generated as an observation plan and sent to the terminal.

[0656] Step 3:

[0657] The terminal displays the observation plan received from the server through the user interface. The terminal analyzes the user's voice tone and facial expressions using an emotion recognition API through interaction with the user and collects the user's emotional data.

[0658] Step 4:

[0659] The server receives emotional data from the terminal. The analyzed emotional data is used to adjust the guide content provided during observation. If the user shows signs of anxiety, dynamic content changes are made, such as providing detailed explanations or visual support.

[0660] Step 5:

[0661] Users share their observation experience with other users by utilizing real-time streaming technology via their devices during observation. In this process, the devices encode video data and transmit it over the network.

[0662] Step 6:

[0663] Once the observation is complete, the user sends feedback to the server via their device. The server analyzes the feedback and stores it in a database for future system improvements. Emotional data is also stored in the same way and used to improve personalized services.

[0664] 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.

[0665] 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.

[0666] 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.

[0667] [Fourth Embodiment]

[0668] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0669] 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.

[0670] 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).

[0671] 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.

[0672] 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.

[0673] 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).

[0674] 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.

[0675] 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.

[0676] 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.

[0677] 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.

[0678] 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.

[0679] 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.

[0680] 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".

[0681] This invention is designed as a system to support astronomical observation and is equipped with various functions to improve user convenience. The following describes in detail how the system operates.

[0682] The first step for the user is to input information, including specifying the object to observe and setting the observation location. The user enters the desired celestial object (e.g., Saturn), desired observation date and time, and the specifications of the telescope to be used into the system. The terminal receives this information and sends it to the server.

[0683] Based on the information received from the user, the server uses the location information of the observation site to retrieve light pollution and weather conditions from an external database. This prepares the server to determine the optimal conditions for observation. For example, by referring to a light pollution map of the observation area and the current weather conditions, it can identify the time when visibility is as good as possible.

[0684] Next, the server analyzes the acquired observation conditions and consults an astronomical database for the target celestial object. This allows it to calculate the optimal timing and direction for observation and automatically generate an observation schedule. For example, when observing Saturn, it determines the time and direction when Saturn is highest in the sky and light pollution is minimal.

[0685] For beginner users, the server generates even more detailed operation tutorials. These include instructions on how to set up the telescope, points to be aware of during observation, how to track celestial objects, and camera setup procedures. This makes it easy for even beginners to prepare for astronomical observation.

[0686] The server then delivers the generated observation plan and accompanying operation tutorial to the terminal. The terminal displays the received information on its user interface. For example, it may show a visualized light pollution map, estimated celestial object positions over time, and detailed operation guides.

[0687] Users perform observations according to the provided observation plan and tutorial. After the observation, users can send feedback to the server. This feedback is reflected in the system's analysis model and used for future improvements. Specifically, this includes improving the tutorials provided based on user experience and improving the accuracy of the observation plan.

[0688] This system efficiently and effectively supports astronomical observation, making it possible for beginners in particular to enjoy observation without requiring a high level of expertise. With such preparation and support, users can easily conduct high-quality astronomical observations.

[0689] The following describes the processing flow.

[0690] Step 1:

[0691] The user enters the celestial object they want to observe, their desired date and time, observation location, and the specifications of the telescope they will use into the terminal. The terminal receives this information and sends it to the server.

[0692] Step 2:

[0693] Based on the location information of the observation site received from the user, the server accesses an external database to obtain data on light pollution levels and weather conditions (temperature, humidity, weather, etc.).

[0694] Step 3:

[0695] The server uses the input data on the object to be observed to calculate the most suitable date, time, and direction for observation. In doing so, it refers to a database of celestial body positions to determine the appropriate time slot.

[0696] Step 4:

[0697] The server generates user tutorials for beginners, including instructions on setting up the telescope, selecting shooting modes, and tracking celestial objects.

[0698] Step 5:

[0699] The server sends the optimized observation plan and generated operation tutorial to the terminal.

[0700] Step 6:

[0701] The terminal displays the received observation plan and tutorial in its user interface, allowing the user to proceed with observation preparations.

[0702] Step 7:

[0703] Users conduct actual observations according to the provided information and send their results and impressions as feedback to the server via their device.

[0704] Step 8:

[0705] The server analyzes the feedback received from users and uses it to improve system performance and refine the next observation plan.

[0706] (Example 1)

[0707] 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".

