Blockchain-based asset transaction management system and method

Abstract

The present application provides a blockchain-based asset transaction management system and method. The system comprises: an asset matching module, configured to bind a non-homogeneous token for a target asset; an asset evaluation module, configured to acquire asset evaluation data of the target asset, input same to an asset evaluation model in a first smart contract, and obtain a price evaluation value of the target asset; a transaction management module, configured to record transaction information of the target asset and upload same to a distributed ledger of the blockchain; and an income distribution module, configured to call a preset income distribution model in a second smart contract, to distribute an income value of the target asset to a corresponding income person. The present application can be applied to transaction management of various types of assets, to improve the security and universality of the asset transaction management.

Description

Asset transaction management system and method based on blockchain Technical Field

[0001] The present application relates to the field of asset transaction management technology, and specifically to an asset transaction management system and method based on blockchain. Background Art

[0002] With the development of internet technology, the application of online transactions is becoming increasingly widespread. While online asset transactions bring great convenience to people's lives, their security is also extremely important. Comprehensively ensuring the security of online asset transactions has always been a key focus of technological research and development. Existing asset transactions often require third-party access, resulting in significant additional costs such as brokerage and management fees. They also pose challenges such as information asymmetry and high transaction barriers. Furthermore, existing asset trading methods are often limited to a narrow range of asset transactions and a single type of transaction. Furthermore, with the deepening application of internet technology across various industries, there is a desire to expand online asset trading to more areas of application.

[0003] Summary of the Invention

[0004] An embodiment of the present application provides an asset transaction management system, comprising: an asset matching module for binding a non-fungible token to a target asset; an asset evaluation module for collecting asset evaluation data of the target asset, inputting the asset evaluation data into an asset evaluation model in a first smart contract, and obtaining a value evaluation value of the target asset; a transaction management module for recording transaction information of the target asset and uploading it to a distributed ledger of a blockchain, wherein the transaction information includes at least information about the holder of the target asset; and a profit distribution module for calling a preset profit distribution model in a second smart contract to distribute the profit value of the target asset to corresponding beneficiaries, wherein the beneficiaries include at least the holder of the target asset.

[0005] An embodiment of the present application also provides an asset transaction management method, which adopts the above-mentioned asset transaction management system, and the method includes: allocating and binding non-fungible tokens to target assets; collecting asset valuation data of the target assets, inputting the asset valuation model in the first smart contract, and obtaining the value assessment value of the target assets; recording the transaction information of the target assets and uploading it to the distributed ledger of the blockchain, wherein the transaction information includes at least the holder information of the target assets; calling the preset profit distribution model in the second smart contract to distribute the profit value of the target assets to the corresponding beneficiaries, and the beneficiaries include at least the holder of the target assets.

[0006] This application transforms tradable and profitable assets into non-fungible token assets, leveraging the uniqueness and immutability of blockchain to ensure transaction security. It utilizes the asset valuation model within smart contracts to provide more reasonable and accurate asset pricing, and through the profit distribution model within smart contracts, fairly distributes profit value to all beneficiaries of the asset. This application can be applied to the transaction management of various assets and encourages more people to participate in asset transaction management. This application integrates and anchors itself to the real industry, addressing the current shortcomings of virtual assets in transactions, such as opacity, instability, and unpredictability. It provides a relatively fair and equitable profit distribution for all contributors, rather than having only asset owners receive the majority of the profits. This application promotes the digitization and decentralization of the industry, truly returning rights and interests to the general public, and facilitating the realization of a form of asset management with universal participation. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Other features, objects and advantages of the present application will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings.

[0008] FIG1 is a block diagram of an asset transaction management system according to an embodiment of the present application;

[0009] FIG2 is a block diagram of an asset transaction management system that adds a revenue tracking module and an asset reporting module according to an embodiment of the present application;

[0010] FIG3 is a schematic diagram of an asset transaction management system implemented using a billboard as an example according to an embodiment of the present application;

[0011] FIG4 is a flowchart of an asset transaction management method according to an embodiment of the present application. DETAILED DESCRIPTION

[0012] Example embodiments will now be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in a variety of forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this application will be comprehensive and complete and will fully convey the concepts of the example embodiments to those skilled in the art. In the figures, the same reference numerals represent the same or similar structures, and thus their repeated description will be omitted. "Or" and "or" in the specification may both mean "and" or "or". Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices. Although "first" or "second" is used in this specification to represent certain features, it is only to indicate the function and is not intended to limit the number and importance of specific features.

