An immersive virtual space transaction method based on space-time mirror

Abstract

The application relates to the technical field of space-time mirror, and discloses an immersive virtual space transaction method based on space-time mirror, which comprises the following steps: providing space-time mirror data of a target physical space to a user terminal, wherein the space-time mirror data comprises a continuous three-dimensional virtual space supporting free roaming and an interactive digital asset bound with a real physical resource; receiving an interaction instruction of the user on the digital asset when the user browses the virtual space; determining the corresponding real physical resource according to the instruction and the binding relationship and acquiring a real-time transaction state of the real physical resource; finally, superimposing a transaction interface layer carrying the real-time transaction state information on a current rendering picture of the user terminal and directly generating a transaction order in response to the operation of the user in the layer. The application realizes deep and seamless fusion of immersive virtual navigation and real-time transaction service, and the browsing, exploration and decision process of the user in the three-dimensional space can be directly converted into a transaction behavior, so that the user experience and business conversion efficiency are remarkably improved.

Description

Technical Field

[0001] This application relates to the technical field of spatiotemporal mirroring, and more particularly to an immersive virtual space trading method based on spatiotemporal mirroring. Background Technology

[0002] With the booming development of the digital tourism industry, online travel platforms have become the main entry point for users to plan their trips and book services. The industry is upgrading from two-dimensional information display to immersive and interactive experiences, aiming to provide users with more realistic and attractive decision-making basis and improve order conversion efficiency. The subject matter of this application relates to an intelligent system that integrates three-dimensional virtual tours and instant transaction services, and its technical background lies in how to break down the current situation where "display, experience, and transaction" are separated in traditional online tourism.

[0003] Currently, the more advanced technical solutions mainly fall into two categories. The first category is high-precision 3D virtual display technology. This type of solution typically uses methods such as oblique photography and laser scanning to reconstruct the real-world 3D of scenic spots or hotels, generating detailed models that can be viewed online, greatly enhancing the visual realism. However, it has significant problems: First, the 3D models are mostly static displays, and users can only passively browse along a preset path, lacking the ability to freely roam and deeply interact from a first-person perspective, resulting in insufficient immersion; second, this technology is usually an independent module from the backend booking system, and after obtaining a good visual experience, users still need to exit the browsing environment and jump to a traditional webpage to complete the booking, leading to process interruption and user churn.

[0004] The second category is lightweight interactive navigation applications. Similar to VR technology, these solutions aim to balance experience and performance, often employing panoramic image stitching or lightweight 3D engines, supporting a certain degree of perspective switching and interactive hotspots. The problems with these applications are twofold: firstly, they sacrifice spatial continuity and a realistic sense of scale for smoothness, making it difficult for users to accurately grasp the overall layout; secondly, their interactive hotspots typically only link to text and image descriptions, failing to deeply integrate with core transaction data such as real-time inventory and dynamic prices. This prevents users from completing a full closed-loop transaction from selection and confirmation to payment within an immersive experience, essentially remaining "advanced advertising" rather than "tradable space."

[0005] Therefore, existing technologies have failed to effectively construct a technical architecture that seamlessly and deeply binds freely explorable immersive virtual spaces with real-time and secure commercial transaction capabilities. This has become a key bottleneck restricting the further improvement of digital cultural tourism experiences and commercial efficiency. Summary of the Invention

[0006] Based on the above-mentioned technical problems, this application provides an immersive virtual space transaction processing method based on spatiotemporal mirroring, which effectively solves the technical challenge of deep integration of immersive virtual environment, real-time commodity status and seamless transaction process.

[0007] An immersive virtual space transaction processing method based on spatiotemporal mirroring, executed by a server, the method comprising: Receive space access requests; In response to the space access request, the spatiotemporal mirror data of the target physical space is acquired and sent. The spatiotemporal mirror data is used to construct and render a continuous three-dimensional virtual space that supports first-person free navigation on the requesting terminal. The continuous three-dimensional virtual space contains at least one interactive digital asset, and the interactive digital asset has a predefined mapping relationship with the real physical resources in the target physical space. Receive an asset interaction request for a target digital asset among the at least one interactive digital assets; The validity of the asset interaction request is determined based on the dynamic intent entropy value of the user within the virtual space. Based on the asset interaction request and the predefined mapping relationship, determine the target real physical resource corresponding to the target digital asset; Obtain the real-time status information of the target's actual physical resources; Generate and send transaction interface data, which is used to overlay and display a transaction interaction interface carrying the real-time status information in the continuous three-dimensional virtual space screen rendered by the requesting terminal. Receive an order generation request initiated through the transaction interaction interface; In response to the order generation request, a transaction order is generated based on the target real physical resource.

[0008] By adopting the above technical solution, the core technical effect of achieving intelligent intent perception and causal-related transactions within an immersive virtual space is achieved. Upon receiving a space access request, the system distributes spatiotemporal mirror data for constructing an immersive 3D scene. This data contains interactive digital assets bound to real-world resources. When a user interacts with these assets, the system not only receives the request but, more importantly, calculates the intent entropy value in real time based on the user's dynamic behavioral sequence within the virtual space. This quantifies the certainty and true intent strength of the user's current interaction, filtering out invalid or falsely triggered operations and ensuring the accuracy of subsequent processes. After identifying the target real-world resource, the system attaches a causal query token when initiating a status query. This token encodes specific spatiotemporal phase information of the current virtual scene, enabling the backend resource management service not only to return the resource status but also to understand the virtual context in which the status was queried. This provides a causal logic chain for potential cross-state transactions or anomaly handling. The entire process, from intent filtering to causal-related querying, provides a highly immersive and free virtual environment for achieving accurate and reliable transactions.

[0009] Furthermore, the spatiotemporal mirror data includes time dimension information associated with the continuous three-dimensional virtual space; obtaining the spatiotemporal mirror data of the target physical space includes: Obtain the current physical state parameters of the target physical space, wherein the current physical state parameters include at least one of the following: real-time time identifier, real-time weather identifier, and real-time occupancy identifier; Based on the current physical state parameters, matching spatiotemporal mirror data is queried and retrieved from the spatiotemporal mirror database. The spatiotemporal mirror database stores multiple versions of spatiotemporal mirror data associated with different physical state parameters, so that the visual representation of the continuous three-dimensional virtual space rendered based on the sent spatiotemporal mirror data matches the current physical state parameters.