[0708] For beginners conducting astronomical observations, analyzing observation conditions, determining the optimal timing, and operating observation equipment can be difficult, making efficient observation challenging. Furthermore, there is a need to incorporate observation experience into the system and provide observation guidance tailored to individual users. This means users can obtain a high-quality observation experience, while the system must be continuously improved using individual feedback.

[0709] 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.

[0710] This invention includes a server that receives information from the user and uses location information to acquire light environment and weather conditions from an external recording device; a server that calculates the optimal time and direction for astronomical observation based on the acquired environmental conditions; and a server that automatically generates and provides instructions for operating observation equipment and imaging techniques for beginners. This makes it easy for beginners to perform astronomical observations, and the system can be improved based on user feedback to provide more personalized instructions and plans.

[0711] A "user device" is a terminal used by a user to access a system and input information, and includes devices such as personal computers and smartphones.

[0712] A "server" is a computing device that receives information sent from users, acquires and analyzes optical environment and weather conditions, and generates and provides operational guidance and observation plans.

[0713] An "external recording device" refers to an external database or cloud service that provides data on the light environment and weather conditions necessary for astronomical observation.

[0714] "Light environment" refers to data indicating the level of light pollution at the observation site, and is an environmental condition that affects the clarity of visibility during nighttime observations.

[0715] "Meteorological conditions" refer to information about weather and atmospheric conditions during astronomical observations, and are factors that affect the accuracy of observations.

[0716] "Observation equipment" refers to instruments used to observe celestial bodies, including telescopes and cameras.

[0717] "Operational guidance" refers to specific instructions and guides provided to users regarding the initial setup and usage of observation equipment, as well as precautions to take during observation.

[0718] "Environmental conditions" refer to factors that affect astronomical observations, including both light conditions and weather conditions.

[0719] "Time and direction" refers to information indicating the time of day and direction in which an object to be observed is most easily visible during astronomical observations.

[0720] "Evaluation" refers to feedback that users provide to the system after observation, and this information contributes to improving the observation experience and the system itself.

[0721] This invention is a system for users to efficiently perform astronomical observations. Based on information entered by the user, this system provides optimal observation conditions and includes features to support observations, particularly for beginners.

[0722] Users utilize devices such as smartphones and personal computers. These devices access the system through a browser or a dedicated application. In this environment, users can input information such as the celestial object to be observed, the location of the observation site, the desired date and time, and the specifications of the observation equipment to be used.

[0723] The terminal transmits the entered information to the server via the internet. Upon receiving the information, the server uses an external recording device to obtain the light environment and weather conditions of the observation site. Commonly used external databases include APIs that provide weather information and light pollution map databases.

[0724] The server analyzes the acquired data and calculates the optimal time and direction for astronomical observation based on environmental conditions. This calculation utilizes astronomical computation libraries and other resources. Furthermore, the server uses a generative AI model to automatically generate instructions for operating observation equipment tailored to the user's knowledge level. This provides specific guidance to novice users on how to set up their telescopes and points to be aware of during observations.

[0725] The generated observation plan and operational instructions are delivered from the server to the terminal. The terminal visually displays this information to the user to support understanding and implementation. For example, information such as "The optimal time for observation is from 9 PM to 11 PM, and the observation target is located in the southeast direction" may be displayed.

[0726] Users perform observations according to the provided information. After the observations, they can send feedback to the server via their terminal. This feedback is reflected in the system's analysis model, contributing to more accurate observation planning and personalized operational guidance.

[0727] A possible example of a prompt message would be: "For astronomical observation, please tell me the best time and location to observe Saturn from Tokyo. I would like to observe it on November 3, 2023 at 8 PM, and I will be using telescope option B."

[0728] This system allows users to effectively enjoy astronomical observation even without advanced expertise, and the system is constantly being improved through continuous feedback.

[0729] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0730] Step 1:

[0731] The user inputs the celestial object to be observed, the observation location, the desired date and time, and the specifications of the observation equipment to be used, using the terminal's user interface. The information entered here serves as the basis for subsequent processing, determining the observation conditions.

[0732] Step 2:

[0733] The terminal sends user-entered information to the server via the HTTP protocol. Efficient data transfer is achieved by serializing the input data, converting it to a format suitable for the communication protocol, and sending it to the server.