[0013] As shown in Figure 1, this application provides a blockchain-based asset trading system, including an asset matching module M100, an asset evaluation module M200, a transaction management module M300, and a profit distribution module M400.

[0014] The asset matching module M100 is used to bind a non-fungible token to the target asset. A non-fungible token (NFT) is a special type of cryptographic asset that circulates on the blockchain. NFT assets differ from mainstream cryptographic assets such as Bitcoin in that each NFT is non-fungible and indivisible. The inherent uniqueness of NFTs allows them to represent similarly unique objects. In this application, the target asset and the NFT are bound one-to-one to ensure a 1:1 correspondence between the asset and the NFT. As a non-fungible token, the NFT can be converted into a fungible payment token during the transaction process. The fungible payment token can be used by users to purchase other assets in the form of NFTs. The use of fungible payment tokens as a medium of exchange facilitates the trading of non-fungible tokens (NFTs) that encode physical and virtual assets. A single transaction may include multiple types of tokens. Compared to homogeneous transactions, multi-token transactions are more efficient, saving users transaction fees and alleviating network congestion.

[0015] The asset evaluation module M200 is used to collect asset evaluation data of the target asset, input the asset evaluation model in the first smart contract, and obtain the value evaluation value of the target asset.

[0016] The transaction management module M300 is used to record the transaction information of the target asset and upload it to the blockchain's distributed ledger. The transaction information includes at least the target asset's holder information. Here, the holder information refers to the identity identification information of the user who purchased the target asset in the asset transaction management system, such as the holder's ID, serial number, identity code, and other information that uniquely identifies the user. The transaction of the target asset can be implemented using transaction smart contracts. Through the application of smart contracts, the blockchain-based sharing economy platform can achieve direct and secure transactions between individuals without the need for intermediaries, automatically executing various transaction agreements and rules, and eliminating the possibility of human error and fraud.

[0017] The profit distribution module M400 is used to call the preset profit distribution model in the second smart contract to distribute the profit value of the target asset to the corresponding beneficiary. The profit distribution model can be implemented by an artificial intelligence derivative algorithm (POC), wherein the profit distribution principle is configured and the distribution principle is executed through the second smart contract. Each beneficiary (participant) from different regions and countries can obtain corresponding fair profits through this profit distribution model. The beneficiaries include at least the holders of the target assets, but are not limited to this. They can also include other participants involved in the operation of the target assets, the holders of the smart contracts corresponding to the target assets, and the smart contracts here can be smart contracts associated with the target assets other than the second smart contract. For example, if the target asset is an advertising space area, the income of the advertising space area comes from advertising. The dividend income ratio of each NFT beneficiary can be automatically calculated through the second smart contract, and the income can be distributed accordingly, thereby realizing the automated income distribution of the advertising space area.

[0018] The revenue value includes the amount of alternative payment tokens. Therefore, when the revenue is distributed, the alternative payment tokens are paid to the beneficiary, allowing the beneficiary to obtain more alternative payment tokens, which can be used to purchase other assets in the form of NFTs. The transaction of the target asset includes the transaction between the two parties using alternative payment tokens. The two parties can also trade through NFTs, that is, they can also exchange the amount of alternative payment tokens corresponding to each NFT, using NFTs as transaction tokens.

[0019] This application is based on blockchain implementation. By combining decentralized networks with Internet technology, an automated asset transaction management system and method can be deployed to redefine asset valuation and income distribution, eliminating many traditional cost interventions, such as brokerage fees, management fees, etc., and breaking the limitations of traditional asset transaction management. It can combine all different types of assets in different regions and countries around the world to achieve more fair, transparent and efficient management, and solve the information asymmetry problem in traditional methods. Specifically, this application converts assets available for trading and income into non-fungible token assets through the asset matching module M100, and provides more reasonable and accurate asset pricing through the asset valuation module M200 using the asset valuation model in the first smart contract. The transaction management module M300 can record the transaction process, using the uniqueness and immutability of the blockchain to ensure the security of the transaction, and through the income distribution module M400, based on the income distribution model in the second smart contract, fairly distributes the income value to all beneficiaries of the asset according to their contribution. Multiple income pools can grow mutually. This application can be applied to the transaction management of various assets and can encourage more people to participate in asset transaction management, thereby improving the universality of asset transaction management.