[0010] By adopting the above technical solution, a technological effect is achieved that synchronizes the visual representation of virtual space with the physical state of the real world in real time, enhancing immersion and realism. The system first acquires the current physical state parameters of the target physical space; these parameters serve as a data bridge connecting reality and virtuality. Subsequently, the system uses these parameters as index keys to query a pre-built spatiotemporal mirror database. This database does not store a single model but rather multiple versions of scene data associated with different physical state parameters. The system retrieves the version data that matches the current real-world parameters and sends it to the terminal. The 3D scene rendered by the terminal using this version data has lighting, shadows, atmosphere, and even dynamic elements within the scene that perfectly match the actual state of the real world. This ensures that the scene seen by the user during virtual roaming is consistent with the appearance of the real physical world at that specific time and place, thus solving the technical problem of the disconnect between virtual tour content and the real environment.

[0011] Furthermore, the method also includes constructing the spatiotemporal mirror database, including: Obtain the original spatial data of the target physical space under various physical states; Based on the original spatial data, a basic three-dimensional model of the target physical space is generated; For each of the various physical states, based on the corresponding original spatial data, auxiliary rendering data is generated that is adapted to the basic 3D model and characterizes the visual attributes of that state. The basic 3D model and the corresponding auxiliary rendering data for each state are associated and stored to form the spatiotemporal mirror database with physical state parameters as the index key.

[0012] The method further includes: extracting spatial cognitive tuning factors from the behavioral data of user groups in the continuous three-dimensional virtual space or corresponding physical space; the associated storage further includes associating the spatial cognitive tuning factors with the basic three-dimensional model and the associated rendering data.

[0013] By adopting the above technical solution, a technological effect has been achieved in constructing an intelligent spatial database that can dynamically evolve and incorporates collective cognition. Database construction begins with collecting raw spatial data under multiple physical states, generating a basic 3D model skeleton. For each specific physical state, the system processes the corresponding raw data, generating supplementary rendering data that records the unique visual attributes of that state, such as textures under specific lighting conditions and particle effects for specific weather conditions. The innovation lies in the fact that, during storage, the system not only associates the basic model with the rendering data for each state but also introduces a spatial cognition tuning factor. This factor is extracted and generated from massive amounts of user behavior data within the space; it acts like an adjustable parameter set. When the database is accessed, this factor can fine-tune the scene's presentation tendencies to better align with the spatial cognitive habits of human groups, thus allowing the database to evolve from a static scene repository into a vibrant cognitive map that reflects and adapts to group preferences.

[0014] Furthermore, acquiring the raw spatial data of the target physical space under various physical states includes: Receive point cloud data and multi-view image data from a sensor array deployed within the target physical space, and use the point cloud data and multi-view image data as the raw spatial data; and / or, The system receives crowdsourced image data from multiple user terminals, representing different perspectives of the target physical space, and fuses the crowdsourced image data with baseline spatial data to generate or update the original spatial data.

[0015] By adopting the above technical solutions, a high-fidelity and continuously updated spatial digitization effect is achieved through the fusion and reconstruction of multi-source heterogeneous data. Its working principle involves two parallel technical solutions. The first solution relies on a sensor array deployed in the field, which periodically and systematically collects laser point clouds and multi-view images, providing high-precision, structured raw data to ensure the geometric accuracy and visual fidelity of the digitized model. The second solution utilizes crowdsourcing, receiving image data captured and uploaded by countless user terminals at different times and from different perspectives. Although this data is not standardly collected, it is vast in quantity, rich in perspectives, and updated in a timely manner. The system uses computer vision algorithms to intelligently fuse and align these crowdsourced images with existing benchmark spatial data, enabling it to repair model details, update changed areas, and even extract textures that better conform to human visual aesthetics from a large number of tourist photos. The two solutions, used individually or in combination, jointly solve the balance problem between data acquisition costs, update timeliness, and model vividness.

[0016] Further, the real-time status information includes at least one of inventory information, price information, available time period information, and reservation status information; obtaining the real-time status information of the target real physical resource includes: Based on the resource identifier of the target real physical resource, initiate a status query to the corresponding resource status management service; Receive the real-time status information returned by the resource status management service, which reflects the latest status of the target's actual physical resources.

[0017] By adopting the above technical solution, the core technical effect of ensuring the real-time and accurate status information of traded items in virtual space is achieved. After identifying the target physical resource, the system initiates a query request to an independent service that manages the status of that resource based on its unique resource identifier. This service maintains a real-time database directly connected to the offline inventory, room availability, and ticket pricing systems. After the query request is sent, the system receives and waits for the response from the service. This response data is the real-time status information, which directly reflects the actual availability of the resource at this moment, such as whether the room has been booked, ticket availability, and current fluctuating prices. By establishing this standardized interface query mechanism, rather than relying on caching or periodic synchronization, it ensures that the bookable status seen by users in virtual space remains strictly consistent with the actual saleable status in the offline commercial system, fundamentally avoiding transaction disputes caused by overselling or inconsistent status.

[0018] Furthermore, after obtaining the real-time status information of the target real physical resource, the method further includes: Based on the real-time status information and the preset transaction rules, determine whether it is currently permissible to generate a transaction order for the target real physical resource; If it is determined that it is not allowed, then an abnormal status indicator and restriction logic are injected into the generated transaction interface data.

[0019] By adopting the above technical solution, the system achieves the technical effect of intelligently finding solutions and maximizing transaction opportunities when virtual transactions encounter obstacles. Its working principle is a hierarchical intelligent decision-making chain. First, when it is determined that the current state does not allow trading, the system does not directly reject it, but instead activates a virtual space state transition mechanism. Based on preset or dynamically generated parallel state branches within the spatiotemporal mirror data, it quickly calculates in the background to find a logically equivalent state that allows trading. If successfully found, the system simultaneously switches the logical state of the target resource and pushes the virtual scene data to the terminal, allowing the user to enter a new tradable state branch almost imperceptibly. If all parallel branches have no tradable states, the system executes a fallback strategy: on the one hand, it clearly marks the anomaly on the front-end interface and disables order placement to prevent user misoperation; on the other hand, it intelligently switches the entire spatiotemporal mirror to a version of the resource at a historically tradable moment and recommends this past state or other related resources to the user. This process simulates an intelligent agent actively solving problems for the user, significantly improving the experience and conversion rate.

[0020] Furthermore, the generation and sending of transaction interface data includes: Generate a transaction interface data package containing the real-time status information, interface layout description, and interaction logic definition. The interface layout description defines the superposition position and visual style fusion parameters of the transaction interaction interface in the continuous three-dimensional virtual space screen. The interaction logic definition includes descriptions of date selection, quantity selection, and order confirmation controls. The generation of the interaction logic definition incorporates the analysis results of the current narrative context of the continuous three-dimensional virtual space.

