Planting industry RDA support system and method based on Internet of Things and block chain

Abstract

The invention discloses a planting industry RDA support system and method based on the Internet of Things and a block chain, and relates to the technical field of planting industry. The data link is in communication connection with the platform layer, and the data link is in communication connection with the platform layer and the physical sensing layer; the block chain and token layer is in communication connection with the data link and platform layer, the block chain and token layer is in communication connection with the data link and platform layer, the block chain and token layer is in communication connection with the data link and platform layer, the block chain and token layer comprises an asset uplink gateway, a multi-tenant block chain network and an intelligent contract factory, and the asset uplink gateway performs data calculation on a verified asset data packet to realize credible evidence storage; and the application and interaction layer is in communication connection with the block chain and token layer, and the application and interaction layer comprises a tenant management portal, a peasant household and cooperative workbench, an investor service platform and a supervision mechanism view, so that the technical effects of establishing a credible data bridge and realizing dynamic value evaluation and real-time risk monitoring of assets are achieved.

Description

Technical Field

[0001] This invention belongs to the field of agricultural technology, and in particular relates to an agricultural RDA support system and method based on the Internet of Things and blockchain. Background Technology

[0002] As a fundamental industry of the national economy, agriculture has long faced core challenges such as limited financing channels, insufficient supply chain transparency, and a lack of risk management tools. In recent years, the tokenization of Real Data Assets (RDA) has emerged as an innovative financial paradigm, offering a new solution to these problems. Its core lies in using blockchain technology to digitally map and standardize the division of tangible agricultural assets such as land, crops, agricultural machinery, and future revenue rights, transforming them into tradable digital tokens. This aims to improve asset liquidity, broaden financing channels, and reshape the value of agricultural assets.

[0003] Currently, technological development in this field follows two relatively independent paths: on the one hand, agricultural IoT technology is maturing, enabling precise monitoring and data collection of the entire agricultural production process through the deployment of various environmental sensors, drone remote sensing equipment, and intelligent agricultural machinery; on the other hand, the blockchain financial technology system is continuously improving, providing reliable underlying technical support for asset token issuance, ownership confirmation, and transaction clearing and settlement. However, current technological status indicates that these two technological systems have not yet achieved effective integration. The key bottleneck lies in the lack of a complete technical solution that can map the dynamic asset status of the physical world (including crop growth, environmental parameters, equipment operation, etc.) onto the blockchain in a real-time, reliable, and tamper-proof manner. This technological gap results in digital tokens lacking solid and verifiable dynamic asset backing, forming "information silos." This not only makes it difficult for investors to participate due to a lack of trust but also hinders agricultural operators from conducting efficient financing based on on-chain assets. Therefore, the industry urgently needs a comprehensive support system and device that can seamlessly connect physical planting and digital finance, achieving a closed-loop process from data collection and reliable on-chain storage to tokenized management.

[0004] Existing technologies for realizing RDA tokenization in the planting industry mainly suffer from the following defects and shortcomings: First, the disconnect between the physical and digital worlds leads to a lack of trust: Under the current technological framework, agricultural IoT systems and blockchain financial platforms operate independently, lacking effective technological integration. Asset status information such as crop growth and environmental data collected by the IoT cannot be automatically uploaded to the blockchain and anchored to corresponding digital tokens in a trustworthy and tamper-proof manner. Investors cannot verify the actual condition of off-chain assets in real time and can only rely on the issuer's unilateral credit endorsement. This makes the underlying asset value of digital tokens lack transparency and credibility, becoming a core obstacle to large-scale application.

[0005] Second, asset status updates are lagging and easily tampered with, making dynamic anchoring difficult: Agricultural assets are dynamically changing, with their value fluctuating continuously depending on growth stage and health condition. Existing technologies largely rely on manual data entry or scheduled batch uploads, resulting in significant delays. Furthermore, data is at risk of being tampered with or lost during transmission and processing. This prevents on-chain tokens from accurately reflecting the real value changes of the underlying assets in real time, hindering dynamic asset valuation and risk pricing, and failing to meet the stringent requirements of financial-grade applications for data timeliness and authenticity.

[0006] In summary, the fundamental flaw of existing technologies lies in their failure to construct an end-to-end closed-loop system that integrates trusted data perception in the physical world with automatic value mapping and risk control in the digital world. The lack of effective collaboration among the various technological components and the presence of multiple breakpoints in data flow prevent the accurate and timely reflection of the true value of agricultural assets in the digital world. Summary of the Invention

[0007] This application provides an IoT and blockchain-based RDA support system and method for the planting industry. It solves the technical problems in the prior art, such as the difficulty in transferring trust between the physical and digital worlds, the lag in dynamic asset valuation and risk monitoring, and the fragmentation and inefficiency of business processes. It achieves the technical effects of establishing a reliable data bridge, realizing dynamic asset valuation and real-time risk monitoring, significantly improving risk pricing capabilities and market efficiency, realizing automated and closed-loop management of business processes, and greatly improving operational efficiency while reducing operational risks and costs.