[0020] The assets in this application can be tangible assets such as real estate, indoor and outdoor advertising space, machinery and equipment, materials or finished products, artwork, parking spaces, and entertainment facilities (such as vending machines). They can also be intangible assets such as intellectual property, music, videos, games (including in-game collectibles such as skins and equipment), and digital assets. Therefore, this application combines different types of assets, and all types of assets can be incorporated into this ecosystem, creating more business opportunities and value. The system in this application is highly scalable and can meet the needs of asset management of different scales and needs.

[0021] This application can also be integrated with other blockchain applications, such as supply chain management, e-commerce, etc., to build a complete blockchain ecosystem, thereby promoting the digitization and automation of the entire asset management process and providing investors with better services and more opportunities. This application can also be applied to the financial market and the insurance industry. In the financial market, it can help investors quickly and accurately assess the value of various financial assets, thereby formulating more effective investment strategies. In the insurance industry, it can help insurance companies better assess risks and formulate more reasonable insurance premiums and compensation plans. The blockchain-based asset transaction management system of this application can be deployed in various node devices of the blockchain, such as deployed in one or more node servers, which are connected to the network. Users can use the node server to log in to the asset trading platform through a unique account and can interact with the blockchain as a node of the blockchain.

[0022] This application further transforms the sharing economy from Web 2.0 to Web 3.0. The sharing economy is based on peer-to-peer transactions, allowing individuals to share or rent their resources (such as cars, homes, or tools) with others. Existing sharing economy business models are often centrally controlled and managed by third-party tech giants. This leads to problems such as high fees, lack of transparency, restrictions, and misuse of user data. This application provides a decentralized and transparent alternative to the sharing economy model, offering a more secure and tamper-proof digital transaction model. By using smart contracts, blockchain-based sharing economy platforms can enable direct and secure transactions between individuals without the need for intermediaries. This empowers users by allowing them to regain control of the platform through social consensus. Implemented on Web 3.0, this application will help break the monopoly of a few platform companies on the network, return control of the industry to users, and lead the industry towards digital, decentralized, and intelligent development. This new capital and equity distribution model, integrated with Web 3.0, allows for a more equitable distribution of benefits based on contribution, providing a model where multiple revenue pools grow in tandem. This addresses the current shortcomings of virtual assets in trading, such as opaque, unstable, and unpredictable prices, and provides a relatively fair and equitable distribution of benefits for all contributors. By anchoring virtual assets to real industries, this helps increase productivity in real industries, increases asset issuance, and contributes to a higher gross national product (GNP) for society. While integrating with the real economy, this application can be well adapted to local policy environments. For example, compliant transactions based on virtual asset exchanges under government supervision align with the core concept of anchoring virtual and digital assets to real economic returns and linking them to the social GDP provided by real industries. It also meets the requirements for STOs (Security Token Offers) in digital asset transactions. In summary, by adopting this application, currency exchange costs and interest rate differentials can be significantly reduced during the decentralized process, effectively mitigating the potential for triggering inflation or deflation in the macroeconomy.

[0023] A blockchain network is a decentralized digital ledger that allows for the secure and transparent transfer of data and assets, or transactions, over a peer-to-peer network. The mechanisms of a public blockchain network involve nodes, which are individuals or organizations that participate in the network by maintaining a synchronized ledger and validating transactions. In this application, each participant acts as a node and contributes to the maintenance of the distributed ledger through a consensus mechanism. In this ledger, transactions are bundled into chronologically linked blocks. Each block has a unique identifier, a hash. Any arbitrary alteration of historical transactions would disrupt the connection between blocks, making them easily identifiable.