[0021] By adopting the above technical solution, the system achieves intelligent adaptation between the transaction interface and the virtual narrative context, enhancing the naturalness and immersion of the interaction. When generating the transaction interface data package, the system not only encapsulates conventional information such as resource status, interface layout, and control logic, but its innovation lies in the fact that the process of generating the interaction logic definition is not template-based. The system performs real-time analysis of the narrative context of the continuous three-dimensional virtual space in which the user is currently located, including the storyline theme, scene atmosphere, and current virtual events. Based on the analysis results, the system dynamically adjusts the definition of the interaction logic. This makes the transaction interface no longer a rigidly embedded heterogeneous element, but rather an integral part of the virtual world narrative, achieving a unity of functionality and immersion.

[0022] Further, receiving the order generation request initiated through the transaction interaction interface includes: The system receives an order generation request that includes transaction parameters set by the user through the transaction interaction interface, the resource identifier of the target real physical resource, and the user identifier. The transaction parameters include at least the date and quantity selected by the user.

[0023] By adopting the above technical solution, a seamless and accurate data transmission effect is achieved from the virtual space interactive interface to the generation of order requests. After the user completes the operation in the transaction interface that integrates real-time status and contextualized interaction logic, the operation is encapsulated into a structured order generation request. The core data body of this request includes at least three parts: first, the specific transaction parameters set by the user through interface controls, such as check-in and check-out dates and purchase quantity; second, the unique resource identifier of the target real physical resource behind the interacted digital asset, which is the key connecting the virtual and the real; and third, the user identifier of the user initiating the operation. After receiving this data packet, the system clearly knows which user wants to purchase which specific resource under what conditions. This process accurately and unambiguously converts the user's complex interactive intentions in the three-dimensional immersive environment into a standardized request that the backend order processing system can understand and execute, ensuring the accuracy of the conversion from visual interaction to business logic.

[0024] Further, receiving the order generation request, which includes the transaction parameters set by the user through the transaction interaction interface, the resource identifier of the target real physical resource, and the user identifier, includes: The received order generation request includes a payment success certificate, which is obtained by the requesting terminal after completing user verification and payment by invoking a local secure payment component; and / or, After receiving the order generation request, the third-party payment service interface is invoked, and after receiving the payment success notification returned by the third-party payment service, the step of generating a transaction order based on the transaction parameters, resource identifier, and user identifier is executed.

[0025] By adopting the above technical solutions, two highly reliable and secure transaction order confirmation and payment integration schemes are provided. In the first scheme, payment verification and execution are pre-processed on the user's local terminal. When the user confirms the order, the terminal calls the local secure payment component to generate a payment success credential after completing user authentication and payment authorization. This credential is sent to the server along with the order generation request. After the server verifies the validity of the credential, it can directly generate the order. The payment process and the order generation process are deeply coupled, ensuring security and efficiency. In the second scheme, the payment process is initiated by the server. After receiving the order generation request, the server does not generate the order immediately but instead calls a third-party payment service interface to guide the user to a trusted payment gateway. Only after the server receives the payment success notification from the payment gateway does it formally execute order creation. These two schemes are suitable for scenarios with extreme requirements for payment convenience and scenarios with strict requirements for payment risk control, respectively, providing flexible and reliable payment closed-loop protection.

[0026] Furthermore, the attribute information of the interactive digital asset stores the predefined mapping relationship, whereby the predefined mapping relationship is a reference to a unique resource identifier pointing to the real physical resource; determining the target real physical resource corresponding to the target digital asset based on the asset interaction request and the predefined mapping relationship includes: The target digital asset identifier is parsed from the asset interaction request; Based on the target digital asset identifier, obtain the resource identifier stored in its attribute information, and determine the resource pointed to by the resource identifier as the target real physical resource.

[0027] By adopting the above technical solution, a core technological effect of accurately and efficiently mapping virtual digital assets to real-world physical resources is achieved. Every interactive digital asset created in virtual space has a pre-defined mapping relationship stored in its attribute information. This relationship is specifically represented as a reference to a unique resource identifier pointing to a real-world physical resource. When the server receives an interaction request for a target digital asset, it first parses the target digital asset identifier from the request data, much like obtaining the virtual object's ID number. Next, the system uses this identifier as the key to query the digital asset's attribute information and extracts the stored resource identifier reference. Finally, based on this resource identifier, the system uniquely identifies the corresponding target real-world physical resource within the resource management system. This chain-reference-identifier resolution process establishes an accurate mapping channel from virtual interaction points to real-world business objects, which is the technological prerequisite for the entire system to achieve "what you see is what you order." Attached Figure Description

[0028] Figure 1 This is a flowchart illustrating the steps of an immersive virtual space transaction processing method based on spatiotemporal mirroring, as described in this application. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be clearly and completely described below in conjunction with specific embodiments. The described embodiments are only some, not all, of the embodiments of this invention. All other implementations obtained by those skilled in the art based on the solutions of this invention without inventive effort should fall within the scope of protection of this invention.

[0030] This invention provides an immersive virtual space transaction processing method based on spatiotemporal mirroring, executed by a server. This method constructs and dynamically schedules a spatiotemporal mirror synchronized with the real world, accurately mapping tradable real physical resources into the virtual space. It also introduces mechanisms such as intent judgment, causal correlation query, intelligent state transition, and contextualized interface generation during user interaction, ultimately completing a complete and reliable closed loop from experience to transaction within the virtual environment. (Refer to...) Figure 1 The following description will be provided in conjunction with specific steps and embodiments.

[0031] Step S100: Receive space access request.

[0032] When a user wishes to explore a specific destination, such as an island resort, they send a request to the system server through an application or browser on their device. This request is called a space access request, and it contains at least a unique identifier for the target physical space, such as the resort's coded ID. The server-side access service receives this request and forwards it to the core service unit responsible for handling virtual space logic, thereby initiating subsequent processes.

[0033] Step S200: In response to the space access request, acquire and send the spatiotemporal mirror data of the target physical space.

[0034] This is the starting point for building a virtual experience environment. The server needs to acquire and send a set of data to the terminal, which uses this data to build and render a continuous 3D virtual space that supports first-person free navigation. In this space, users can walk and look around freely as in reality, rather than passively watching images or videos from a fixed perspective.

[0035] This data is called spatiotemporal mirror data. It contains not only geometric and textural information of three-dimensional space, but also temporal dimension information associated with this continuous three-dimensional virtual space, enabling the virtual space to reflect the state at a specific moment. To obtain spatiotemporal mirror data that best matches the current real world, the server performs two key sub-steps.

