Geological three-dimensional science popularization system based on VR technology

Abstract

The invention provides a geological three-dimensional science popularization system based on a VR technology, and the system comprises an AI-driven geological data intelligent processing and three-dimensional scene dynamic construction module which is configured to intelligently extract key geological elements from one or more geological data sources through employing an artificial intelligence algorithm, and a high-precision and interactive three-dimensional geological virtual reality scene is constructed based on the geological elements, and the module can dynamically optimize the scene and load the scene as required. According to the system, the understandability and science popularization interestingness of geological phenomena are remarkably improved, learning interests are stimulated, complex geological structures, geomorphic forms and ancient environments can realistically reappear through an AI-enhanced high-precision three-dimensional scene construction technology, the cognitive threshold of geological knowledge is greatly reduced through an interactive geological process simulation function, and the system is suitable for popularization and application. Abstract is changed into concrete, and boring is changed into vivid, so that the user can be effectively stimulated.

Description

Technical Field

[0001] The present invention relates to the field of geological popular science technology, and in particular to a three-dimensional geological popular science system based on VR technology. Background Art

[0002] Geology is a body of knowledge that studies the Earth's material composition, internal structure, external characteristics, interactions between its layers, and its evolutionary history. Traditionally, popularizing geology relies primarily on textual descriptions and two-dimensional diagrams in textbooks, physical mineral and rock specimens and static models displayed in museums, and limited field trips where conditions permit. With the advancement of information technology, some geoparks and museums have begun disseminating information through official websites, producing brochures and reading materials, and providing guided tours.

[0003] These methods have popularized geological knowledge to a certain extent, but their limitations are also very obvious, such as: lack of intuitiveness and dynamism. For geological phenomena and processes that are large-scale, have long time spans, or are invisible to the naked eye, two-dimensional graphics and static models can hardly provide intuitive and dynamic displays, and learners often need to rely on abstract thinking to understand; lack of interactivity and sense of participation. Learners are mostly in a state of passively receiving information, lack opportunities for active exploration and practical operations, and it is difficult to stimulate deep learning interest; difficulty in crossing time and space scales: many key geological phenomena, such as deep geological structures and historical geological events, cannot be directly observed or experienced; limited fun and appeal. Traditional popular science methods are not attractive enough to the younger generation and it is difficult to effectively capture their attention in the era of "information explosion"; popular science methods are single and lack innovation. As pointed out in the above-mentioned study, the popular science methods of geology are still single, the sense of innovation is not strong, and emerging technologies have not been fully explored and utilized. Summary of the Invention

[0004] (1) Technical problems solved In response to the shortcomings of the existing technology, the present invention provides a three-dimensional geological science popularization system based on VR technology, which solves the problems of insufficient intuitiveness and dynamism, lack of interactivity and sense of participation, difficulty in crossing time and space scales, limited interest and appeal, and single popularization method and lack of innovation.

[0005] (2) Technical solution To achieve the above objectives, the present invention is implemented through the following technical solutions: a three-dimensional geological science popularization system based on VR technology, comprising: An AI-driven geological data intelligent processing and 3D scene dynamic construction module, configured to intelligently extract key geological elements from one or more geological data sources using artificial intelligence algorithms, and construct a high-precision, interactive 3D geological virtual reality scene based on the geological elements. The module is also capable of dynamically optimizing and loading the scene on demand. A multi-mode immersive interaction and geological process evolution simulation module is configured to provide users with multi-dimensional immersive navigation and interaction functions based on virtual reality devices in the three-dimensional geological virtual reality scene, and support users to perform visual, interactive, dynamic simulation and reproduction of preset or user-parameterized key geological processes; The AI-enabled personalized learning and collaborative knowledge exploration module is configured to use artificial intelligence technology to analyze users' interactive behaviors and learning status in a virtual reality environment in real time to generate user portraits, and provide users with personalized popular science content push, learning path guidance and intelligent question-and-answer services in combination with geological knowledge graphs. The module also supports multiple users to access the same shared virtual geological scene in the form of virtual avatars for synchronous collaborative exploration, task collaboration and real-time communication.