[0734] Step 3:

[0735] The server analyzes the received observation data and acquires data on the light environment and meteorological conditions of the observation site via an external recording device. The input is the user's observation data, and the output is the latest environmental data of the observation site. An API call is made to receive data in JSON format.

[0736] Step 4:

[0737] The server analyzes the acquired environmental data and uses an astronomical computing library to calculate the optimal time and direction for observation. The input is light environment and meteorological data, and the output is optimal observation schedule information and direction. Here, the server performs time calculations to identify the time period when light pollution is minimized.

[0738] Step 5:

[0739] The server uses a generative AI model to automatically generate operating instructions for observation equipment for novice users. The inputs are the observation conditions and the user's skill level, and the output is the instruction content. Here, the generative AI model dynamically creates specific operating steps according to the observation conditions.

[0740] Step 6:

[0741] The server sends the generated observation plan and operational instructions to the terminal. Here, the data is formatted into a user-friendly format such as HTML or PDF. The input is observation information and instruction data, and the output is instruction information presented to the user.

[0742] Step 7:

[0743] Users conduct astronomical observations according to the observation plan and operating instructions displayed on the terminal. This section provides detailed instructions on how users specifically set up their observation equipment and proceed with their observations.

[0744] Step 8:

[0745] After completing their observations, users send feedback to the server via their terminal. The input is the observation experience and evaluation, and the output is feedback information for improvement. This allows the system's analysis model to be continuously updated, and improvements are made based on user feedback.

[0746] (Application Example 1)

[0747] 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".

[0748] Enjoying the process of observing phenomena often requires specialized knowledge and experience, which can be a significant hurdle, especially for beginners. Furthermore, it's difficult to create optimal conditions for observation, and results are frequently affected by changes in weather and environmental conditions. Additionally, there's a lack of methods to maximize the learning and educational benefits of observation, highlighting the need for personalized guidance tailored to each user.

[0749] 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.

[0750] In this invention, the server includes means for receiving instructions from the user and obtaining environmental and weather conditions from external sources using information about the evaluation site; means for calculating the optimal time and direction for observing phenomena based on the obtained conditions; means for automatically generating and providing instructions on how to operate the device and suggestions on how to take photographs to novice users; and means for providing personalized experience guides using information terminals. This reduces the technical burden on the user and makes it possible to provide a high-quality observation experience and learning effect.

[0751] A "user" refers to the entity that uses the system to observe phenomena.

[0752] An "evaluation point" refers to a specific geographical location where the phenomenon is observed.

[0753] "Environmental conditions" refer to ambient brightness and other properties that affect the visibility of the object being observed.

[0754] "Weather conditions" refer to the meteorological conditions at the time of observation, such as precipitation, cloud cover, and wind speed.

[0755] "External information sources" refer to external databases or sources that provide data on environmental and weather conditions.

[0756] "Phenomenon observation" refers to the act or process of observing a specific natural phenomenon.

[0757] "Timing and direction" refers to parameters that indicate the optimal date, time, and direction for observing the phenomenon.

[0758] "Apparatus" refers to observational instruments and equipment used to observe phenomena.

[0759] "Operating procedure instructions" refers to information that explains how to use the device.

[0760] "Photography method" refers to the procedures and techniques for taking photographs to record observations of phenomena.

[0761] "Automatic generation" refers to a process in which a system generates information based on statistical models or rules without requiring manual intervention.

[0762] An "information terminal" refers to an electronic device used by a user to receive information.

[0763] An "experience guide" refers to the guidance and support information provided to enhance the user's observation experience.

[0764] The system implementing this invention mainly consists of a server and a user information terminal. The following describes how each component functions.

[0765] The server first receives information sent by the user, including the evaluation location, the phenomenon to be observed, and the desired observation date and time. The server uses this information to obtain the relevant environmental and weather conditions from external sources. This process involves using an API (e.g., the OpenWeatherMap API) to retrieve weather data.

[0766] Next, the server uses an AI algorithm to calculate the optimal time and direction for observing the phenomenon, based on the acquired weather and environmental conditions. This uses a machine learning model based on TensorFlow. This model derives the most suitable date, time, and direction to minimize the effects of light pollution.

[0767] Furthermore, the server automatically generates operating instructions and shooting methods according to the user's skill level and delivers them to the user's information terminal. For beginners, the instructions are particularly concise and easy to understand. In this process, natural language processing using Python is employed to generate content tailored to the user.