[0008] In a first aspect, embodiments of the present invention provide an agricultural RDA support system based on the Internet of Things and blockchain, comprising: a physical sensing layer, the physical sensing layer including multiple physical sensing devices and blockchain tamper-proof tags, wherein the multiple physical sensing devices are used to collect raw agricultural data; a data link and platform layer, the data link and platform layer being communicatively connected to the physical sensing layer, and the data link and platform layer including a data asset management platform, a data asset management toolbox, and a template configuration library, wherein the raw agricultural data is processed through the data asset management platform to obtain verified asset data packages; and a blockchain and tokenization layer. The blockchain and tokenization layer is communicatively connected to the data link and platform layer. The blockchain and tokenization layer includes an asset on-chain gateway, a multi-tenant blockchain network, and a smart contract factory. The asset on-chain gateway performs data calculations on the verified asset data packets to achieve trusted evidence storage. The application and interaction layer is also communicatively connected to the blockchain and tokenization layer. The application and interaction layer includes a tenant management portal, a farmer and cooperative workbench, an investor service platform, and a regulatory agency view. The application and interaction layer provides customized interactive interfaces for users with different roles and supports multi-tenant parallel access and business collaboration.

[0009] Secondly, this invention also provides a method for supporting RDA in the planting industry based on the Internet of Things (IoT) and blockchain. The method includes: Step 1: System initialization configuration and tenant registration; Step 2: Collection of raw planting data through multiple physical sensing devices, and transmission of the collected data to a data access gateway via an IoT network; Step 3: Intelligent data analysis and value assessment of the collected raw planting data through a data asset management platform to obtain verified asset data packages; Step 4: Trusted data on-chaining and trusted notarization using an asset on-chain gateway at the blockchain and tokenization layer; Step 5: Digital token issuance and asset management using a smart contract factory at the blockchain and tokenization layer; Step 6: Real-time display of sensor data and analysis results through a production monitoring dashboard at the application and interaction layer, and risk warnings through a risk warning center; Step 7: Investors discover and select investment targets through an investor service platform, complete token transactions, and automatically execute profit distribution operations through a profit distribution contract; Step 8: Regulatory agencies monitor the system's operating status in real-time through a regulatory agency view and conduct audit tracking; Step 9: Consumers can scan the blockchain tamper-proof label on product packaging for traceability verification and value realization.

[0010] The above-described one or more technical solutions in the embodiments of the present invention have at least one or more of the following technical effects: This invention provides an IoT and blockchain-based RDA support system and method for agricultural production. The system includes a physical sensing layer comprising multiple physical sensing devices and a blockchain tamper-proof tag, wherein the physical sensing devices are used to collect raw agricultural data; a data link and platform layer, which is communicatively connected to the physical sensing layer and includes a data asset management platform, a data asset management toolkit, and a template configuration library, wherein the data asset management platform processes the raw agricultural data to obtain verified asset data packages; and a blockchain and tokenization layer, which is also communicatively connected to the data link and platform layer, and includes an asset on-chain gateway, a multi-tenant blockchain network, and a smart contract factory, wherein the asset on-chain gateway verifies the raw agricultural data. The subsequent asset data package undergoes data calculation to achieve trusted evidence storage. The application and interaction layer communicates with the blockchain and tokenization layer. This layer includes a tenant management portal, a farmer and cooperative workbench, an investor service platform, and a regulatory agency view. The application and interaction layer provides customized interactive interfaces for users with different roles and supports multi-tenant parallel access and business collaboration. This solves the technical problems of trust transfer between the physical and digital worlds, lagging dynamic asset valuation and risk monitoring, and fragmented and inefficient business processes in existing technologies. It establishes a trusted data bridge, enables dynamic asset valuation and real-time risk monitoring, significantly improves risk pricing capabilities and market efficiency, and achieves automated and closed-loop management of business processes, greatly improving operational efficiency and reducing operational risks and costs.

[0011] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0012] Figure 1 This is a schematic diagram of the structure of an agricultural RDA support system based on the Internet of Things and blockchain in an embodiment of the present invention; Figure 2 for Figure 1 A schematic diagram of the structure of the blockchain and tokenization layer in China; Figure 3 for Figure 1 A flowchart illustrating the trusted data transmission and evidence preservation mechanism in China; Figure 4 This is a schematic diagram illustrating the value transformation of agricultural RDA in one application scenario according to an embodiment of the present invention. Figure 5 This is a flowchart illustrating an RDA support method for the planting industry based on the Internet of Things and blockchain, as described in an embodiment of the present invention.

[0013] Figure labeling: Physical sensing layer 100; Environmental monitoring sensor group 101; Crop growth monitoring device 102; Intelligent water and fertilizer integration device 103; Warehouse monitoring device 104; Agricultural machinery tracking device 105; Blockchain anti-tamper tag 106; Data link and platform layer 200; Data asset management platform 201; Data asset management toolbox 202; Template configuration library 203; Tenant management 2011; Template engine 2012; Data access gateway 2013; Data processing engine 2014; Blockchain and tokenization layer 300; Asset on-chain gateway 301; Multi-tenant blockchain network 302; Smart contract factory 303; Data receiving module 3011; Hash calculation module 3012; IPFS storage interface 3013; Transaction generation module 3014; Blockchain interface module 3015; Consensus management layer 3021; ​​Data isolation layer 3022; Cross-chain interaction module 3023; Issuance contract 3031; Compliance contract 3032; Profit distribution contract 3033; Application and interaction layer 400; Tenant management portal 401; Farmer and cooperative workbench 402; Investor service platform 403; Regulatory agency view 404. Detailed Implementation

[0014] This application provides an RDA support system and method for the planting industry based on the Internet of Things and blockchain, which solves the technical problems of difficulty in transferring trust between the physical and digital worlds, lag in dynamic asset valuation and risk monitoring, and fragmentation and inefficiency of business processes in the prior art.