[0024] In this embodiment, the transaction management module is also configured to receive transaction information encrypted using the transaction initiator's private key and forward it to the transaction recipient. The recipient is configured to verify the authenticity of the transaction information using the transaction initiator's public key. Once the transaction recipient confirms the transaction is successful, the transaction management module records the target asset's transaction information and uploads it to the blockchain's distributed ledger. Therefore, the use of key encryption protects the privacy of participants. Participants use a pair of keys to manage their accounts: the public key is shared with others, while the private key is kept confidential by the account owner, further enhancing the security of transaction data. Specifically, when initiating a transaction, the transaction initiator signs the encrypted transaction information using the sender's private key, which is then digitally signed and appended to the transaction data. The transaction is then broadcast to the network and verified by other nodes using the sender's public key. The consensus algorithm selects a node to package the transaction into a block, which is then verified by peers on the network. Once confirmed, a block is appended to the previous block, forming a chain of transaction history records. Transaction history is recorded on a distributed ledger, creating a transparent and immutable record of all transactions on the network, achieving a high degree of transparency, trust, and auditability. All transaction data is traceable and cannot be tampered with, and participants have the right to view the entire transaction history, reducing the risk of fraud or disputes.

[0025] In this embodiment, the asset transaction management system can be applied not only to the valuation, trading, and profit distribution of individual assets, but also to the case where a single asset is divided into multiple sub-assets. For larger assets, they can be divided into multiple areas, each representing a sub-asset. For example, a large billboard can be divided into multiple advertising space areas, each representing a sub-asset. A parking lot can be divided into multiple parking spaces, each representing a sub-asset. This allows for more granular and flexible management of asset transactions. Furthermore, investing in individual sub-assets is much easier, addressing the high transaction barriers associated with traditional methods.

[0026] Specifically, the asset matching module M100 is also used to divide an entire asset into multiple sub-assets, and use the multiple sub-assets as target assets, and bind NFTs to each of the target assets respectively, so that the value evaluation, transaction and income distribution of a single sub-asset can be achieved through the management of NFTs and the subsequent separate processing of the target assets by each module. For example, after obtaining the value evaluation value of a certain advertising space area separately, the user can purchase one or more advertising space areas separately without having to purchase the entire billboard, which has a lower investment cost and is easier for more people to participate. Similarly, after obtaining the value evaluation value of a parking space in a parking lot separately, the user can purchase a single parking space separately without having to purchase the entire parking lot.

[0027] When the target asset is a sub-asset of an overall asset, the asset evaluation module M200 collects the asset evaluation data of the target asset, inputs the asset evaluation model in the first smart contract, and obtains the value evaluation value of the target asset. The asset evaluation module M200 may collect the asset evaluation data of a single target asset, and obtain the value evaluation value of a single target asset based on the asset evaluation model in the first smart contract.

[0028] In another embodiment, when the asset evaluation data of the overall asset is not easy to split, the value evaluation value of the overall asset can be calculated first and then distributed to each sub-asset. Specifically, the asset evaluation module M200 collects the asset evaluation data of the overall asset, obtains the value evaluation value of the overall asset based on the asset evaluation model in the first smart contract, and calculates the value evaluation value of the target asset based on the value ratio of the target asset in the overall asset, that is, m i =m*s i , m is the valuation of the overall assets, m i is the valuation of the ith asset, s i is the value share information of the i-th sub-asset. The value share information here refers to the share of the value of the target asset in the value of the overall assets. The value share information can be calculated, for example, by using data such as the area of ​​the target asset and the area of ​​the overall assets, the position of the target asset in the overall assets, the historical transaction amount of the target asset and the historical transaction amount of the overall assets. For example, for advertising space areas of the same area, the better the location (for example, the closer to the middle of the billboard or the closer to the road next to the billboard), the higher the value share. For advertising area spaces with similar locations, the larger the area, the higher the value share will be.

[0029] In this embodiment, the asset valuation data includes at least one or more of the blockchain's distributed ledger data, historical transaction data from an exchange or market, and asset attribute data. The distributed ledger data may include historical transaction data from the blockchain-based asset transaction management system. The exchange or market's historical transaction data includes historical transaction data from various trading platforms and actual exchanges or markets. The asset attribute data may include, for example, hardware and infrastructure setup costs, maintenance, and depreciation expenses for the asset. The distributed ledger data and historical transaction data may include not only historical transaction data related to the current target asset, but also historical transaction data for assets of similar categories to the current target asset, historical transaction data for other sub-assets of the overall asset corresponding to the current target asset, and so on.