[0768] The information terminal displays detailed observation plans and operating procedure instructions to the user. This includes visualized data and real-time advice. Furthermore, the experience guide function allows for the display of information about the observation target using AR technology. Integration with the Google Maps API assists in visualizing observation locations.

[0769] After conducting actual observations, users send feedback about their results and experiences to the system. This feedback is analyzed using a generative AI model and used to personalize future operating instructions and observation plans.

[0770] For example, if a user plans to observe Saturn at a specific location, the system will calculate the optimal observation time for that location and use Google Maps to show the direction from the user's current location. Furthermore, it can provide points to be aware of during observation and instructions on how to properly set up the camera, using natural language processing with Python. An example of a prompt would be, "Please tell me the best time and place to observe Saturn under conditions with minimal light pollution."

[0771] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0772] Step 1:

[0773] The user inputs the evaluation location, the phenomenon to be observed, and the desired observation date and time via an information terminal. These inputs are prepared as a dataset to be sent to the server. The server receives this dataset and holds it for processing in the next step.

[0774] Step 2:

[0775] The server uses the received information about the evaluation location to obtain environmental and weather conditions from an external source (e.g., the OpenWeatherMap API). The server sends an API request and receives light pollution and weather data as a response. Based on this data, observation conditions are constructed.

[0776] Step 3:

[0777] Based on the acquired environmental and weather conditions, the server uses an AI algorithm to calculate the optimal time and direction for observing the phenomenon. A model using TensorFlow estimates the required date, time, and direction. This output is compiled into a list as part of the observation plan.

[0778] Step 4:

[0779] The server generates operating instructions and shooting methods based on the user's skill level. Using natural language processing techniques with Python, prompts are provided to a generation AI model, which then generates appropriate explanations. These explanations are then incorporated into the overall observation plan.

[0780] Step 5:

[0781] The generated observation plan and explanation are delivered from the server to the information terminal. The terminal displays this information on the user interface and visualizes the guidance data using AR technology as needed. This allows the user to intuitively grasp the details of the observation.

[0782] Step 6:

[0783] After observation, the user enters feedback using an information terminal. This feedback data is sent to the server. The server stores this data and analyzes it using a generative AI model to personalize the next observation plan and explanation. This process ensures continuous improvement of the system.

[0784] 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.

[0785] This invention is a system designed to assist users performing astronomical observations. It includes functions to analyze user actions and emotional data, and to provide personalized operation tutorials and shooting suggestions. The specific operation of the system is described below.

[0786] First, the user inputs the celestial object they want to observe, their desired observation date and time, observation location, and the specifications of the telescope they will use into the terminal. The terminal receives this information and sends it to the server. In addition, the terminal uses a built-in emotion engine to recognize the user's emotional state in real time. This emotional data can be acquired through user interaction and biosensor data (e.g., voice tone, emotion analysis through facial recognition).

[0787] Based on the observation site information received from the user, the server retrieves relevant light pollution and weather condition data from an external database. Using this data, it calculates the optimal observation time and direction for the target celestial object and creates an observation plan.

[0788] The server further analyzes the user's emotional state as recognized by the emotion engine and generates an operation tutorial based on that. For example, if the user is showing anxiety or confusion, the tutorial will provide more detailed explanations and additional visual support. Conversely, if the user is showing enjoyment or interest, it can suggest challenging operations or experimental tasks.

[0789] The observation plan and operation tutorial generated in this way are delivered from the server to the terminal. The terminal displays the received information through the user interface. Specific examples include the date, time, and location of celestial objects, weather information, visuals regarding light pollution, and operation procedures and advice tailored to the user's emotional state.

[0790] After the observation period ends, users provide feedback through their devices. This feedback is analyzed by the server and used to improve the system's analysis model. Emotional data from the emotion engine is also accumulated, contributing to improved interaction accuracy and the provision of more personalized services in the future.

[0791] Thus, the present invention constructs a system that provides users with a comfortable and effective astronomical observation experience, and realizes a mechanism that can be applied to a wide range of users, from beginners to experienced observers.

[0792] The following describes the processing flow.

[0793] Step 1:

[0794] The user inputs the celestial object they want to observe, their desired date and time, observation location, and the specifications of the telescope they will use into the terminal. The terminal receives this information and sends it to the server. At the same time, the terminal activates an emotion engine and collects the user's emotion data.