[0015] The overall concept of the technical solutions in the embodiments of the present invention is as follows: This invention provides an IoT and blockchain-based RDA support system and method for agricultural planting. The system comprises: a physical sensing layer, including multiple physical sensing devices and blockchain tamper-proof tags, wherein the multiple physical sensing devices are used to collect raw agricultural planting data; a data link and platform layer, communicatively connected to the physical sensing layer, and including a data asset management platform, a data asset management toolbox, and a template configuration library, wherein the data asset management platform processes the raw agricultural planting data to obtain verified asset data packages; and a blockchain and tokenization layer, communicatively connected to the data link and platform layer, and including an asset on-chain gateway and multiple... The system comprises a tenant blockchain network and a smart contract factory. The asset on-chain gateway performs data calculations on the verified asset data packets to achieve trusted evidence storage. An application and interaction layer communicates with the blockchain and tokenization layer. This layer includes a tenant management portal, a farmer and cooperative workbench, an investor service platform, and a regulatory agency view. The application and interaction layer provides customized interfaces for users with different roles and supports multi-tenant parallel access and business collaboration. This establishes a trusted data bridge, enables dynamic asset valuation and real-time risk monitoring, significantly improves risk pricing capabilities and market efficiency, and achieves automated and closed-loop management of business processes. Ultimately, it significantly improves operational efficiency and reduces operational risks and costs.

[0016] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Example 1 This embodiment provides an RDA support system for the agricultural industry based on the Internet of Things and blockchain, such as... Figure 1 As shown, the system includes: The physical sensing layer 100 includes multiple physical sensing devices and a blockchain anti-tampering tag 106, wherein the multiple physical sensing devices are used to collect raw planting data.

[0018] Furthermore, the plurality of physical sensing devices specifically include: an environmental monitoring sensor group 101, including a soil moisture sensor, a soil temperature sensor, a soil EC value sensor, a soil pH value sensor, an air temperature and humidity sensor, a light intensity sensor, and a carbon dioxide concentration sensor installed in the field, and connected to the data asset management platform via LoRa, Zigbee, or 4G or 5G networks, wherein each sensor's data packet contains a tenant identifier to ensure data isolation; The crop growth monitoring device 102 includes a multispectral drone and a fixed high-definition camera set in the field. The multispectral drone is used to carry out aerial photography and collect multispectral images, and the fixed high-definition camera is used to collect images of crop growth status. The intelligent water and fertilizer integrated device 103 includes a controller, an irrigation valve, a fertilizer pump, and a flow sensor. The controller is used to control the start and stop of the irrigation valve and the fertilizer pump, and the flow sensor is used to monitor the irrigation amount and fertilizer amount in real time. The warehouse monitoring device 104 is installed in a grain warehouse or cold storage, and includes a temperature and humidity sensor and an RFID scanner for inventory counting. The temperature and humidity sensor is used to collect environmental data, and the RFID scanner is used to automatically scan and record inventory changes when goods enter or leave the warehouse. Agricultural machinery tracking device 105, which is installed on agricultural machinery and has a built-in GPS module and operation status.

[0019] Specifically, this system provides an RDA support system for the planting industry based on the Internet of Things (IoT) and blockchain. This system adopts a layered architecture design, deeply integrating IoT, big data, artificial intelligence, and blockchain technologies to construct an end-to-end closed-loop system from trusted data perception in the physical world to the tokenization and financial application of assets in the digital world. The physical perception layer 100 is the terminal for the system's interaction with the physical world, employing a multi-tenant architecture design to support simultaneous access by multiple agricultural operators. Each tenant corresponds to an independent agricultural industry template, which pre-sets standardized data collection specifications and device configuration parameters. This layer includes multiple physical sensing devices and blockchain tamper-proof tags 106. The specific physical sensing devices are as follows: environmental monitoring sensor group 101, crop growth monitoring device 102, intelligent water and fertilizer integration device 103, warehouse monitoring device 104, and agricultural machinery tracking device 105.

[0020] Specifically, the environmental monitoring sensor group 101 includes soil moisture sensors, soil temperature sensors, soil EC value sensors, soil pH value sensors, air temperature and humidity sensors, light intensity sensors, and carbon dioxide concentration sensors deployed in the field. These sensors connect to the data asset management platform via LoRa, Zigbee, or 4G / 5G networks, continuously collecting and uploading environmental data according to the sampling frequency preset in the agricultural industry template. Each sensor's data packet contains a tenant identifier to ensure data isolation.

[0021] Furthermore, the crop growth monitoring device 102 includes a regularly flying multispectral drone and fixed high-definition cameras deployed in the field. The drone performs aerial photography missions according to the flight plan set by the agricultural template, acquiring high-resolution multispectral images; the fixed cameras acquire images of crop growth status according to the shooting frequency configured in the template. All image data is transmitted wirelessly to the data asset management toolbox at the data link layer for analyzing crop growth, leaf area index, and early identification of pests and diseases.

[0022] Furthermore, the intelligent water and fertilizer integration device 103 includes a controller, an irrigation valve, a fertilizer pump, and a flow sensor. The controller controls the start and stop of the irrigation valve and fertilizer pump according to the irrigation strategy preset by the agricultural template or intelligent instructions from the platform layer. The flow sensor monitors the irrigation and fertilizer application in real time. All operational data is uploaded via the Internet of Things communication module as an important record for asset maintenance.

[0023] Furthermore, the warehouse monitoring device 104 is deployed inside the grain warehouse or cold storage, including temperature and humidity sensors and an RFID scanner for inventory counting. The temperature and humidity sensors collect environmental data according to the monitoring frequency set by the agricultural template, and the RFID scanner automatically scans and records inventory changes when goods enter or leave the warehouse.