[0006] Preferably, the AI-driven geological data intelligent processing and three-dimensional scene dynamic construction module includes: The intelligent geological feature recognition and automatic and semi-automatic modeling unit uses deep learning algorithms to automatically identify and interpret key geological features such as strata, lithology, faults, folds, and ore bodies from geological maps, remote sensing images, drilling data, or geophysical exploration data. It also uses pre-set geological expertise database rules to implement constraints, enabling rapid or assisted construction of 3D geological models. The multi-scale geological model intelligent fusion and dynamic level of detail management unit is used to intelligently and seamlessly integrate 3D geological models from different sources, with different precision and spatial scales. It also dynamically adjusts the display level of detail of each geological model in the scene based on the user's viewing angle, distance, focus point, and VR hardware performance. The AI-assisted scene content generation and enhancement unit uses generative artificial intelligence technology to assist in the generation or dynamic enrichment of geological textures, paleontological morphological details, ancient vegetation or ecological landscape elements of a specific geological historical period in the scene, so as to enhance the realism and content richness of the scene.

[0007] Preferably, the multi-mode immersive interaction and geological process evolution simulation module includes: The parameter-driven and real-time interactive simulation unit for geological processes allows users to set or adjust one or more key parameters affecting a specific geological process through a VR interactive interface. The system calculates the dynamic evolution of the geological process in real time based on a built-in geodynamic model, physics engine, or empirical formula, and presents the results in a 3D visual format in the VR scene. The multi-sensory geological sensory and feedback unit, in addition to high-fidelity visual rendering, also integrates spatialized 3D sound field simulation and an optional tactile feedback device interface to enhance the user's comprehensive perception of geological phenomena; The time-space shuttle and multi-scale observation control unit supports users to freely "fast forward", "pause" and "replay" operations on a grand geological time scale to observe the paleogeography, paleoecology and paleostructure of different geological historical periods; and supports users to smoothly and seamlessly zoom, switch and explore details between a wide range of spatial scales.

[0008] Preferably, the AI-assisted scene content generation and enhancement unit includes: A personalized navigation and adaptive learning path recommendation unit based on user portraits and geological knowledge graphs continuously tracks and analyzes users' gaze data, head and hand movement trajectories, interaction object selection preferences, and behavioral data in embedded science popularization Q&A. It uses machine learning algorithms to dynamically build and update user portraits and matches these portraits with pre-built, structured geological knowledge graphs. This intelligently recommends the most appropriate science popularization content modules, exploration sequences, interactive tasks, or guides users to focus on specific geological phenomena, achieving adaptive and differentiated learning path guidance. The contextual AI Q&A and geological encyclopedia instant messaging unit allows users to ask questions about currently observed geological phenomena, objects, or simulated geological processes at any time in the VR scene through natural language voice recognition or integrated virtual text input. The built-in AI geological assistant can understand the user's intention in asking questions and, based on the current scene context, retrieve, integrate, and generate accurate and easy-to-understand answers from the background geological knowledge base, popular science material database, or linked external authoritative geological information sources. The answers can be in the form of voice broadcasts, text displays, pop-up diagrams, short animation demonstrations, or hyperlinks to relevant geological encyclopedia entries; The unit supports multi-person online virtual geological collaborative investigation, discussion and training. This unit allows multiple remote users connected via the network to enter and share the same three-dimensional virtual geological scene at the same time in the form of their own interactive virtual avatars. In the scene, users can conduct real-time two-way or multi-way voice communication, share their respective perspectives, jointly observe and mark geological phenomena, collaboratively operate virtual geological exploration tools, jointly complete preset geological science tasks, and conduct online exchanges and discussions, share results and mutual learning. Teachers or counselors can also participate as avatars of special roles to provide remote teaching guidance, process monitoring and effect evaluation.

[0009] Preferably, the deep learning algorithms used for intelligent identification of geological features and automatic and semi-automatic modeling units include but are not limited to: convolutional neural networks for segmentation, classification and target detection of geological images; recurrent neural networks or long short-term memory networks for processing serialized geological data; and graph neural networks for analyzing complex topological relationships and spatial connectivity between geological bodies.