[0795] Step 2:

[0796] Based on the observation location and astronomical information received from the user, the server accesses external light pollution and weather databases to obtain the light pollution level and weather conditions (temperature, humidity, and weather) for the relevant area.

[0797] Step 3:

[0798] The server analyzes the acquired data to determine the optimal observation timing and direction for the target celestial object. It then constructs an observation plan by referring to the celestial object's ephemeris data (celestial object position information).

[0799] Step 4:

[0800] The server customizes the user tutorial based on the user's emotions analyzed by the emotion engine. For example, if the user indicates stress, it adds supportive and detailed explanations and relaxation-promoting advice.

[0801] Step 5:

[0802] The server sends an optimized observation plan and a personalized operation tutorial to the terminal.

[0803] Step 6:

[0804] The terminal displays the transmitted observation plan and tutorial in its user interface. This includes a map of celestial body positions, observation conditions, and specific operating procedures and precautions.

[0805] Step 7:

[0806] Users conduct astronomical observations using the provided observation plan and tutorials as a guide. The emotion engine continues to monitor the user's emotions and adjusts interactions as needed.

[0807] Step 8:

[0808] After the observation period ends, users provide feedback through their devices, sharing their impressions and experiences. This feedback, including emotional data, is received by the server.

[0809] Step 9:

[0810] The server analyzes the collected feedback and sentiment data, updates the system's analysis model, and uses it as training data for the sentiment engine. This improves the service provided to users in the future.

[0811] (Example 2)

[0812] 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".

[0813] Conventional astronomical observation systems lacked detailed operational guidance for beginners and were inadequate in automatically generating observation plans based on observation conditions and environments. Furthermore, they did not incorporate user-centric interaction, making it difficult to provide an observation experience optimized for each individual.

[0814] 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.

[0815] In this invention, the server includes means for receiving information from the user and obtaining environmental and meteorological conditions from an external database using observation site data; means for calculating the optimal time and direction for astronomical observation based on the obtained environmental conditions; and means for recognizing the user's emotional state and automatically generating and providing telescope operation instructions and shooting methods accordingly. This makes it possible to provide observation plans and support optimized for each individual user and improve the astronomical observation experience.

[0816] "Means of receiving information from users" refers to the function by which the system acquires information such as observation targets, date and time, observation location, and equipment specifications entered by the user via a terminal.

[0817] "Means for obtaining environmental and meteorological conditions from an external database using data from observation sites" refers to a function that obtains light pollution, weather, and other environmental conditions for a designated observation point from an external database.

[0818] "Means for calculating the optimal time and direction for astronomical observation based on acquired environmental conditions" refers to a function that analyzes acquired environmental data to calculate the date, time, and direction at which the target celestial object can be best observed.

[0819] "A means of recognizing the user's emotional state and automatically generating and providing telescope operation guides and shooting methods accordingly" refers to a function that analyzes the user's emotions in real time and generates and provides customized operation guides and shooting advice tailored to that state.

[0820] "Means for distributing generated observation plans and operation manuals to user devices" refers to a function that sends the observation schedule and operation guide generated by the server to the user's terminal for display.

[0821] "A means of receiving user feedback after observations are completed and improving the system's analysis model" refers to a function that receives user feedback after observations are completed and incorporates it into the analysis model to improve the system.

[0822] This invention is a system for supporting astronomical observation, aiming to streamline user operation and provide a personalized observation experience. This system automatically generates an optimal observation plan and operation tutorial based on user input information. Specific embodiments of this invention are described below.

[0823] The user inputs details of the celestial object to be observed, the desired observation date and time, the observation location, and the telescope to be used into the terminal. The terminal is equipped with an interface for managing the input information, which enhances user convenience.

[0824] This device uses a built-in emotion recognition engine to evaluate the user's emotional state in real time during input. This engine understands the user's state by analyzing voice tone and using facial recognition technology. The data collected by the device is sent to the server in an encoded form.

[0825] The server analyzes the acquired data and retrieves light pollution and weather data relevant to the observation site from an external database. This database includes information sources such as weather forecast APIs and light pollution maps. The server uses this data to calculate the optimal time and direction for observation.

[0826] Furthermore, the server utilizes a generative AI model to create personalized tutorials based on the user's emotional state. For example, if a user shows confusion, the tutorial will include detailed step-by-step instructions and image-based support information.