[0036] Step S210: Obtain the current physical state parameters of the target physical space.

[0037] These parameters serve as a dynamic bridge connecting the virtual and the real world. In one embodiment, the current physical state parameter can be a real-time weather indicator obtained from an authoritative meteorological data interface, such as sunny, rainy, snowy, or foggy. In another embodiment, it can be a real-time time indicator derived from the system clock and geolocation service, such as early morning, noon, dusk, or late night. Furthermore, it can include real-time occupancy indicators obtained from IoT networks or business systems, such as the instantaneous visitor density at a scenic spot or the real-time waiting number at a specific restaurant in a hotel. These parameters can be used individually or in combination to comprehensively depict the true state of the target physical space at the current moment. The system obtains these parameters by calling the corresponding data interfaces or message services.

[0038] Step S220: Based on the current physical state parameters, query and retrieve matching spatiotemporal mirror data from the spatiotemporal mirror database.

[0039] The spatiotemporal mirror database is the core data warehouse of the system. It doesn't store a single 3D scene, but rather multiple versions of spatiotemporal mirror data associated with different physical state parameters. For example, for the same resort beach scene, the database might store multiple versions such as "Beach_Sunny_Morning," "Beach_Rainy_Dusk," and "Beach_Celebration_Crowded." Each version fully defines all the visual and auditory attributes that the virtual scene should have under that specific combination of physical state parameters.

[0040] The server combines the current physical state parameters obtained in step S210, such as weather equal to rain and time equal to dusk, into a query condition. Then, using this condition as the index key, it queries the spatiotemporal mirror database. The database engine retrieves the data version with the highest matching degree, such as beach_rain_dusk, and retrieves the spatiotemporal mirror data for that version. Finally, the server sends this data to the user terminal that initiated the request via the network.

[0041] Upon receiving the spatiotemporal mirror data, the graphics rendering engine on the terminal immediately begins parsing and rendering. The resulting continuous 3D virtual space, visually identical to the current physical parameters, generates a virtual environment that closely matches the actual physical state. Users will see a virtual beach shrouded in mist and rain, with streetlights twinkling and few tourists, a scene highly consistent with the real-world appearance of the resort. This dynamic matching mechanism fundamentally solves the technical problems of static virtual tour content and its disconnect from the real environment, achieving a real-time mirroring of the physical world from the virtual world through data-driven processing.

[0042] The construction of the spatiotemporal mirror database is a prerequisite for the execution of step S220. This is a relatively independent and asynchronous background data production process, which mainly includes the following sub-steps: Step S221: Obtain the original spatial data of the target physical space under various physical states.

[0043] This is the source of digitization; data can come from different channels to meet different needs. One approach to achieving high-precision reconstruction is to receive point cloud data and multi-view image data from a sensor array deployed within the target's physical space. The sensor array may include a LiDAR system to emit laser beams to measure distances and generate dense point clouds to accurately characterize the 3D geometry; it also includes a set of calibrated high-resolution cameras that simultaneously capture images from different angles to obtain rich texture and color information. This approach provides standardized, high-fidelity raw data.

[0044] Another approach to achieving low-cost, sustainable updates is to receive crowdsourced imagery data from multiple user terminals, representing different perspectives of the target physical space. This includes photos and videos taken by tourists using their phones and cameras, uploaded to the system after user authorization. While this data is not collected in a standardized manner, it offers advantages such as large data volume, wide perspective coverage, and timely updates. The system uses computer vision algorithms, such as structure-of-motion reconstructive motion, to perform feature point matching, alignment, and fusion processing on these crowdsourced images and existing high-precision benchmark spatial data. This allows for continuous refinement of model details and updates to changes caused by renovations or seasonal variations at extremely low cost.

[0045] These two data acquisition methods can be implemented individually or in combination. The former ensures the geometric accuracy of the basic model, while the latter endows the model with vivid details and timeliness, together resolving the contradiction between the high cost of high-quality 3D digitization and the difficulty of dynamic updates.

[0046] Step S222: Based on the original spatial data, generate a basic three-dimensional model of the target physical space.

[0047] Using the raw spatial data obtained in step S221, a basic 3D model is generated through a 3D reconstruction algorithm. This model defines the overall geometric structure of the space, such as terrain, building outlines, roads, and interior layout. The reconstruction algorithm can be based on traditional point cloud processing methods such as Poisson reconstruction and rolling sphere method, or it can be an implicit reconstruction method based on emerging artificial intelligence technologies such as neural radiation fields.

[0048] Step S223: For each of the multiple physical states, generate supplementary rendering data that is adapted to the base 3D model and characterizes the visual attributes of that state.

[0049] The base 3D model is the skeleton, while the supplementary rendering data is the skin and makeup that give it life in different states. The system needs to generate a set of rendering data for each physical state it plans to support, such as sunny, rainy, and snowy days. This set of data is processed based on the raw data collected or simulated under that state. For example, for a sunny state, it needs to generate specular maps under direct sunlight, clear shadow maps, and skybox textures for blue skies and white clouds. For a rainy state, it needs to generate wetness maps for object surfaces, a dynamic raindrop particle system, hazy atmospheric scattering parameters, and reflective effects for puddles on the ground. These supplementary rendering data precisely describe the visual effects that every part of the base model should have under that state.

[0050] Step S224: Link and store the basic 3D model, the auxiliary rendering data corresponding to each state, and the spatial cognitive tuning factors extracted from user group behavior to form a spatiotemporal mirror database.

[0051] This is the final step in database construction and also a key innovation. The system doesn't simply package the model and rendering data; instead, it introduces a spatial cognitive tuning factor. This factor is a multi-dimensional vector extracted by analyzing massive amounts of historical user behavior data in this space or similar virtual environments—such as mainstream travel routes, distribution of popular photo spots, and patterns of dwell time in different areas—using machine learning methods like clustering and principal component analysis. It encodes the unconscious cognitive habits and attention patterns of the population towards this space.

[0052] During storage, the system associates and binds the basic 3D model, the complete set of auxiliary rendering data under a specific combination of physical state parameters, and the corresponding spatial cognitive tuning factors to form a complete record. This record uses the combination of physical state parameters as the index key. All state records together constitute a spatiotemporal mirror database. When a record is queried, its embedded spatial cognitive tuning factors can be used by the terminal rendering engine or interactive logic module to fine-tune the default camera movement curve and optimize the appearance position and intensity of visual guidance elements. This ensures that the virtual space presented to the user is not only visually realistic, but its internal rhythm and focus also better meet the cognitive expectations of human groups, thereby improving the comfort and efficiency of the guided tour.