[0024] Furthermore, the agricultural machinery tracking device 105 is installed on agricultural machinery such as tractors and harvesters, and has a built-in GPS module and operation status sensor. The GPS module records the location trajectory of the agricultural machinery at a frequency configured by the agricultural template, and the operation status sensor determines the operation status by monitoring parameters such as the engine speed and hydraulic system pressure of the agricultural machinery.

[0025] Furthermore, the blockchain tamper-proof label 106 adopts the form of QR code or RFID / NFC chip, which is activated when agricultural products are packaged. It is uniquely bound to the token ID of the batch of agricultural products on the blockchain through encryption algorithm. The label information includes tenant identifier and product traceability information.

[0026] The system also includes a data link and platform layer 200, which is communicatively connected to the physical sensing layer 100. The data link and platform layer 200 includes a data asset management platform 201, a data asset management toolbox 202, and a template configuration library 203. The data asset management platform 201 processes the original planting data to obtain a verified asset data package.

[0027] Furthermore, the data asset management platform 201 includes: a tenant management system 2011, which is used for tenant identity authentication, permission management, and resource allocation, with each tenant having independent data storage space and computing resources; a template engine 2012, which is used to store and manage multiple agricultural industry templates, each template containing data collection specifications, data processing rules, and business logic configurations; a data access gateway 2013, which is used to receive data uploaded by the physical sensing layer and route the data to the corresponding processing pipeline according to the tenant identifier; and a data processing engine 2014, which is used to clean, format, and perform quality verification on the collected raw agricultural data to ensure that the data conforms to the template specifications.

[0028] Furthermore, the data asset management toolkit 202 includes: a yield prediction model, which dynamically predicts the future yield of each plot based on the tenant's historical data, real-time environmental data, and crop growth model using an LSTM neural network algorithm; a pest and disease identification model, which automatically identifies signs of pests and diseases and assesses the asset health risk level by analyzing images transmitted by the multispectral UAV and the fixed high-definition camera through a convolutional neural network; and a growth status assessment model, which uses machine learning algorithms to classify and quantify crop growth and output a growth index score. Furthermore, the template configuration library 203 is used to store multiple predefined agricultural industry templates. Each agricultural industry template includes data collection parameter configuration, analysis model parameter settings, business rule definitions, and report template customization. Tenants can select or customize exclusive templates according to their own needs.

[0029] Specifically, the data link and platform layer 200 communicates with the physical sensing layer 100. This layer is the data hub and intelligent brain of the system, adopting a multi-tenant architecture to ensure data isolation among tenants while sharing basic services. The data link and platform layer 200 includes a data asset management platform 201, a data asset management toolbox 202, and a template configuration library 203.

[0030] Furthermore, such as Figure 3As shown, the Data Asset Management Platform 201, as the core data processing platform, mainly includes the following key components: Tenant Management 2011, Template Engine 2012, Data Access Gateway 2013, and Data Processing Engine 2014. Specifically: Tenant Management 2011 is responsible for tenant authentication, permission management, and resource allocation; each tenant has independent data storage space and computing resources. Template Engine 2012 is used to store and manage multiple agricultural industry templates, each template containing data collection specifications, data processing rules, and business logic configurations. Data Access Gateway 2013 is used to receive data uploaded from the physical sensing layer and route the data to the corresponding processing pipeline based on the tenant identifier. Data Processing Engine 2014 is used to clean, format, and perform quality verification on the collected raw agricultural data to ensure that the data conforms to the template specifications.

[0031] Furthermore, the Data Asset Management Toolkit 202 primarily provides shared intelligent analytics services for multi-tenant environments. Its core models are pre-trained on massive amounts of agricultural data and can be continuously optimized and fine-tuned based on tenants' specific historical data to ensure the accuracy of assessments. Specifically, this includes: a yield prediction model that uses LSTM neural network algorithms to dynamically predict future yields for each plot based on tenants' historical data, real-time environmental data, and crop growth models; a pest and disease identification model that analyzes images transmitted from drones and cameras using convolutional neural networks to automatically identify signs of pests and diseases and assess the asset health risk level; and a growth status assessment model that uses machine learning algorithms to classify and quantify crop growth, outputting a growth index score.

[0032] Furthermore, the template configuration library stores multiple predefined agricultural industry templates. Each template includes: data collection parameter configuration, analysis model parameter settings, business rule definitions, and report template customization. Tenants can select or customize exclusive templates according to their own needs.

[0033] Furthermore, this invention proposes a multi-tenant templated configuration technology for the agricultural industry based on a multi-tenant architecture. By pre-setting standardized agricultural industry templates, it enables rapid access and personalized configuration for different agricultural operators. Each agricultural industry template includes complete data collection specifications, analysis model parameters, and business rule definitions, allowing tenants to flexibly customize it according to crop type, planting scale, and other characteristics. This technology solves the problem of traditional systems being unable to adapt to diverse agricultural scenarios, achieving a balance between standardization and customization, and significantly reducing system deployment and maintenance costs.

[0034] Furthermore, this embodiment employs a dynamic asset valuation system based on a multimodal AI model, developing a dynamic asset valuation technology specifically for the planting industry. It integrates yield prediction models, pest and disease identification models, and growth status assessment models to form a multimodal AI analysis system. By processing time-series environmental data through LSTM neural networks, analyzing multispectral images through convolutional neural networks, and quantifying growth status using machine learning algorithms, real-time and accurate valuation of agricultural assets is achieved. This technology overcomes the lag inherent in traditional static valuation methods, providing a reliable value basis for token issuance and trading.