[0010] Preferably, the parameterized driving and real-time interactive simulation unit of the geological process includes: Internal dynamic geological processes: such as plate tectonic movement, orogeny, magmatic activity, metamorphism, and the development and occurrence of earthquakes; External geological forces: such as weathering, erosion, erosion, transportation and deposition of various media, and the dynamic evolution of various landform types formed thereby; Geological disaster processes: such as the initiation, movement, and accumulation of landslides, collapses, and debris flows; the occurrence and development of ground subsidence and ground fissures; and the formation and evolution of barrier lakes and their risk of collapse. Resource formation and environmental evolution processes: such as the formation and enrichment process of specific types of mineral deposits, changes in paleoclimate and paleoenvironment, and the evolution of paleontology and mass extinction events.

[0011] Preferably, the virtual geological collaborative investigation, discussion and training unit that supports multiple people online further provides the following supporting functions: a shared virtual whiteboard or note-taking tool that allows multiple users to jointly mark, draw or record observations; customizable virtual avatars to distinguish different user identities or roles; a scene-embedded task management and progress tracking system for allocating and monitoring collaborative learning tasks; and session recording and playback functions to facilitate subsequent review and summary of learning outcomes.

[0012] (3) Beneficial effects The present invention provides a three-dimensional geological science popularization system based on VR technology. It has the following beneficial effects: 1. Significantly improve the comprehensibility and popular science interest of geological phenomena, stimulate learning interest, and through AI-enhanced high-precision three-dimensional scene construction technology, it can realistically reproduce complex geological structures, landforms and paleoenvironments. In addition, its interactive geological process simulation function greatly lowers the cognitive threshold of geological knowledge, turning the abstract into the concrete and the boring into the vivid, thereby effectively inspiring users.

[0013] 2. To achieve truly personalized and intelligent geological science popularization and improve the efficiency of knowledge absorption, the system can analyze the user's interactive behavior, visual focus, answering status, etc. in real time, build dynamic user portraits and cognitive models to provide each user with customized science popularization services, and dynamically adjust the difficulty and depth of science popularization information according to the user's understanding level.

[0014] 3. Enable efficient multi-person collaborative geological learning and discussion, promote cooperation and knowledge sharing, and enable multiple users to enter the same immersive geological scene with virtual avatars, share perspectives, communicate in real-time voice, jointly operate virtual tools to simulate geological surveys, collaboratively analyze geological phenomena, and discuss scientific issues online. This not only promotes the spirit of cooperative learning and the cultivation of team problem-solving skills, but also deepens the understanding and memory of geological knowledge through mutual assistance and exchange of ideas among members.

[0015] 4. Greatly improve the generation efficiency, scene realism and scientific nature of high-quality geological VR content. The in-depth application of AI technology in intelligent processing of geological data, automatic identification of key geological features, three-dimensional geological modeling, and AI-assisted scene content generation and enhancement technology can significantly shorten the development cycle of complex, high-precision geological VR scenes and reduce production costs. AI-assisted scene content generation and enhancement technology can also generate more realistic and detailed geological textures, paleontological morphology and paleoenvironmental elements. Combined with a scientific geological process simulation engine, it further improves the scientific nature of popular science content and the realism of scenes, thereby improving the overall quality and update speed of popular science content. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a modular flow chart of a geological three-dimensional popular science system based on VR technology proposed in this invention. DETAILED DESCRIPTION