[0053] Step S300: Receive an asset interaction request for a target digital asset among at least one interactive digital asset.

[0054] Within the realistic virtual space rendered on the terminal, numerous interactive digital assets are pre-placed. These assets are concrete objects within the virtual scene and are directly related to user experience or transactions, such as distinctive beds in hotel rooms, lounge chairs on balconies, sightseeing cable cars in scenic areas, and shop windows in souvenir shops. Each interactive digital asset has a predefined mapping relationship with a specific real physical resource within the target physical space. For example, the bed in the virtual room maps to a specific room type in the hotel management system; the virtual sightseeing cable car maps to a seat resource on a train in the ticketing system.

[0055] Users interact with these assets in two main ways, thereby triggering asset interaction requests.

[0056] Step S310: Asset interaction requests include the first type of request triggered by the requesting terminal performing a selection operation on the target digital asset in the rendered screen. This is a proactive and precise interaction method. Users can select specific objects in the virtual scene remotely by clicking with the mouse cursor, pointing with a ray emitted from a controller, or using gesture recognition via a camera. After detecting this operation, the terminal generates an interaction request containing the identifier of the selected digital asset and sends it to the server.

[0057] Step S320: Asset interaction requests include a second type of request automatically triggered when the requesting terminal detects that the spatial distance between the virtual viewpoint and the target digital asset is less than a preset threshold. This simulates a passive and natural interaction method of "getting closer to observe" in reality. The terminal calculates the three-dimensional spatial distance between the user's current virtual viewpoint or virtual avatar and each interactive digital asset in the scene in real time. When the distance to an asset is less than a preset threshold, such as 0.5 meters, the terminal automatically generates an interaction request and sends it to the server without requiring the user to perform any additional clicks. The preset threshold can be adjusted according to the asset type; large furniture such as sofas can be set to 1 meter, and small ornaments such as table lamps can be set to 0.3 meters.

[0058] These two triggering mechanisms provide users with a flexible and intuitive interaction method, adapting to different usage scenarios and precision requirements.

[0059] Step S400: Determine the validity of the asset interaction request based on the user's dynamic intent entropy value within the virtual space.

[0060] This is an intelligent filtering layer designed to prevent accidental operations and improve the accuracy of subsequent core processes. Upon receiving an asset interaction request, the server does not process it immediately but first determines its validity. This determination is based on the user's dynamic intent entropy value within the virtual space. The intent entropy value is an indicator calculated in real-time by analyzing the user's recent behavioral sequences in the current session, used to quantify the clarity and certainty of the user's current operational intent.

[0061] The system maintains a sliding window of user behavior, recording information such as changes in the user's movement speed, view rotation angular velocity, and click intervals over the past few seconds. If the behavior sequence consists of rapid, erratic movement and frequent clicks, the calculated intent entropy value will be high, indicating that the current operation may be aimless browsing or accidental touches. If the behavior sequence consists of smooth movement followed by a pause and then a click, the entropy value will be low, indicating a clear intent based on observation. The server uses a lightweight machine learning model or rule engine to determine the validity of the current interaction request based on the real-time calculated intent entropy value. If it is determined to be invalid or of low confidence, the system can choose to ignore the request or send a prompt to the terminal requiring user confirmation, thereby filtering out a large number of meaningless operations and ensuring that subsequent critical steps such as resource determination and status query are initiated based on the user's clear intent.

[0062] Step S500: Based on the asset interaction request and the predefined mapping relationship, determine the target real physical resource corresponding to the target digital asset.

[0063] After confirming the interaction is valid, the system needs to map the clicks in the virtual world to real-world goods. This process relies on predefined mapping relationships stored in the attribute information of each interactive digital asset. Specifically, this relationship is represented by a reference to a unique resource identifier pointing to a real physical resource. For example, the attribute of the digital asset identified as "asset_premium_bed_01" stores a reference value "room_type_suite_king". The determination process includes the following sub-steps: Step S510: Parse the target digital asset identifier from the asset interaction request. The server extracts the unique identifier of the virtual object being interacted with by the user from the request data packet.

[0064] Step S520: Based on the target digital asset identifier, obtain the resource identifier stored in its attribute information, and identify the resource pointed to by the resource identifier as the target real physical resource. The system uses the digital asset identifier as the key to query the asset attribute database and obtain the real resource identifier bound to it, such as "room_type_suite_king". Subsequently, in the resource management system, the system identifies the entity corresponding to this identifier as the target real physical resource, such as the resource "Deluxe Ocean View Suite - King Bed" in a hotel room type management system. This process establishes a precise and error-free mapping channel from virtual interaction points to real-world commercial objects.

[0065] Step S530: During the process of obtaining the resource identifier based on the target digital asset identifier, the associated resource topology map derived from the digital asset identifier is queried in parallel to locate the main resource node and associated resource nodes.

[0066] This is an optimization step to enhance system intelligence and business potential. The associated resource topology graph is a resource relationship network stored in a graph structure. Nodes represent resources, and edges represent different types of relationships between resources, such as spatial adjacency, functional complementarity, and consumption scenario association. When the system queries the main resource identifier in step S520, it can query this topology graph in parallel using the same digital asset identifier as the entry point. The graph database will quickly return a subgraph with the resource as the main node, which contains multiple associated resource nodes strongly related to the main resource node.

[0067] For example, when a user interacts with the virtual sofa in the "Luxury Ocean View Suite," the system, while identifying the "Luxury Ocean View Suite" as the primary resource, may immediately discover related resource nodes such as "Family Connecting Suite," "Rooftop Ocean View Bar," and "Private Butler Service" through parallel queries. In this way, the system prepares a batch of highly relevant alternative or value-added recommendation options early in the process, providing real-time data support for subsequent handling of potential status anomalies or combined marketing, thus achieving intelligent resource discovery.

[0068] Step S600: When initiating a status query for the target real physical resource to the resource status management service, attach a causal query token generated based on the current spatiotemporal mirror phase.

[0069] After identifying the real-world transaction object, the system needs to query its latest status. However, this query is not an isolated network call. To ensure the causal traceability of the entire virtual transaction process, the system generates and attaches a special causal query token when constructing the query request. This token is generated based on the currently used spatiotemporal mirror phase. The phase can be understood as the version hash value of the current spatiotemporal mirror data, or a comprehensive identifier combining scene status, user virtual location, and other information. The token encodes the virtual context in which this status query occurred, such as which version of the resort mirror the user is using and the specific location in the virtual space where the interaction was initiated.