[0035] The system also includes a blockchain and tokenization layer 300, which is communicatively connected to the data link and platform layer 200. The blockchain and tokenization layer 300 includes an asset on-chain gateway 301, a multi-tenant blockchain network 302, and a smart contract factory 303. The asset on-chain gateway 301 performs data calculations on the verified asset data packets to achieve trusted evidence storage.

[0036] Furthermore, the asset on-chain gateway 301 includes: a data receiving module, which receives verified asset data packets from the data asset management platform 201, the verified asset data packets containing tenant identifier, asset identifier, timestamp, and business data; a hash calculation module, which performs hash calculation on the verified asset data packets using the SHA-256 algorithm and generates a hash value digital fingerprint; an IPFS storage interface, which uploads the verified asset data packets to the IPFS distributed storage system and obtains a content identifier; a transaction generation module, which packages the hash value digital fingerprint, content identifier, tenant identifier, and timestamp to generate an on-chain transaction data packet; and a blockchain interface module, which submits the on-chain transaction data packet to the corresponding on-chain partition through the blockchain API and receives a transaction receipt returned by the blockchain network for verification. The multi-tenant blockchain network 302 includes: a consensus management layer, which manages the consensus mechanism among multiple tenants; a data isolation layer, which ensures the privacy and security of each tenant's data through encryption technology and access control policies; and a cross-chain interaction module, which supports data exchange and value transfer between tenants under compliance requirements, enabling cross-chain asset circulation. The smart contract factory 303 is based on a template design and enables the rapid deployment of customized smart contracts for different tenants. The smart contract factory includes: issuance contract, compliance contract, and revenue distribution contract.

[0037] Specifically, such as Figure 2As shown, the blockchain and tokenization layer 300 adopts a multi-chain architecture, supporting multiple tenants to perform asset tokenization operations on a unified blockchain network, while ensuring the isolation and security of each tenant's data. This layer includes an asset on-chain gateway 301, a multi-tenant blockchain network 302, and a smart contract factory 303.

[0038] Furthermore, the asset on-chain gateway 301 serves as a trusted data bridge, connecting the data link with the platform layer 200 and the blockchain network. It mainly includes the following components: data receiving module 3011, hash calculation module 3012, IPFS storage interface 3013, transaction generation module 3014, and blockchain interface module 3015. Specifically: the data receiving module 3011 is responsible for receiving verified asset data packets from the data asset management platform. The data packets contain tenant identifiers, asset identifiers, timestamps, and business data; the hash calculation module 3012 uses the SHA-256 algorithm to perform hash calculations on the received data packets, generating unique hash value digital fingerprints to ensure data integrity and immutability; the IPFS storage interface 3013 uploads the verified asset data packets to the IPFS distributed storage system to obtain a content identifier (CID), realizing distributed storage and fast retrieval of data; the transaction generation module 3014 packages the hash value, content identifier, tenant identifier, and timestamp to generate a standardized on-chain transaction data packet; the blockchain interface module 3015 submits the on-chain transaction to the corresponding on-chain partition through the blockchain API and receives transaction receipts returned by the blockchain network for verification.

[0039] This invention constructs a complete trusted on-chain technology system for IoT data by establishing a reliable transmission and storage mechanism for IoT data to the blockchain. It achieves a reliable mapping from physical world data to the digital world through an asset on-chain gateway. Key technologies include: data fingerprint generation based on the SHA-256 algorithm, content addressing for IPFS distributed storage, and a partitioned consensus mechanism for multi-tenant blockchain networks. This mechanism ensures the integrity, immutability, and verifiability of agricultural asset data, providing a solid underlying asset backing for digital tokens and solving the trust deficiency problem in the traditional agricultural digitization process.

[0040] Furthermore, the multi-tenant blockchain network 302 adopts a partitioned architecture design, where each tenant has an independent on-chain data space while sharing the underlying blockchain infrastructure. It mainly comprises the following components: a consensus management layer 3021, a data isolation layer 3022, and a cross-chain interaction module 3023. Specifically, the consensus management layer 3021 manages the consensus mechanism among multiple tenants, employing an improved Byzantine fault-tolerant algorithm to ensure network consistency and availability; the data isolation layer 3022 uses encryption technology and access control policies to ensure the privacy and security of each tenant's data, preventing unauthorized access; and the cross-chain interaction module 3023 supports data exchange and value transfer between tenants while meeting compliance requirements, enabling cross-chain asset circulation.

[0041] Furthermore, the Smart Contract Factory 303, based on a template-based design, enables the rapid deployment of customized smart contracts for different tenants. It primarily includes the following contract types: Issuance Contract 3031, Compliance Contract 3032, and Profit Distribution Contract 3033. Specifically: Issuance Contract 3031 automatically generates compliant digital tokens based on the tenant's asset characteristics and business needs, supporting both fungible and non-fungible tokens; Compliance Contract 3032 executes tenant-specific KYC / AML rules to verify investor identity and transaction compliance, ensuring compliance with regulatory requirements; Profit Distribution Contract 3033 automatically executes profit distribution according to the distribution rules set by the tenant, supporting multiple distribution strategies and real-time settlement functions.

[0042] The system also includes an application and interaction layer 400, which is communicatively connected to the blockchain and tokenization layer 300. The application and interaction layer 400 includes a tenant management portal 401, a farmer and cooperative workbench 402, an investor service platform 403, and a regulatory agency view 404. The application and interaction layer 400 provides customized interactive interfaces for users with different roles and supports multi-tenant parallel access and business collaboration.