[0827] The generated observation plan and tutorial are delivered from the server to the terminal. The terminal receives them and displays them on the user interface. For example, if a user enters the prompt "I want to know what celestial objects will be visible in the direction of Mt. Fuji tonight. Since it's a new moon, the stars should be clearly visible," the system analyzes this and provides an appropriate observation plan and tutorial.

[0828] After the observation is complete, the user enters feedback about the observation experience via a terminal. This feedback is analyzed on the server and used to adjust the system's analysis model and improve the individual user experience. The accumulated data contributes to improving the accuracy of future observations.

[0829] Thus, this system allows users to enjoy a comfortable and efficient astronomical observation experience. This invention caters to a wide range of users, from beginners to experienced observers, and provides services that meet their specific needs.

[0830] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0831] Step 1:

[0832] The user inputs the celestial object they wish to observe, their desired observation date and time, observation location, and the specifications of the telescope they will use into the terminal. This input information is used as basic data for creating the observation plan. Specifically, the user fills in the information into a form in a dedicated application on the terminal, and this registers the details in the user interface.

[0833] Step 2:

[0834] The device acquires the user's emotional state in real time, along with the input information, using its built-in emotion recognition engine. Specifically, it utilizes a voice tone sensor and a facial recognition camera to extract emotional data from the user's voice tone and facial expressions. After this data is analyzed, it is ready to be sent to the server.

[0835] Step 3:

[0836] The terminal sends collected user input information and emotional state data to the server. This data is encrypted using a communication protocol and securely transferred to the server. The output here is a comprehensive user dataset for the server to use for analysis.

[0837] Step 4:

[0838] The server uses the received observation data to access an external database and retrieve light pollution data and weather conditions for the relevant observation site. This information is obtained via an API and serves as input data necessary for evaluating observation conditions. Using this data, the optimal time and direction for observation are calculated.

[0839] Step 5:

[0840] The server utilizes a generative AI model to automatically generate operation tutorials based on user sentiment data. Specifically, if the user expresses anxiety, it creates detailed operation instructions; if they express enjoyment, it offers challenging suggestions. The final output is a customized operation guide.

[0841] Step 6:

[0842] The server delivers the created observation plan and operation tutorial to the terminal. The terminal receives this and displays it on the user interface, providing information to the user. Specifically, the screen displays the optimal date, time, direction, and operating procedures for astronomical observation.

[0843] Step 7:

[0844] After the observation is complete, the user enters feedback on the observation via a terminal. This feedback is sent from the terminal to the server and used to improve the system's analysis model. The accumulated data will contribute to future personalized suggestions and accuracy improvements.

[0845] (Application Example 2)

[0846] 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".

[0847] Conventional astronomical observation systems have difficulty dynamically changing content to suit users' interests and skill levels, and also have limited means of sharing observation experiences with others in real time. Therefore, there is a need for a system that can improve the quality of the observation experience and accommodate a wider range of users.

[0848] 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.

[0849] In this invention, the server includes means for receiving input from the user and obtaining light pollution and weather conditions from an external database using information about the observation site; means for calculating the optimal timing and direction for astronomical observation based on the obtained observation conditions; means for sharing the observation status in real time via a communication network; means for analyzing the user's emotional data and dynamically changing the content during observation; means for distributing the generated observation plan and operation tutorial to the user's information processing device; and means for receiving feedback from the user and improving the system's analysis model. This enables the provision of personalized observation guides in real time, enriching the observation experience and allowing for sharing among users.

[0850] A "user" is someone who inputs data to use the system for astronomical observation.

[0851] "Observation site" refers to the location where the user intends to conduct astronomical observations, and includes information such as its geographical location and surrounding environmental conditions.

[0852] "Light pollution" refers to artificial light that interferes with astronomical observations at observation sites and is a major factor that significantly affects observation conditions.

[0853] "Weather conditions" refers to meteorological information that affects astronomical observations, such as the weather at the observation site, wind speed, and humidity.

[0854] An "external database" is an external information storage device that the system accesses to obtain information about light pollution and weather conditions.

[0855] "Observation conditions" is a general term for information regarding the environment, time, and location necessary for astronomical observation, including light pollution and weather conditions.

[0856] "Means of sharing in real time" refers to methods for instantly sharing observations with other users via a communication network.

[0857] "Emotional data" refers to data that indicates the user's psychological state, and is information obtained through voice tone and facial expression analysis.

[0858] "Dynamically changing content" refers to the act of optimizing the observation guides and information provided in real time based on user sentiment data.