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0018] like Figure 1 As shown, an embodiment of the present invention provides a three-dimensional geological science popularization system based on VR technology, including: The AI-driven geological data intelligent processing and 3D scene dynamic construction module is configured to intelligently extract key geological elements from one or more geological data sources using artificial intelligence algorithms, and construct a high-precision, interactive 3D geological virtual reality scene based on the geological elements. The module can also dynamically optimize and load the scene on demand. Specifically, it includes the following units: The intelligent identification and automatic and semi-automatic modeling units of geological features use deep learning algorithms including but not limited to: convolutional neural networks for segmentation of geological images, such as remote sensing images, core photos, thin-section images, classification, and target detection; recurrent neural networks or long-short-term memory networks for processing serialized geological data, such as well logging curves and time-series ground subsidence data; graph neural networks for analyzing complex topological relationships and spatial connectivity between geological bodies (such as fault networks, fracture systems, and pore structures) to automatically identify and interpret key geological features of strata, lithology, faults, folds, and ore bodies from geological maps, remote sensing images, drilling data, or geophysical exploration data, and combine them with pre-set geological professional knowledge base rules for constraints to achieve rapid or assisted construction of three-dimensional geological models; The multi-scale geological model intelligent fusion and dynamic level of detail management unit is used to intelligently and seamlessly integrate 3D geological models from different sources, with different precision and spatial scales. It also dynamically adjusts the display level of detail of each geological model in the scene based on the user's viewing angle, distance, focus point, and VR hardware performance. AI-assisted scene content generation and enhancement unit uses generative artificial intelligence technology (such as generative adversarial networks (GANs) or diffusion models) to assist in generating or dynamically enriching geological textures (such as rock surfaces, soil profiles), paleontological morphological details, paleoenvironmental vegetation or ecological landscape elements in specific geological historical periods to enhance the realism and content richness of the scene. The multi-mode immersive interaction and geological process evolution simulation module is configured in the three-dimensional geological virtual reality scene to provide users with multi-dimensional immersive navigation and interaction functions based on virtual reality devices, and supports users to perform visual, interactive, dynamic simulation and reproduction of preset or user-parameterized key geological processes (such as tectonic movement, landform shaping, mineral deposit formation, geological disasters, etc.). Specifically, it includes the following units: The parameter-driven and real-time interactive simulation unit for geological processes allows users to set or adjust one or more key parameters affecting specific geological processes (such as flow and slope in river erosion, stress magnitude and direction in fault activity, and temperature and viscosity in magma activity) through a VR interactive interface (such as virtual sliders, menu selections, and voice commands). The system calculates the dynamic evolution of the geological process in real time based on built-in geodynamic models, physics engines, or empirical formulas, and presents the results in a three-dimensional visual manner in the VR scene. Specifically, it includes: internal dynamic geological actions: such as plate tectonic movement (subduction, collision, expansion, and transform fault activity of plates), orogeny (the formation and evolution of folds and thrust structures), magmatic activity (underplating, intrusion, and eruption of magma, and the formation and activity of volcanoes), metamorphism, and the gestation and occurrence of earthquakes; External geological forces: such as weathering, erosion, erosion by various media (flowing water, wind, glaciers, oceans, groundwater), transportation and deposition, and the dynamic evolution of various landform types (such as fluvial landforms, deltas, karst landforms, aeolian landforms, glacial landforms, and coastal landforms) formed thereby; Geological disaster processes: such as the initiation, movement, and accumulation of landslides, collapses, and debris flows; the occurrence and development of ground subsidence and ground fissures; and the formation and evolution of barrier lakes and their risk of collapse. Resource formation and environmental evolution: such as the formation and enrichment of specific mineral deposits (oil, natural gas, coal, and metal minerals), paleoclimate and paleoenvironmental changes, and paleontological evolution and mass extinction events; The multi-sensory geological sensory and feedback unit, in addition to high-fidelity visual rendering, also integrates spatialized 3D sound field simulation (for reproducing environmental and event sounds such as earthquakes, volcanic eruptions, rock crushing, and water flow) and an optional haptic feedback device interface (for connecting to touch gloves or force feedback controllers to simulate the roughness of different rocks, the vibration of fault activity, and the force sensation of operating virtual tools), thereby enhancing the user's comprehensive perception of geological phenomena. Time and space shuttle in the multi-scale observation control unit, allowing users to freely "fast forward", "pause" and "rewind" on a grand geological time scale (for example, billions of years from the formation of the Earth to the present, or millions of years of evolution of a specific geological event) to observe the paleogeography, paleoecology and paleotectonic features of different geological historical periods; and supporting users to smoothly and seamlessly zoom, switch and explore details between a wide range of spatial scales (for example, from global plate tectonics to regional geological structures, to outcrop scales, and even mineral crystal microstructures in rock thin sections) The AI-enabled personalized learning and collaborative knowledge exploration module is configured to use artificial intelligence technology to analyze users' interactive behaviors and learning status in the virtual reality environment in real time to generate user profiles. It then combines the geological knowledge graph to provide users with personalized popular science content push, learning path guidance, and intelligent question-and-answer services. The module supports multiple users accessing the same shared virtual geological scene in the form of virtual avatars for synchronous collaborative exploration, task collaboration, and real-time communication. Specifically, it includes the following units: The personalized navigation and adaptive learning path recommendation unit based on user portraits and geological knowledge graphs continuously tracks and analyzes users' gaze data, head and hand movement trajectories, interactive object selection preferences, and behavioral data in embedded science popularization questions and answers. It uses machine learning algorithms to dynamically build and update user portraits (including their knowledge level, cognitive style, areas of interest, learning progress, etc.), and matches this portrait with a pre-built, structured geological knowledge graph (which defines the hierarchical relationships, dependencies, and difficulty attributes between geological concepts, principles, and phenomena). This intelligently recommends the most appropriate science popularization content modules, exploration sequences, interactive tasks, or guides users to focus on specific geological phenomena, achieving adaptive and differentiated learning path guidance. The contextual AI intelligent question-answering and geological encyclopedia instant messaging unit allows users to ask questions about currently observed geological phenomena, objects, or simulated geological processes at any time in the VR scene through natural language voice recognition or integrated virtual text input. The built-in AI geological assistant (usually a chatbot based on a large language model and fine-tuned with geological expertise) can understand the user's intention to ask questions and, based on the current scene context, retrieve, integrate, and generate accurate and easy-to-understand answers from the background geological knowledge base, popular science material database, or linked external authoritative geological information sources. The answers can be in the form of voice broadcasts, text displays, pop-up diagrams, short animation demonstrations, or hyperlinks to relevant geological encyclopedia entries; The unit supports multi-person online virtual geological collaborative investigation, discussion and training. This unit allows multiple remote users connected via the network to simultaneously enter and share the same three-dimensional virtual geological scene in the form of their own interactive virtual avatars. In the scene, users can conduct real-time two-way or multi-way voice communication, share their own perspectives (or choose to follow the perspective of a specific user), and jointly observe and mark geological phenomena. Collaborative operation of virtual geological exploration tools (such as virtual geological hammer, compass, GPS locator, sample collector, profile drawing board) to jointly complete preset geological science popularization tasks (such as simulated geological mapping, virtual route geological survey, geological disaster risk point identification and assessment), and conduct online communication and discussion, results sharing and mutual learning. Teachers or counselors can also participate as avatars of special roles to provide remote teaching guidance, process monitoring and effect evaluation. The following support functions are further provided: shared virtual whiteboards or note-taking tools that allow multiple users to jointly mark, draw or record observations; customizable virtual avatars to distinguish different user identities or roles (such as students, teachers, experts); scene-embedded task management and progress tracking systems for allocating and monitoring collaborative learning tasks; and session recording and playback functions for subsequent review and summary of learning results.