[0030] In this embodiment, the asset valuation module M200 is configured to periodically collect asset valuation data for the target asset within a preset time period according to a preset valuation cycle, input the data into the asset valuation model within the first smart contract, and update the target asset's valuation. The asset valuation module incorporates the traditional financial industry's price-to-earnings ratio valuation method, benchmarking / spiraling the value of the payable transaction tokens within the target asset's revenue pool (mining pool). For example, if the valuation cycle is set to 24 hours, the target asset's latest valuation is updated every 24 hours. The asset valuation model is a real-time online learning model, such as a deep neural network model. This asset valuation model effectively combines the advantages of real-world asset management and virtual artificial intelligence, continuously adapting to new market conditions and trading patterns, and accurately and rapidly evaluating the target asset. The asset valuation model is updated in real time and can automatically adjust the accuracy of the valuation results based on market changes. By providing more accurate valuation results, investors can develop more effective investment strategies and improve returns, eliminating the high costs and risks associated with traditional methods. This effectively promotes transparency and liquidity in the asset valuation market, enhancing the overall market's activity and competitiveness.

[0031] This embodiment provides an asset valuation model that can process multimodal dynamic data. For structured time series data, a recursive neural network structure can be used to model sequential patterns that change over time. Specifically, a long short-term memory (LSTM) unit can be used to capture such sequential patterns in a computationally efficient manner. The asset valuation model includes a structured processing network and a value assessment network, and the value assessment network includes an LSTM unit to achieve value assessment predictions that change over time. The structured processing network includes pre-processing the input data into a form that can be processed by the value assessment network. When processing various data, unstructured data can be processed by different forms of neural network structures.

[0032] The asset valuation data also includes social network data, one example of which is the social network between asset owners and buyers. Potential social interactions (e.g., frequency) are a valuable source of valuation information. Social network data is derived from public discussions on social media platforms, including but not limited to Twitter, Instagram, and Facebook. In this embodiment, the asset valuation model does not require the collection of any personal data. All social media data is de-identified and aggregated to a collective level.

[0033] Unlike structured tabular data sets, social networks represent the relationship ties between participants. However, social network data is often graphical data. Traditional machine learning algorithms cannot be directly applied to graphs because machine learning models require fixed-length input vectors, which graphs cannot meet. This application solves this problem by adopting graph embedding technology to map each node in the graph to a low-dimensional vector while retaining the graph structure information. This enables traditional machine learning algorithms to be applied to graphs by treating the embedded vectors as input data. Graph embedding is a technique used in machine learning to represent nodes in a graph as feature vectors in a continuous vector space. Graphs are used to represent complex relationships between objects, such as social network data, protein interactions, and recommendation systems. For example, each node in social network data includes each user, and the lines between each node represent the social relationships, interaction frequency, etc. between each user. Graph embedding technology extracts effective information based on the graph of social network data as input to the value assessment network.

[0034] Graph embedding can be implemented using a variety of methods, including matrix factorization, random walks, and deep learning-based approaches such as graph convolutional networks (GCNs). GCNs are neural networks that can be used to embed graphs by performing convolutions on the graph's adjacency matrix, capturing both local and global node representations. Therefore, using graph embedding components, graphs such as social data can be converted into vector form, which can then be used as input to a valuation network for asset value prediction.

[0035] In addition to graphics, another type of unstructured data is image data. Image data is a valuable source of information that facilitates asset valuation. In addition to text-based social media platforms, photos and videos (videos can be broken down into image frames) are common on modern social media platforms. This application, for example, uses convolutional layers to mathematically model image data for training and predicting image features. Convolutional neural networks (CNNs) are a specific neural network architecture designed to perform image processing and recognition tasks and have been very successful in a wide range of these tasks. CNNs can extract image features using multiple neurons. Their core is to apply convolutional filters to the input image to identify different features, such as edges and textures, and further use pooling layers to aggregate the outputs of the convolutional layers. Therefore, the pooling layer effectively reduces the spatial dimensionality of the feature map, helping to improve the network's computational efficiency. Finally, a fully connected layer is used at the end of the CNN network to perform the classification task, where the output of the previous layer is converted into a probability distribution of possible categories. After obtaining the image classification results output by the CNN, the image classification results can also be used as input data for the valuation network, incorporating image information into the asset valuation process. The training of CNN models is mainly to adjust the weights of filters and neurons to minimize the difference between the predicted category labels and the actual category labels.