[0043] Furthermore, the tenant management portal 401 includes: a tenant registration and authentication module, used for online registration, identity verification, and permission allocation of new tenants; a template selection and configuration interface, providing visual template selection and parameter configuration tools, and supporting tenants to customize exclusive business templates according to their own needs; and a resource monitoring and management panel, used to display the tenant's resource usage, system operation status, and business data statistics in real time. The farmer and cooperative workbench 402 includes: an asset information management module, used to support farmers in maintaining basic data such as plot information, crop planting plans, and equipment files; a production monitoring dashboard, used to display sensor data, AI analysis results, and early warning information in real time; and a financing management interface, used to provide financing application, progress tracking, and fund usage management.

[0044] Furthermore, the investor service platform 403 includes: a project discovery engine that matches agricultural RDA projects based on investor preferences and risk tolerance using an intelligent recommendation algorithm; an asset monitoring panel that displays real-time status information, return data, and market performance of investment assets; and a risk assessment tool that provides professional investment risk analysis reports. The regulatory agency view 404 includes: a compliance review panel that monitors the compliance status of each tenant in real-time; a risk warning center that receives automatically pushed risk event and abnormal transaction alerts from the system, supporting rapid response and handling; and a statistical analysis tool that generates multi-dimensional regulatory statistical reports.

[0045] Specifically, the application and interaction layer 400 provides customized interactive interfaces for users with different roles, supporting multi-tenant parallel access and business collaboration. This layer includes a tenant management portal 401, a farmer and cooperative workbench 402, an investor service platform 403, and a regulatory agency view 404.

[0046] Furthermore, the tenant management portal 401 provides a unified tenant entry point and management functions, mainly including the following modules: tenant registration and authentication module, template selection and configuration interface, and resource monitoring and management panel. Specifically: the tenant registration and authentication module supports online registration, identity verification, and permission allocation for new tenants, ensuring the security of system access; the template selection and configuration interface provides a visual template selection and parameter configuration tool, allowing tenants to customize exclusive business templates according to their own needs; the resource monitoring and management panel displays the tenant's resource usage, system operating status, and business data statistics in real time, supporting flexible resource adjustments.

[0047] Furthermore, the Farmer and Cooperative Workbench 402 provides agricultural operators with comprehensive management functions, mainly including the following modules: Asset Information Management Module, Production Monitoring Dashboard, and Financing Management Interface. Specifically: The Asset Information Management Module supports farmers in maintaining basic data such as land plot information, crop planting plans, and equipment files; the Production Monitoring Dashboard can display sensor data, AI analysis results, and early warning information in real time, supporting multi-dimensional data visualization; the Financing Management Interface provides full-process services such as financing application, progress tracking, and fund usage management, supporting the selection of various financing options.

[0048] Furthermore, the Investor Service Platform 403 provides investors with professional investment management tools, primarily including the following modules: a project discovery engine, an asset monitoring panel, and a risk assessment tool. Specifically: the project discovery engine matches suitable agricultural RDA projects based on investor preferences and risk tolerance through intelligent recommendation algorithms; the asset monitoring panel displays real-time status information, return data, and market performance of investment assets, and supports customizable alert settings; the risk assessment tool provides professional investment risk analysis reports, including assessments of market risk, credit risk, and operational risk.

[0049] Furthermore, the Regulator View 404 provides regulators with a transparent regulatory interface, primarily comprising the following modules: a compliance review panel, a risk alert center, and statistical analysis tools. Specifically: the compliance review panel allows real-time monitoring of each tenant's compliance status, including KYC / AML implementation and transaction behavior monitoring; the risk alert center receives automatically pushed risk event and abnormal transaction alerts, supporting rapid response and handling; and the statistical analysis tools generate multi-dimensional regulatory statistical reports, supporting data export and visualization analysis.

[0050] This embodiment employs a smart contract-driven, end-to-end automated management method. By designing an automated business management architecture based on smart contracts, and through the collaborative work of issuance contracts, compliance contracts, and revenue distribution contracts, it achieves end-to-end automation from asset registration and token issuance to revenue distribution. Key technologies include: a templated contract factory mechanism, automated KYC / AML compliance verification, and an intelligent revenue distribution algorithm. This method significantly improves business processing efficiency, reduces the risk of human error, and ensures the transparency and reliability of business processes.

[0051] At the physical sensing layer, LoRa and Zigbee communication methods can be replaced by other low-power wide-area network technologies such as NB-IoT. At the blockchain layer, the multi-tenant partitioned architecture can also be implemented by deploying an independent chain for each tenant, although the cost is higher. At the AI ​​analysis layer, the LSTM model can be replaced by the Transformer time series model in some scenarios; the CNN model can be replaced by image recognition models such as Vision Transformer. At the data storage layer, IPFS can be replaced by other distributed storage protocols such as Arweave.

[0052] Therefore, through the collaborative work of the above four layers, this system achieves a complete mapping and reliable flow of agricultural assets from the physical world to the digital world. Data exchange and business collaboration between each layer are conducted through standardized interface protocols, forming a complete closed-loop system. The system adopts a modular design, supports functional expansion and business innovation, and can meet the digitalization needs of agricultural operators of different sizes.