[0070] Step S700: Obtain the real-time status information of the target's actual physical resources.

[0071] Step S710: Based on the resource identifier of the target physical resource, initiate a status query to the corresponding resource status management service. The system sends the resource identifier, such as "room_type_suite_king", along with the causal query token generated in step S600, to the independent service responsible for managing the resource, namely the resource status management service. This service typically interfaces directly with offline property management systems, inventory databases, ticketing systems, etc., to maintain the latest status of the resource.

[0072] Step S720: Receive real-time status information returned by the resource status management service. The resource status management service processes the query request, retrieves the current status of the target resource from its real-time database, including inventory information, price information, available time period information, and reservation status information, and encapsulates this information in a response and returns it to the system server. This response data is the real-time status information of the target physical resource, accurately reflecting the actual tradability of the resource at this very moment.

[0073] Step S800: Based on real-time status information and preset transaction conditions, determine whether it is currently permissible to generate a transaction order for the target real physical resource.

[0074] After receiving real-time status information, the server makes a judgment based on preset business rules. Preset transaction conditions may include minimum stay requirements, whether online cancellation is supported, and user eligibility restrictions. The system combines comprehensive status information, such as room availability being 0, with the rules to perform logical operations and determine whether a user is currently allowed to submit an order for this resource.

[0075] If the decision is approved, the process proceeds to step S900 to continue generating the transaction interface.

[0076] If a decision is made that is not allowed, such as when the target room type is sold out, the system will not simply return an error page. Instead, it will initiate an innovative intelligent decision-making chain to proactively attempt to resolve the issue.

[0077] Step S810: Based on the parallel state branches supported by the spatiotemporal mirror data, initiate a virtual space state transition to find a tradable state.

[0078] Parallel state branches are an important concept in spatiotemporal mirror data models. They represent the manifestation of the same resource or logically equivalent resource under different conditions. For hotel rooms, parallel state branches might be other rooms of the same type on different floors within the same building. For tourist attractions, they might be ticket resources for the same attraction at different entry times.

[0079] When a transaction is deemed not permitted, the system immediately initiates a virtual space state transition calculation in the background based on the parallel state branches supported by the current spatiotemporal mirror data. It quickly traverses all known parallel branches, checking whether the real physical resources corresponding to each branch are currently in a tradable state.

[0080] Step S811: If a tradable state is successfully found, the target real physical resources and spatiotemporal mirror data are synchronously switched to the corresponding tradable state branch.

[0081] Suppose the system, through iteration, discovers that a room in the same hotel, with the same layout, but on a higher floor, is currently available for booking, and this room has a corresponding parallel state branch in the virtual space. The system will perform two synchronous operations: First, in terms of business logic, it switches the target real-world physical resource from the previously sold-out room to this newly found tradable room. Second, it sends a command to the user terminal, guiding the terminal's rendering engine to smoothly transition the currently displayed virtual scene from the original floor view to a new, higher floor view. This new view corresponds to the spatiotemporal mirror data of the tradable state branch. For the user, they may only perceive a slight increase in perspective or a fade in the scene, and find themselves "inside" a room with the exact same layout and decor, but with a better view and currently available for booking. This virtual space state transition mechanism creatively utilizes the flexibility of the virtual environment, intelligently and seamlessly transforming a real-world out-of-stock state into a virtual experience of availability and tradability, a key innovation for improving conversion rates.

[0082] Step S812: If a tradable state is not successfully found, inject an anomaly status identifier and restriction logic into the generated transaction interface data, and trigger a data switching operation to switch the spatiotemporal mirror data to be sent to a historical version and inject alternative resource recommendation information.

[0083] If the system fails to find a tradable state after traversing all parallel branches, a fallback strategy is executed. One strategy is to inject an anomaly flag and restriction logic into the trading interface data generated in subsequent step S900. The anomaly flag tells the front-end interface to highlight messages such as "sold out"; the restriction logic disables the order placement button on the interface to prevent accidental user operation.

[0084] Another more user-friendly strategy is to trigger a data switching operation. Instead of searching for parallel spaces, the system rewinds along the timeline. It switches the spatiotemporal mirror data prepared to be sent to the terminal to the historical version of the target resource at a relatively recent tradable point in history. For example, it shows the user a virtual scenario of when the room was available for booking yesterday afternoon. Simultaneously, alternative resource recommendations are injected into the generated transaction interface data. For example, it prompts the user, "This room type was available yesterday; we recommend rooms for tomorrow, or you can view other featured villas in the same property." This series of processes simulates a diligent intelligent sales assistant that strives to provide valuable information and alternative options even when the preferred solution is not feasible, maximizing the retention of user interest and potential transaction opportunities.

[0085] Step S900: Generate and send transaction interface data.

[0086] Regardless of resource status, the system needs to generate a transaction interface to present to the user. The goal of generating and sending transaction interface data is to create a transaction interaction interface that is deeply integrated with the virtual environment and carries real-time status information.

[0087] Step S910: Generate a transaction interface data package containing real-time status information, interface layout description, and interaction logic definition. The system integrates real-time status information, such as price and available dates, with predefined or dynamically generated interface descriptions. The interface layout description defines the overlay position, size, transparency, and visual style blending parameters of the transaction interaction interface in a continuous three-dimensional virtual space, ensuring that it looks like part of the virtual world rather than a rigid webpage pop-up. The interaction logic definition details the function of each control within the interface, such as how the date picker pops up, how the quantity is increased or decreased, and the triggering logic of the confirmation button.

[0088] Step S920: The generation of the interaction logic definition incorporates the analysis results of the current narrative context in the continuous three-dimensional virtual space. This is another creative design of this solution to enhance immersion. Narrative context refers to the theme, style, and atmosphere of the virtual environment in which the user is currently located. For example, the user may be exploring a virtual hotel with a "steampunk" theme, or a virtual scenic area with a "Classic of Mountains and Seas" mythology theme. The system will analyze the narrative context created by the current spatiotemporal mirror data.

[0089] Based on the analysis results, the system dynamically adjusts the definition of interaction logic. In a "steampunk" themed hotel, the interaction logic for booking a room might be defined as "signing a gear contract," the date selector might be designed as a rotating dashboard, and the confirmation button's click feedback would be a steam jet sound effect and animation. In a "Classic of Mountains and Seas" themed hotel, the same function might be expressed as "offering a sacred stone to secure a lodging," with interface elements filled with ancient Chinese patterns. This transforms the transaction interface from a purely functional component into a contextualized interactive element seamlessly integrated with the virtual world's narrative, fundamentally eliminating the boundaries of functional interfaces that disrupt immersion.