[0036] For example, in one specific example, the asset valuation model includes a structured processing network and a value assessment network. The structured processing network includes a GCN based on graph embedding technology and a CNN for image processing. In this embodiment, before inputting various asset valuation data into the asset valuation model, a data preprocessing step is also included. For image data, this includes resizing the image or normalizing pixel values. For social network data, the data is preprocessed by creating a graphical representation of the network, where nodes represent users and edges represent relationships between users. For structured data, the data may be subjected to feature engineering techniques to extract relevant features. After preprocessing, the image data is input into the CNN for image feature extraction, and features are extracted from the social network data using graph embedding technology. All input data is then integrated and input into the value assessment network. When training the asset valuation model, asset valuation data for multiple asset samples is collected as a training set. The actual asset value of each asset sample is annotated. The asset valuation data for each asset sample is then input into the asset valuation model. A loss function is constructed by comparing the predicted valuation value output by the model with the standard actual asset value. The asset valuation model is then trained iteratively in reverse order. After training is complete, the model's evaluation results can be tested using a test set. If the evaluation results are poor, further optimization training can be performed. In this embodiment, the asset valuation model has an online feature, allowing it to be continuously updated based on newly acquired asset valuation data, thereby adapting to changes over time.

[0037] As shown in Figure 2, the system also includes a revenue tracking module M500, which is configured to collect revenue-related data from the target asset, invoke a third smart contract, and calculate the target asset's revenue value based on this revenue-related data. In this embodiment, through a closed-loop business model fully integrated with the real economy, multiple real-economy revenue pools are used to provide corresponding virtual asset revenue holders with a spiraling increase in value-added revenue based on virtual ecosystem revenue. These revenue pools include: profit sharing from the real economy; revenue from creation and services generated during the production process of the real economy; profit sharing from e-commerce portals and product distribution based on Web 3.0 logic and technology provided during the integration with the real economy; and value-added revenue generated by virtual and digital assets, such as actual applications on billboards that link to corresponding e-commerce web pages and are counted by the number of link visits; and value-added revenue generated by integration with intangible assets such as brands and product patents. By invoking the third smart contract, the target asset's revenue pools can be continuously tracked, thereby calculating the target asset's distributable revenue value.

[0038] In this embodiment, the profit distribution module uses the following steps to call the preset profit distribution model in the second smart contract to distribute the profit value of the target asset to the corresponding beneficiaries:

[0039] Determine the beneficiary corresponding to the target asset;

[0040] The contribution data of the beneficiaries is obtained based on a preset revenue distribution model, and the contribution value of each beneficiary is calculated. In this embodiment, the beneficiaries also include the creators and / or sharers of the content released in the target asset. The revenue distribution model may include preset contribution value calculation rules, such as defining the contribution value of a holder who purchases an asset, the contribution value of a sharer who promotes the asset, and the contribution value of a creator who invests content in the asset. The number of times a sharer shares and the income generated by the sharing, as well as the income generated by the content created by the creator, will also affect their contribution value.

[0041] The profit value that each beneficiary deserves is calculated based on the total contribution value of all beneficiaries and the contribution value of each beneficiary.

[0042] In this embodiment, when the target asset is a sub-asset of an overall asset, the income from the overall asset may be distributed simultaneously to the holders of multiple sub-asset types. In this case, obtaining the beneficiary's contribution data includes obtaining the beneficiary's contribution data for each sub-asset of the overall asset. The beneficiary's contribution data includes the percentage of the value of the sub-asset corresponding to the beneficiary in the overall asset. For example, if a beneficiary's contribution value for a sub-asset is a, and the sub-asset's value in the overall asset accounts for b%, then the beneficiary's contribution value for the overall asset is a*b%.

[0043] Calculate the income value that each beneficiary deserves based on the sum of the contribution values ​​of all beneficiaries and the contribution value of each beneficiary, including: calculating the income value that each beneficiary deserves based on the overall income of the overall asset, the sum of the contribution values ​​of the beneficiaries of each sub-asset corresponding to the overall asset, and the contribution value of each beneficiary. For example, if the overall income of the overall asset is x, and the sum of the contribution values ​​of all beneficiaries of the overall asset is sum, then the contribution value of each beneficiary is calculated as: x*a i / sum,a i Indicates the contribution value of the beneficiary of the i-th sub-asset to the overall asset.