[0053] Furthermore, the core problem this invention aims to solve is: how to build a reliable, automated, and efficient bridge to achieve seamless connection and value anchoring between dynamically changing agricultural assets in the physical world and financial activities in the digital world. To address this core problem, this invention provides a multi-layered system architecture and dedicated device integrating IoT, AI, and blockchain technologies, specifically designed to solve the following three key technical issues: First, it solves the problem of trust transfer between the physical and digital worlds: by building a trusted data bridge composed of various dedicated sensors, IoT gateways and asset on-chain gateways, it ensures that the full life cycle data of agricultural assets can be automatically and tamper-proofly collected and anchored to the blockchain, fundamentally solving the problem of insufficient credibility and public trust in the underlying asset data of digital tokens.

[0054] Second, it addresses the issue of lagging dynamic asset valuation and risk monitoring: by introducing big data AI analysis tools, it can intelligently analyze real-time collected environmental and crop growth data to achieve dynamic prediction and automatic early warning of risks such as future yield, pests and diseases, and drought. This solves the problem of the disconnect between the value of on-chain tokens and the real state of the underlying assets, and provides the market with real-time and accurate risk pricing basis.

[0055] Third, it addresses the issues of fragmented and inefficient business processes. By deploying a blockchain and tokenization layer that includes smart contracts such as issuance contracts, compliance contracts, and revenue distribution contracts, key business processes such as asset registration, token issuance, compliance review, and revenue distribution are automated, overcoming the inefficiencies and high costs caused by reliance on manual operations in existing technical solutions.

[0056] This system can achieve the following beneficial technical effects: First, it establishes a trusted data bridge, effectively solving the challenge of trust transfer between the physical and digital worlds. This invention employs a trusted data collection and transmission chain composed of various specialized sensors, IoT gateways, and asset on-chain gateways. By generating an immutable data fingerprint anchored to the blockchain through a hash calculation module, it ensures the authenticity and integrity of agricultural asset data throughout its entire lifecycle during collection, transmission, and storage. This provides the on-chain digital token with a solid and verifiable underlying asset backing, greatly enhancing investor trust and participation, fundamentally overcoming the trust deficiency problem caused by insufficient data credibility in existing technologies.

[0057] Secondly, it enables dynamic asset valuation and real-time risk monitoring, significantly improving risk pricing capabilities and market efficiency. This invention introduces a big data AI analysis platform integrating AI models for yield prediction, pest and disease identification, and growth status assessment. This platform continuously and intelligently analyzes real-time collected environmental and crop growth data, dynamically predicting yield, accurately assessing asset risk, and issuing timely warnings. This allows the value of on-chain tokens to reflect the real-time and accurate changes in the underlying asset's state, providing a reliable basis for risk pricing in the market and effectively solving the problem of token value being disconnected from the actual asset state due to valuation lags in existing technologies.

[0058] Third, it achieves automated and closed-loop management of business processes, significantly improving operational efficiency and reducing operational risks and costs. Because this invention deploys a smart contract factory including issuance contracts, compliance contracts, and profit distribution contracts, it automates and standardizes key financial activities such as asset registration, token issuance, compliance review, and profit distribution. This greatly reduces reliance on manual operations in business processes, avoiding inefficiency, frequent errors, and moral hazards caused by human intervention, forming an efficient, transparent, and reliable business closed loop. It successfully solves the problems of high operating costs and low efficiency caused by fragmented business processes and reliance on manual labor in existing technologies.

[0059] Fourth, it provides a highly scalable multi-tenant and templated architecture, enhancing the system's versatility and scalability. Because this invention incorporates multi-tenant support and agricultural industry template configuration mechanisms at each system level, agricultural operators of different sizes and types can quickly access and customize digital solutions to meet their specific needs. This design not only ensures the isolation and security of data among tenants but also achieves service standardization and rapid deployment through templates, significantly reducing the system's usage threshold and operational complexity, thus laying a solid technical foundation for the large-scale promotion of RDA in the planting industry.

[0060] In summary, this invention, through the deep integration and synergistic operation of technologies at various levels, not only solves individual technical pain points but also constructs a complete digital ecosystem for agricultural assets, achieving efficient transformation from "data to trust to value." By building a complete and trustworthy data bridge and an intelligent risk control system, it realizes the deep integration of agricultural assets and digital finance.

[0061] Example 2 This embodiment also provides a method for supporting RDA in the planting industry based on the Internet of Things and blockchain. This method is implemented based on the aforementioned system architecture, such as... Figure 5 As shown, the method includes: Step 1: Initialize system configuration and register tenants.

[0062] Specifically, system initialization and tenant registration involve the following steps: First, system initialization configuration is performed, a multi-tenant blockchain network is deployed, and an agricultural industry template library is pre-configured. New tenants complete registration and authentication through the tenant management portal, and the system assigns each tenant a unique digital identity and resource space. Tenants select or customize agricultural industry templates based on their business needs. These templates include data collection parameters, analysis model configurations, and business rule settings. The system automatically deploys the corresponding data processing pipelines and smart contracts based on the template configuration.

[0063] Step 2: Collect raw agricultural data through multiple physical sensing devices and transmit the collected data to the data access gateway via the Internet of Things network.

[0064] Specifically, asset data acquisition and preprocessing: Physical sensing layer devices collect data according to the parameters configured in the template. Environmental monitoring sensor groups collect soil and atmospheric environmental data at preset frequencies; crop growth monitoring devices perform aerial and fixed-point photography tasks as planned; intelligent water and fertilizer integration devices record irrigation and fertilization operation data; warehouse monitoring devices monitor changes in the storage environment; and agricultural machinery tracking devices record operational status in real time. All collected data is transmitted to the data access gateway via the Internet of Things network, with tenant identifiers embedded in the data packets to ensure data isolation.