[0019] Working Principle: Utilizing AI-driven intelligent geological data processing and dynamic 3D scene construction modules, raw geological data is acquired from one or more sources. AI algorithms (such as deep learning models) are then used to clean and fuse the data, intelligently identify and interpret geological features (such as strata, structures, lithology, and ore bodies). Based on these interpretation results, 3D geological modeling technology is used to construct a scientifically based, high-precision 3D geological virtual reality scene that can be smoothly rendered and interacted with in a VR environment. During the construction of this scene, AI-assisted scene content generation and enhancement technology may also be used to enhance visual elements such as textures, paleontology, or paleoenvironments, and dynamic level of detail management may be implemented to optimize performance. In the constructed and optimized loaded 3D geological virtual reality scene, through multi-modal immersive interaction and geological process evolution simulation modules, users wearing VR terminal devices are provided with immersive navigation (such as walking, flying, and teleporting), observation (such as multi-angle and multi-scale viewing), and interactive tools (such as virtual handle selection, grabbing, and operation). Based on user input (such as adjusting the timeline and changing geological action parameters) or system-preset scripts, the system dynamically simulates and visualizes the spatiotemporal evolution of key geological actions (such as plate movement, landform evolution, and disaster occurrence) in real time in the form of 3D animation or state changes based on built-in geodynamic models, physics engines, or empirical rules. At the same time, corresponding multi-sensory feedback (such as visual changes, spatial sound effects, and optional tactile vibration) is provided to enhance the user's sense of presence. Through the AI-enabled personalized learning and collaborative knowledge exploration module, the user's interactive behavior (such as eye trajectory, operating habits, exploration path, task completion) and learning status (such as response to popular science knowledge points and answer accuracy) in the virtual environment are monitored and analyzed in real time throughout the entire process or specific stages of the user's VR experience, and a personalized user portrait and cognitive model are constructed using machine learning algorithms; then, this user portrait is matched with the system's built-in structured geological knowledge map to push the most appropriate popular science content to the user, recommend personalized learning paths, provide contextual intelligent question-and-answer services, and dynamically adjust the difficulty and depth of subsequent content based on learning results; and when the system is in multiplayer mode, the module is responsible for managing multiple users accessing the same shared virtual geological scene, ensuring synchronization of virtual avatars and smooth real-time voice communication between users, and providing functions for collaborative operation of virtual tools, joint completion of exploration tasks, and online communication and discussion to promote collaborative learning and the social construction of knowledge. Content not described in detail in this specification belongs to the existing technology known to professional and technical personnel in this field.