[0090] Step S1000: Receive an order generation request initiated through the transaction interaction interface.

[0091] Users complete their transactions within a contextualized interface, such as selecting a date and number of participants, and then clicking the confirmation button. The terminal then generates an order request and sends it back to the server.

[0092] Step S1010: Receive an order generation request containing the transaction parameters set by the user through the transaction interaction interface, the resource identifier of the target real physical resource, and the user identifier. This is the most common and core data structure for an order generation request. It explicitly includes three elements: what the user wants, i.e., the resource identifier of the target real physical resource; the conditions the user wants, i.e., the transaction parameters, which at least include the date and quantity selected by the user; and who the user is, i.e., the user identifier. This structured data packet accurately translates the user's complex intentions in the 3D immersive environment into a standardized business request that the backend order system can understand and process.

[0093] Step S1020: The received order generation request includes a payment success credential. This is a deeply integrated payment solution. The payment success credential is obtained by the requesting terminal after completing user verification and payment by calling the local secure payment component. For example, a user in the terminal app calls the payment interface via fingerprint or facial recognition to complete the deduction. The payment service provider or the terminal operating system returns a signed credential representing the successful payment. The terminal attaches this credential to the order generation request and uploads it together. After receiving it, the server only needs to verify the authenticity and validity of the payment credential; once verification is successful, the order can be generated directly. This method greatly simplifies the payment process and provides a smooth user experience.

[0094] Step S1030: After receiving the order generation request, the server calls the third-party payment service interface. Upon receiving a payment success notification from the third-party payment service, it then executes the step of generating a transaction order based on transaction parameters, resource identifiers, and user identifiers. This is another more common payment integration method. The server first receives an order generation request without a payment result. Subsequently, the server actively calls the interfaces of third-party payment services such as Alipay and WeChat Pay to generate a payment order and redirects the user to the payment gateway page. After the user completes the payment at the payment gateway, the third-party payment service notifies the server of payment success via an asynchronous callback. Upon receiving this payment success notification, the server then formally executes the order creation process. This method facilitates centralized risk control and order management by the server.

[0095] Step S1040: The order generation request also embeds on-chain evidence of the transfer of rights within the virtual space. This is an extension for future digital asset transactions. When a user purchases a digital collectible or reserves a virtual property with a unique digital number within the virtual space, the system can generate a corresponding ownership or usage right transfer record on the blockchain via a smart contract when the transaction occurs. The unique hash value of this on-chain transaction, or the newly generated digital asset token identifier, will be embedded into the order generation request as on-chain evidence. This means that the transaction is not only recorded in a centralized database, but its core rights and interests are also simultaneously anchored to a transparent, tamper-proof distributed ledger, giving virtual consumption verifiable and transferable asset attributes.

[0096] Step S1100: In response to the order generation request, generate a transaction order based on the target real physical resources.

[0097] This is the end of the entire process. After completing all necessary verifications, including payment verification and inventory pre-holding, the server creates a formal, immutable transaction order record in the order system. This order is strictly bound to the target real physical resource determined in step S500, as well as the transaction parameters and user identifier in step S1010. After the order is generated, the system notifies the relevant resource status management service to update the inventory and returns a successful order result to the user terminal. Thus, the user's exploration and interaction in the immersive virtual space ultimately closes the loop into a real commercial transaction.

[0098] In addition to the core transaction process mentioned above, the system also continuously runs a background learning and guidance process to optimize the user experience.

[0099] Step P100: Receive and record the requester's behavioral data within the continuous 3D virtual space. Throughout the user's browsing process, the system continuously receives their behavioral data stream, including movement trajectory coordinates, spatial location of the viewpoint focus, duration of focus dwell in front of specific points of interest, and trigger records for various interactive digital assets. This data is an objective mapping of the user's interests and preferences.

[0100] Step P200: Update the preference model associated with the requester based on behavioral data.

[0101] Step P210: Extract features from the behavioral data to obtain spatial location features and asset interaction features. The system extracts structured features from the raw behavioral logs, such as whether the areas where users frequently stay belong to "natural landscape areas" or "cultural exhibition areas," and whether the assets that are frequently interacted with belong to "high-end rooms" or "family-friendly facilities."

[0102] Step P220: Input spatial location features and asset interaction features into the prediction model to calculate the requester's real-time interest distribution for various spatial functions and asset types, and update the preference model using the real-time interest distribution. The system uses a machine learning model, such as a deep neural network, to predict the probability distribution of the user's current interest in different categories of content based on the extracted features. This distribution vector is used to update the user's long-term preference model, enabling the model to reflect the latest changes in their interests.

[0103] Step P230: The parameter update process of the prediction model is optimized within a dynamically reconstructed topological preference space. This is an innovation at the preference learning level. Traditional model updates perform gradient descent in a fixed feature space. This approach introduces a dynamically reconstructed topological preference space. This means that during model training and updates, the system not only adjusts the model parameters but may also adaptively adjust the topological structure of the feature space itself based on the macroscopic distribution and evolution patterns of all user behavior features. For example, the system might discover that the correlation between the feature dimensions "sea view" and "tranquility" has significantly increased in recent user behavior, and thus "bring these two dimensions closer" in the topological space. This is equivalent to dynamically constructing a custom mathematical space that better fits the current evolution of user interests for the model's learning process. Optimization within this space allows the model to better capture the nonlinear changes and deep correlations of user interests, thereby producing more accurate and robust personalized preference representations.

[0104] Step P300: Generate and send guidance instruction data based on the updated preference model. Based on the updated, more accurate preference model, the system calculates the areas or assets that are most attractive to the current user but have not yet been fully explored. Then, corresponding guidance instruction data is generated and sent to the user's terminal. This data is used to generate or modify visual guidance elements in the continuous 3D virtual space rendered on the requesting terminal to provide non-mandatory prompts for unexplored areas or uninterrupted assets. For example, for a user who loves modern art, the system might point to the entrance of a distant, unvisited contemporary art gallery at the edge of their virtual field of vision with a faint, flowing halo. This guidance is gentle, aesthetically pleasing, deeply integrated into the environment, and fully personalized, realizing an intelligent exploration assistant function and enhancing the user's discovery enjoyment and system stickiness.