[0859] An "information processing device," also known as a user terminal, is an electronic device that has the function of receiving and displaying observation plans and operation tutorials.

[0860] "Feedback" refers to information about impressions and suggestions for improvement provided by users after completing their observation experience, and contributes to improving the system's analysis model.

[0861] This invention provides a system for making astronomical observation a personalized and enriching experience. The system optimizes observation conditions based on user input and provides observation guidance and experience based on that information. The interactive interaction between the server, terminal, and user enhances the effectiveness of the observation.

[0862] The server receives information about the observation location and date / time entered by the user, accesses external light pollution and weather condition databases, and collects this data. Based on the collected data, it calculates the optimal observation timing and direction for astronomical observation. Based on the calculation results, it generates an observation plan and provides it to the user.

[0863] The device receives observation plans and operation tutorials, which are displayed via a user interface. During this process, the device uses voice tone and facial recognition technology to collect user emotion data. Specifically, it utilizes an emotion recognition API (e.g., Microsoft Azure Emotion API) to evaluate the user's psychological state.

[0864] Users can share their observations with other users in real time via their devices. To achieve this, real-time streaming technologies (e.g., WebRTC) are used to share the observation experience with others over a communication network. Through this sharing function, astronomical observation is expanded beyond a personal experience into shareable content.

[0865] For example, when observing the Perseid meteor shower with family in the summer, the user might prompt, "Generate a guide for observing the Perseid meteor shower." Based on the proposed observation plan, the system uses the user's emotional data and real-time feedback to adjust the guidance during the observation, enhancing the observation experience.

[0866] This system will make astronomical observation more accessible and provide personalized services to individual users. User feedback will be used to improve the system and further enhance the quality of the observation experience in the future.

[0867] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0868] Step 1:

[0869] The user enters information into the terminal, including the celestial object they wish to observe, the date and time, the observation location, and the optical instruments they will use. This input data is sent to the server. Based on this information, the server accesses an external database to obtain light pollution and weather conditions, and collects the necessary environmental data.

[0870] Step 2:

[0871] The server uses acquired weather data and light pollution information to calculate the optimal observation time and direction for astronomical observation. Known models and algorithms from the database are applied to the calculation. The calculation results are generated as an observation plan and sent to the terminal.

[0872] Step 3:

[0873] The terminal displays the observation plan received from the server through the user interface. The terminal analyzes the user's voice tone and facial expressions using an emotion recognition API through interaction with the user and collects the user's emotional data.

[0874] Step 4:

[0875] The server receives emotional data from the terminal. The analyzed emotional data is used to adjust the guide content provided during observation. If the user shows signs of anxiety, dynamic content changes are made, such as providing detailed explanations or visual support.

[0876] Step 5:

[0877] Users share their observation experience with other users by utilizing real-time streaming technology via their devices during observation. In this process, the devices encode video data and transmit it over the network.

[0878] Step 6:

[0879] Once the observation is complete, the user sends feedback to the server via their device. The server analyzes the feedback and stores it in a database for future system improvements. Emotional data is also stored in the same way and used to improve personalized services.

[0880] 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.

[0881] 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.

[0882] 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.

[0883] 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.

[0884] 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.

[0885] 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.

[0886] 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.

[0887] 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.

[0888] 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."

[0889] 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.

[0890] 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.

[0891] 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.

[0892] 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.

[0893] 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.

[0894] 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.

[0895] 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.

[0896] 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.

[0897] 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.

[0898] 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.

[0899] 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.

[0900] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0901] The following is further disclosed regarding the embodiments described above.

[0902] (Claim 1)

[0903] A means of receiving input from the user and using the information of the observation site to obtain light pollution and weather conditions from an external database,

[0904] A means for calculating the optimal timing and direction for astronomical observation based on acquired observation conditions,

[0905] A means of automatically generating and providing telescope operation tutorials and suggestions for photography techniques to beginner users,

[0906] A means for distributing the generated observation plan and operation tutorial to the user terminal,

[0907] A means of receiving user feedback and improving the system's analysis model,

[0908] A system that includes this.

[0909] (Claim 2)

[0910] The system according to claim 1, further comprising means for obtaining information on a celestial object to be observed from a database and adjusting the observation plan based on that information.

[0911] (Claim 3)

[0912] The system according to claim 1, further comprising means for accumulating user feedback and personalizing operation tutorials based on that feedback.