[0020] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A three-dimensional geological science popularization system based on VR technology, characterized by: include: An AI-driven geological data intelligent processing and 3D scene dynamic construction module, configured to intelligently extract key geological elements from one or more geological data sources using artificial intelligence algorithms, and construct a high-precision, interactive 3D geological virtual reality scene based on the geological elements. The module is also capable of dynamically optimizing and loading the scene on demand. A multi-mode immersive interaction and geological process evolution simulation module is configured to provide users with multi-dimensional immersive navigation and interaction functions based on virtual reality devices in the three-dimensional geological virtual reality scene, and support users to perform visual, interactive, dynamic simulation and reproduction of preset or user-parameterized key geological processes; The AI-enabled personalized learning and collaborative knowledge exploration module is configured to use artificial intelligence technology to analyze users' interactive behaviors and learning status in a virtual reality environment in real time to generate user portraits, and provide users with personalized popular science content push, learning path guidance and intelligent question-and-answer services in combination with geological knowledge graphs. The module also supports multiple users to access the same shared virtual geological scene in the form of virtual avatars for synchronous collaborative exploration, task collaboration and real-time communication.

2. The three-dimensional geological science popularization system based on VR technology according to claim 1, characterized in that: The AI-driven geological data intelligent processing and 3D scene dynamic construction module includes: The intelligent geological feature recognition and automatic and semi-automatic modeling unit uses deep learning algorithms to automatically identify and interpret key geological features such as strata, lithology, faults, folds, and ore bodies from geological maps, remote sensing images, drilling data, or geophysical exploration data. It also uses pre-set geological expertise database rules to implement constraints, enabling rapid or assisted construction of 3D geological models. The multi-scale geological model intelligent fusion and dynamic level of detail management unit is used to intelligently and seamlessly integrate 3D geological models from different sources, with different precision and spatial scales. It also dynamically adjusts the display level of detail of each geological model in the scene based on the user's viewing angle, distance, focus point, and VR hardware performance. The AI-assisted scene content generation and enhancement unit uses generative artificial intelligence technology to assist in the generation or dynamic enrichment of geological textures, paleontological morphological details, ancient vegetation or ecological landscape elements of a specific geological historical period in the scene, so as to enhance the realism and content richness of the scene.