[0105] In summary, this invention effectively solves the technical challenge of deeply integrating immersive virtual environments, real-time product status, and seamless transaction processes through the aforementioned systematic approach. By dynamically constructing and precisely matching spatiotemporal mirror data, high-fidelity real-time synchronization between the virtual environment and the real world is achieved, providing a realistic and credible visual and contextual foundation for immersive transactions. The introduction of intent entropy value judgment effectively filters out invalid interactions in the virtual space, improving the accuracy and reliability of subsequent core processes. By establishing predefined mappings and parallel associated resource queries, precise positioning and intelligent recommendation preparation from virtual interaction to real-world resources are achieved. Through causal query tokens and virtual space state transition mechanisms, an intelligent transaction decision chain with causal tracing capabilities and proactive problem-solving abilities is constructed, intelligently seeking alternative solutions when resources are unavailable, greatly increasing the likelihood of transaction completion and user experience. The generation of contextualized transaction interfaces through narrative context analysis completely breaks down the barriers between functional interfaces and the immersive environment, achieving a unity between commercial functions and virtual narratives. By supporting on-chain notarization, transactions within the virtual space are endowed with verifiable and transferable digital asset attributes, expanding the value dimension of transactions. By modeling users in a dynamically reconstructed topology preference space, more accurate and robust personalized behavior analysis and intelligent guidance are achieved.

Claims

1. A method for processing immersive virtual space transactions based on spatiotemporal mirroring, characterized in that, The method includes: Receive space access requests; In response to the space access request, the system acquires and sends spatiotemporal mirror data of the target physical space. The spatiotemporal mirror data is used to construct and render a continuous three-dimensional virtual space that supports first-person free navigation on the requesting terminal. The continuous three-dimensional virtual space contains at least one interactive digital asset, and the interactive digital asset has a predefined mapping relationship with the real physical resources in the target physical space. Receive an asset interaction request for a target digital asset among the at least one interactive digital assets; The validity of the asset interaction request is determined based on the dynamic intent entropy value of the user within the virtual space. Based on the asset interaction request and the predefined mapping relationship, determine the target real physical resource corresponding to the target digital asset; Obtain the real-time status information of the target's actual physical resources; Generate and send transaction interface data, which is used to overlay and display a transaction interaction interface carrying the real-time status information in the continuous three-dimensional virtual space screen rendered by the requesting terminal. Receive an order generation request initiated through the transaction interaction interface; In response to the order generation request, a transaction order is generated based on the target real physical resource.

2. The method according to claim 1, characterized in that, The spatiotemporal mirror data includes time dimension information associated with the continuous three-dimensional virtual space; obtaining the spatiotemporal mirror data of the target physical space includes: Obtain the current physical state parameters of the target physical space, wherein the current physical state parameters include at least one of the following: real-time time identifier, real-time weather identifier, and real-time occupancy identifier; Based on the current physical state parameters, matching spatiotemporal mirror data is queried and retrieved from the spatiotemporal mirror database. The spatiotemporal mirror database stores multiple versions of spatiotemporal mirror data associated with different physical state parameters, so that the visual representation of the continuous three-dimensional virtual space rendered based on the sent spatiotemporal mirror data matches the current physical state parameters.

3. The method according to claim 2, characterized in that, The method further includes constructing the spatiotemporal mirror database, including: Obtain the original spatial data of the target physical space under various physical states; Based on the original spatial data, a basic three-dimensional model of the target physical space is generated; For each of the various physical states, based on the corresponding original spatial data, auxiliary rendering data is generated that is adapted to the basic 3D model and characterizes the visual attributes of that state. The basic 3D model and the corresponding auxiliary rendering data for each state are associated and stored to form the spatiotemporal mirror database with physical state parameters as the index key.

4. The method according to claim 3, characterized in that, The acquisition of raw spatial data of the target physical space under various physical states includes: Receive point cloud data and multi-view image data from a sensor array deployed within the target physical space, and use the point cloud data and multi-view image data as the raw spatial data; and / or, The system receives crowdsourced image data from multiple user terminals, representing different perspectives of the target physical space, and fuses the crowdsourced image data with baseline spatial data to generate or update the original spatial data.

5. The method according to claim 1, characterized in that, The real-time status information includes at least one of inventory information, price information, available time period information, and reservation status information; obtaining the real-time status information of the target real physical resource includes: Based on the resource identifier of the target real physical resource, initiate a status query to the corresponding resource status management service; Receive the real-time status information returned by the resource status management service, which reflects the latest status of the target's actual physical resources.

6. The method according to claim 1, characterized in that, After obtaining the real-time status information of the target's real physical resources, the method further includes: Based on the real-time status information and the preset transaction rules, determine whether it is currently permissible to generate a transaction order for the target real physical resource; If it is determined that it is not allowed, then an abnormal status indicator and restriction logic are injected into the generated transaction interface data.

7. The method according to claim 1, characterized in that, The generation and sending of transaction interface data includes: Generate a transaction interface data package containing the real-time status information, interface layout description, and interaction logic definition. The interface layout description defines the superposition position and visual style fusion parameters of the transaction interaction interface in the continuous three-dimensional virtual space screen. The interaction logic definition includes descriptions of date selection, quantity selection, and order confirmation controls. The generation of the interaction logic definition incorporates the analysis results of the current narrative context of the continuous three-dimensional virtual space.

8. The method according to claim 1 or 7, characterized in that, Receiving an order generation request initiated through the transaction interaction interface includes: The system receives an order generation request that includes transaction parameters set by the user through the transaction interaction interface, the resource identifier of the target real physical resource, and the user identifier. The transaction parameters include at least the date and quantity selected by the user.

9. The method according to claim 8, characterized in that, The receiving of the order generation request, which includes the transaction parameters set by the user through the transaction interaction interface, the resource identifier of the target real physical resource, and the user identifier, includes: The received order generation request includes a payment success certificate, which is obtained by the requesting terminal after completing user verification and payment by invoking a local secure payment component; and / or, After receiving the order generation request, the third-party payment service interface is invoked, and after receiving the payment success notification returned by the third-party payment service, the step of generating a transaction order based on the transaction parameters, resource identifier, and user identifier is executed.

10. The method according to claim 1, characterized in that, The attribute information of the interactive digital asset stores the predefined mapping relationship, which is a reference to a unique resource identifier pointing to the real physical resource; The step of determining the target real physical resource corresponding to the target digital asset based on the asset interaction request and the predefined mapping relationship includes: The target digital asset identifier is parsed from the asset interaction request; Based on the target digital asset identifier, obtain the resource identifier stored in its attribute information, and determine the resource pointed to by the resource identifier as the target real physical resource.

Images