[0044] As shown in Figure 2, in this embodiment, the asset transaction management system also includes: an asset reporting module M600, which is used to generate a revenue report based on the revenue-related data and revenue distribution. For example, when applied to the advertising field, artificial intelligence will automatically record the ownership and revenue distribution of the advertising space area, and provide corresponding data statistics and reports to help advertisers and NFT holders better manage their advertising and revenue. For example, artificial intelligence can realize the automatic tracking and statistics of indicators such as advertising clicks, impressions and conversion rates, thereby helping advertisers and NFT holders to better understand the advertising effect and revenue, thereby improving the transparency, security and efficiency of the advertising market.

[0045] Figure 3 schematically illustrates the system architecture for applying the present application to billboards. In this example, an entire large physical digital billboard is a whole asset, which is combined with numerous small LED display panels. Each display panel serves as an advertising space area, becomes a sub-asset, and is bound 1:1 to an NFT. The number of NFTs corresponds exactly to the number of advertising space areas, and the NFTs in each area carry a unique value. By purchasing a single advertising space area, a user becomes an NFT holder, and thus an NFT beneficiary, and will be entitled to a share of the revenue from the target physical asset. The revenue-related data includes traffic data and / or transaction data for the content corresponding to the target asset. The revenue of the target physical asset can be calculated based on the revenue-related data. In addition, for creators who place advertising content in the advertising space area and forward it on social platforms, when revenue is generated, a revenue distribution model will be used to distribute alternative payment currencies or non-fungible tokens based on the value of each advertising area.

[0046] As shown in Figure 4 , an embodiment of the present invention further provides an asset transaction management method. The flowchart shown in Figure 4 is for illustrative purposes only and does not necessarily include all steps. For example, some steps may be decomposed, while others may be combined or partially combined. Furthermore, the order of the steps in Figure 4 is merely illustrative; the actual order of execution may vary depending on the circumstances.

[0047] As shown in FIG4 , the asset transaction management method includes the following steps:

[0048] S100: Bind non-fungible tokens to target assets;

[0049] S200: Collect asset evaluation data of the target asset, input the data into the asset evaluation model in the first smart contract, and obtain the value evaluation value of the target asset;

[0050] S300: Recording the transaction information of the target asset and uploading it to the distributed ledger of the blockchain, wherein the transaction information at least includes the holder information of the target asset;

[0051] S400: Calling a preset profit distribution model in the second smart contract to distribute the profit value of the target asset to corresponding beneficiaries, and the beneficiaries at least include the holder of the target asset.

[0052] The asset transaction management method is implemented based on the above-mentioned asset transaction management system, so it can have the beneficial effects of the above-mentioned asset transaction management system, and can adopt the specific implementation method of the above-mentioned system to implement each step, which will not be repeated here.

[0053] The above content is a further detailed description of the present application in conjunction with specific preferred embodiments, and the specific implementation of the present application cannot be considered to be limited to these descriptions. For ordinary technicians in the technical field to which the present application belongs, several simple deductions or substitutions can be made without departing from the concept of the present application, and all of them should be considered to fall within the scope of protection of the present application.

Claims

1. An asset transaction management system based on blockchain, characterized in that: include: Asset matching module, used to allocate and bind non-fungible tokens to target assets; An asset evaluation module, used to collect asset evaluation data of the target asset, input the asset evaluation model in the first smart contract, and obtain the value evaluation value of the target asset; A transaction management module, used to record the transaction information of the target asset and upload it to the distributed ledger of the blockchain, wherein the transaction information at least includes the holder information of the target asset; The profit distribution module is used to call the preset profit distribution model in the second smart contract to distribute the profit value of the target asset to the corresponding beneficiaries, and the beneficiaries at least include the holders of the target asset.

2. The blockchain-based asset transaction management system according to claim 1, characterized in that: The asset matching module is also used to divide an entire asset into multiple sub-assets, and use the multiple sub-assets as target assets, and bind non-fungible tokens to each of the target assets.

3. The blockchain-based asset transaction management system according to claim 2, characterized in that: When the target asset is a sub-asset of an overall asset, the asset evaluation module collects asset evaluation data of the target asset, inputs the asset evaluation model in the first smart contract, and obtains the value evaluation value of the target asset, including: The asset evaluation module collects asset evaluation data of a single target asset, and obtains a value evaluation value of the single target asset based on the asset evaluation model in the first smart contract; or The asset evaluation module collects the asset evaluation data of the overall assets, obtains the value evaluation value of the overall assets based on the asset evaluation model in the first smart contract, and calculates the value evaluation value of the target asset according to the value proportion information of the target asset in the overall assets.