[0913] "Example 1"

[0914] (Claim 1)

[0915] A means for receiving information from the user and using location information to acquire light environment and weather conditions from an external recording device,

[0916] A means for calculating the optimal time and direction for astronomical observation based on acquired environmental conditions,

[0917] A means for automatically generating and providing instruction on the operation of observation equipment and imaging techniques for beginners,

[0918] Means for transmitting the generated observation plan and operational instructions to the user device,

[0919] A means of receiving user feedback and improving the information analysis model,

[0920] A system that includes this.

[0921] (Claim 2)

[0922] The system according to claim 1, further comprising means for acquiring information about the celestial object to be observed from a recording device and modifying the observation plan based on that information.

[0923] (Claim 3)

[0924] The system according to claim 1, further comprising means for accumulating user evaluations and personalizing operational guidance based on them.

[0925] "Application Example 1"

[0926] (Claim 1)

[0927] A means of receiving instructions from the user and using information from the evaluation site to obtain environmental and weather conditions from external sources,

[0928] A means for calculating the optimal time and direction for observing the phenomenon based on the acquired conditions,

[0929] A means of automatically generating and providing instructions on how to operate the device and suggestions on how to take pictures to beginner users,

[0930] A means for distributing the generated plan and operating procedure explanation to an information terminal,

[0931] A means of receiving feedback from users and improving the system's analysis model,

[0932] A means of providing personalized experience guides using information terminals,

[0933] A means of presenting phenomenon information and educational content in real time through personalized guides,

[0934] A system that includes this.

[0935] (Claim 2)

[0936] The system according to claim 1, further comprising means for obtaining information on the phenomenon to be observed from an information source and adjusting and optimizing the observation plan based on that information.

[0937] (Claim 3)

[0938] The system according to claim 1, comprising means for accumulating user feedback, personalizing the operation procedure explanation based on that feedback, and further optimizing the experience guide.

[0939] "Example 2 of combining an emotion engine"

[0940] (Claim 1)

[0941] A means of receiving information from users and using data from observation sites to obtain environmental conditions and weather information from an external database,

[0942] A means for calculating the optimal time and direction for astronomical observation based on acquired environmental conditions,

[0943] A means for recognizing the user's emotional state and automatically generating and providing telescope operation instructions and shooting methods accordingly,

[0944] A means for distributing the generated observation plan and operation manual to the user's equipment,

[0945] A means of receiving user feedback after the observation period and improving the system's analysis model,

[0946] A system that includes this.

[0947] (Claim 2)

[0948] The system according to claim 1, further comprising means for acquiring data of a celestial object to be observed from a storage device and adjusting the observation plan based on that data.

[0949] (Claim 3)

[0950] The system according to claim 1, further comprising means for accumulating user feedback and personalizing telescope operation instructions based on that feedback.

[0951] "Application example 2 when combining with an emotional engine"

[0952] (Claim 1)

[0953] A means of receiving input from the user and using the information of the observation site to obtain light pollution and weather conditions from an external database,

[0954] A means for calculating the optimal timing and direction for astronomical observation based on acquired observation conditions,

[0955] A means of sharing observation data in real time via a communication network,

[0956] A means to analyze user sentiment data and dynamically change its content during observation,

[0957] A means for distributing the generated observation plan and operation tutorial to the user's information processing device,

[0958] A means of receiving user feedback and improving the system's analysis model,

[0959] A system that includes this.

[0960] (Claim 2)

[0961] The system according to claim 1, further comprising means for obtaining information on the celestial object to be observed from stored information and adjusting the observation plan based on that information.

[0962] (Claim 3)

[0963] The system according to claim 1, further comprising means for accumulating user feedback and personalizing operational instructions based on that feedback. [Explanation of symbols]

[0964] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving input from the user and using the information of the observation site to obtain light pollution and weather conditions from an external database, A means for calculating the optimal timing and direction for astronomical observation based on acquired observation conditions, A means of automatically generating and providing telescope operation tutorials and suggestions for photography techniques to beginner users, A means for distributing the generated observation plan and operation tutorial to the user terminal, A means of receiving user feedback and improving the system's analysis model, A system that includes this.

2. The system according to claim 1, further comprising means for obtaining information on a celestial object to be observed from a database and adjusting the observation plan based on that information.

3. The system according to claim 1, further comprising means for accumulating user feedback and personalizing operation tutorials based on that feedback.

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