3. The three-dimensional geological science popularization system based on VR technology according to claim 1, characterized in that: The multi-mode immersive interaction and geological process evolution simulation module includes: The parameter-driven and real-time interactive simulation unit for geological processes allows users to set or adjust one or more key parameters affecting a specific geological process through a VR interactive interface. The system calculates the dynamic evolution of the geological process in real time based on a built-in geodynamic model, physics engine, or empirical formula, and presents the results in a 3D visual format in the VR scene. The multi-sensory geological sensory and feedback unit, in addition to high-fidelity visual rendering, also integrates spatialized 3D sound field simulation and an optional tactile feedback device interface to enhance the user's comprehensive perception of geological phenomena; The time-space shuttle and multi-scale observation control unit supports users to freely "fast forward", "pause" and "rewind" on a grand geological time scale to observe the paleogeography, paleoecology and paleostructure of different geological historical periods; and supports users to smoothly and seamlessly zoom, switch and explore details between a wide range of spatial scales.

4. The three-dimensional geological science popularization system based on VR technology according to claim 1, characterized in that: The AI-assisted scene content generation and enhancement unit includes: A personalized navigation and adaptive learning path recommendation unit based on user portraits and geological knowledge graphs continuously tracks and analyzes users' gaze data, head and hand movement trajectories, interaction object selection preferences, and behavioral data in embedded science popularization Q&A. It uses machine learning algorithms to dynamically build and update user portraits and matches these portraits with pre-built, structured geological knowledge graphs. This intelligently recommends the most appropriate science popularization content modules, exploration sequences, interactive tasks, or guides users to focus on specific geological phenomena, achieving adaptive and differentiated learning path guidance. The contextual AI Q&A and geological encyclopedia instant messaging unit allows users to ask questions about currently observed geological phenomena, objects, or simulated geological processes at any time in the VR scene through natural language voice recognition or integrated virtual text input. The built-in AI geological assistant can understand the user's intention in asking questions and, based on the current scene context, retrieve, integrate, and generate accurate and easy-to-understand answers from the background geological knowledge base, popular science material database, or linked external authoritative geological information sources. The answers can be in the form of voice broadcasts, text displays, pop-up diagrams, short animation demonstrations, or hyperlinks to relevant geological encyclopedia entries; The unit supports multi-person online virtual geological collaborative investigation, discussion and training. This unit allows multiple remote users connected via the network to enter and share the same three-dimensional virtual geological scene at the same time in the form of their own interactive virtual avatars. In the scene, users can conduct real-time two-way or multi-way voice communication, share their respective perspectives, jointly observe and mark geological phenomena, collaboratively operate virtual geological exploration tools, jointly complete preset geological science tasks, and conduct online exchanges and discussions, share results and mutual learning. Teachers or counselors can also participate as avatars of special roles to provide remote teaching guidance, process monitoring and effect evaluation.

5. The three-dimensional geological science popularization system based on VR technology according to claim 2, characterized in that: The deep learning algorithms used for intelligent identification of geological features and automatic and semi-automatic modeling units include but are not limited to: convolutional neural networks for segmentation, classification and target detection of geological images; recurrent neural networks or long short-term memory networks for processing serialized geological data; and graph neural networks for analyzing complex topological relationships and spatial connectivity between geological bodies.

6. The three-dimensional geological science popularization system based on VR technology according to claim 3, characterized in that: The parameterized driving and real-time interactive simulation unit of the geological process includes: Internal dynamic geological processes: such as plate tectonic movement, orogeny, magmatic activity, metamorphism, and the development and occurrence of earthquakes; External geological forces: such as weathering, erosion, erosion, transportation and deposition of various media, and the dynamic evolution of various landform types formed thereby; Geological disaster processes: such as the initiation, movement, and accumulation of landslides, collapses, and debris flows; the occurrence and development of ground subsidence and ground fissures; and the formation and evolution of barrier lakes and their risk of collapse. Resource formation and environmental evolution processes: such as the formation and enrichment process of specific types of mineral deposits, changes in paleoclimate and paleoenvironment, and the evolution of paleontology and mass extinction events.

7. The three-dimensional geological science popularization system based on VR technology according to claim 4, characterized in that: The virtual geological collaborative survey, discussion and training unit that supports multiple people online further provides the following supporting functions: a shared virtual whiteboard or note-taking tool that allows multiple users to jointly mark, draw or record observations; customizable virtual avatars to distinguish different user identities or roles; a scene-embedded task management and progress tracking system for assigning and monitoring collaborative learning tasks; and session recording and playback functions to facilitate subsequent review and summary of learning outcomes.

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