4. The blockchain-based asset transaction management system according to claim 1, characterized in that: The asset evaluation model is an online learning asset evaluation model.

5. The asset transaction management system according to claim 4, characterized in that: The asset evaluation data includes at least one or more of the distributed ledger data of the blockchain, historical transaction data of an exchange or market, and asset attribute data.

6. The asset transaction management system according to claim 4, characterized in that: The asset evaluation data also includes social network data, and the asset evaluation model is used to process the asset attribute data using the social network data based on a graph embedding method to obtain input data with a preset structure.

7. The blockchain-based asset transaction management system according to claim 4, characterized in that: The asset evaluation module is used to regularly collect asset evaluation data of the target asset within a preset time period according to a preset value evaluation cycle, and input the asset evaluation data into the asset evaluation model in the first smart contract to update the value evaluation value of the target asset; wherein, the asset evaluation module combines the price-earnings ratio valuation method to increase the value of the transaction tokens payable in the income pool of the target asset.

8. The asset transaction management system according to claim 1, characterized in that: The system also includes a revenue tracking module, which is used to collect revenue-related data of the target asset, call a third smart contract, and calculate the revenue value of the target asset based on the revenue-related data.

9. The asset transaction management system according to claim 8, characterized in that: The profit distribution module uses the following steps to call the preset profit distribution model in the second smart contract to distribute the profit value of the target asset to the corresponding beneficiaries: Determine the beneficiary corresponding to the target asset; Acquire the contribution data of the beneficiaries based on a preset benefit distribution model, and calculate the contribution value of each beneficiary; The benefit value that each beneficiary deserves is calculated based on the total contribution value of all beneficiaries and the contribution value of each beneficiary.

10. The asset transaction management system according to claim 9, characterized in that: Also includes: The asset reporting module is used to generate an income report based on the income-related data and income distribution.

11. The asset transaction management system according to claim 9, characterized in that: When the target asset is a sub-asset of an overall asset, obtaining the contribution data of the beneficiary includes: respectively obtaining the contribution data of the beneficiary corresponding to each sub-asset of the overall asset; The income value that each beneficiary deserves is calculated based on the total contribution value of all beneficiaries and the contribution value of each beneficiary, including: the income value that each beneficiary deserves is calculated based on the overall income of the overall assets, the total contribution value of the beneficiaries of each sub-asset corresponding to the overall assets and the contribution value of each beneficiary.

12. The asset transaction management system according to claim 11, characterized in that: The beneficiary's contribution data includes information on the value proportion of the sub-asset corresponding to the beneficiary in the overall assets.

13. The asset transaction management system according to claim 8, characterized in that: The beneficiaries also include creators and / or sharers of the content placed in the target asset; The beneficiaries also include the smart contract holders corresponding to the target assets.

14. The asset transaction management system according to claim 13, characterized in that: The revenue-related data includes traffic data and / or transaction data of the delivery content corresponding to the target asset.

15. The asset transaction management system according to claim 1, characterized in that: The transaction management module is also used to receive transaction information encrypted by the transaction initiator using its own private key and forward it to the transaction recipient. The transaction recipient is configured to use the public key of the transaction initiator to verify the authenticity of the transaction information. When the transaction recipient confirms that the transaction is successful, the transaction management module records the transaction information of the target asset and uploads it to the distributed ledger of the blockchain.

16. The asset transaction management system according to claim 1, characterized in that: The revenue value includes the amount of alternative payment tokens, and the transaction of the target asset includes the transaction between the two parties through non-fungible tokens and / or alternative payment tokens.

17. An asset transaction management method, characterized in that: Using the asset transaction management system described in claim 1, the method comprises the following steps: Allocate and bind non-fungible tokens to target assets; Collect asset evaluation data of the target asset, input it into the asset evaluation model in the first smart contract, and obtain the value evaluation value of the target asset; Recording the transaction information of the target asset and uploading it to the distributed ledger of the blockchain, wherein the transaction information at least includes the holder information of the target asset; The preset profit distribution model in the second smart contract is called to distribute the profit value of the target asset to the corresponding beneficiaries, and the beneficiaries at least include the holders of the target asset.

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