[0065] Step 3: Through the data asset management platform, perform data intelligence analysis and value assessment on the collected raw planting data to obtain a verified asset data package.

[0066] Specifically: Data intelligent analysis and value assessment: The data asset management platform cleans, formats, and verifies the quality of the collected raw crop data. The data processing engine standardizes the data according to template specifications to ensure data quality and consistency. The data asset management toolkit calls upon corresponding analytical models: the yield prediction model predicts future yields based on environmental data and growth models; the pest and disease identification model analyzes image data to assess health risks; and the growth status assessment model quantifies and scores crop growth. After the analysis results are verified, an asset value assessment report is generated.

[0067] Step 4: Use the asset on-chain gateway of blockchain and tokenization layer to perform trusted data on-chain and trusted evidence storage.

[0068] Specifically, the trusted data on-chain and notarization process is as follows: The asset on-chain gateway receives verified asset data packets, generates data fingerprints through the hash calculation module, and stores the verified asset data packets in the IPFS distributed storage system to obtain content identifiers. The transaction generation module packages the hash value digital fingerprint, content identifier, tenant identifier, and timestamp to generate an on-chain transaction data packet. The blockchain interface module submits the on-chain transaction data packet to the corresponding partition of the multi-tenant blockchain network. The network confirms the transaction through a consensus mechanism and permanently records the data hash value on the blockchain, completing trusted notarization.

[0069] Step 5: Utilize the smart contract factory of blockchain and tokenization layer to complete the issuance of digital tokens and asset management.

[0070] Specifically, digital token issuance and asset management: The smart contract factory deploys customized issuance contracts based on tenant templates, automatically generating digital tokens based on on-chain asset valuation results. The issuance contracts support both fungible and non-fungible tokens, with token quantity and value strictly corresponding to the underlying assets. Compliance contracts execute KYC / AML verification to ensure token issuance and trading comply with regulatory requirements. The system establishes a complete lifecycle management file for each token, recording its issuance, circulation, and change history.

[0071] Step 6: Display sensor data and analysis results in real time through the production monitoring dashboard in the application and interaction layer, and issue risk warnings through the risk warning center.

[0072] Specifically, the system provides real-time monitoring and risk warnings: continuously monitors changes in asset status and displays sensor data and analysis results in real time through a production monitoring dashboard. When anomalies are detected, the system automatically triggers a risk warning mechanism: abnormal environmental parameters trigger an environmental warning; pest and disease identification triggers a health warning; and market fluctuations trigger a value warning. Warning information is pushed to relevant stakeholders through multiple channels, supporting rapid response and risk management.

[0073] Step 7: Investors discover and select investment targets through the investor service platform, complete token transactions, and automatically execute profit distribution operations through the profit distribution contract.

[0074] Specifically, in terms of transaction execution and profit distribution: Investors discover and select investment targets through the investor service platform and complete token transactions under the supervision of compliant contracts. Transaction data is recorded on the blockchain in real time, ensuring transparency and traceability. When assets generate returns, the profit distribution contract automatically executes the distribution operation, allocating the returns to token holders according to preset rules. The distribution process is fully automated, reducing human intervention and improving execution efficiency.

[0075] Step 8: Regulatory agencies monitor the system's operational status in real time through the regulatory agency view and conduct audit trails.

[0076] Specifically, regulatory compliance and audit trail: Regulatory agencies monitor the system's operational status in real time through an agency view, a compliance review panel displays the compliance status of each tenant, and a risk warning center receives alerts for abnormal events. Statistical analysis tools generate multi-dimensional regulatory reports to support regulatory decision-making. All operation records and data changes are permanently stored on the blockchain, forming a complete audit trail chain that meets regulatory audit requirements.

[0077] Step 9: Consumers can verify the origin and realize the value by scanning the blockchain tamper-proof label on the product packaging.

[0078] Specifically, traceability verification and value realization: Consumers can scan the blockchain tamper-proof label on product packaging to query data throughout the entire lifecycle from planting to distribution, verifying the authenticity and quality of the product. Token holders manage their assets through their digital wallets (as external components interacting with the system), viewing asset status and returns in real time. When assets meet predetermined conditions, the system supports token redemption or physical delivery, realizing the final conversion of asset value.

[0079] The method in this embodiment establishes a complete closed loop for digital management of agricultural RDA through the cyclical execution of the above nine steps. Each step is based on a multi-tenant architecture design, supporting parallel operation by multiple agricultural operators while ensuring data isolation and business security. The system adopts standardized interface protocols and modular functional design, possessing good scalability and adaptability, and can meet the digitalization needs of agricultural assets of different scales and types.

[0080] Example 3 This embodiment also provides an RDA support method for the planting industry based on the Internet of Things and blockchain. The implementation background is an asset tokenization project of a konjac planting base. Specifically, a konjac professional cooperative owns an 800-mu standardized konjac planting base, mainly growing the flower konjac variety. The cooperative faces problems such as financing difficulties, extensive production management, high market risks, and difficulties in product quality traceability. By adopting the RDA support system of this invention, the planting base is tokenized as an asset, with a planned financing of 5 million yuan for the construction of an intelligent irrigation system and the expansion of production scale.

[0081] The specific implementation process is as follows: like Figure 4 As shown, during the system initialization phase, the cooperative completes registration and authentication through the tenant management portal, selecting the "Agriculture" professional template. The system assigns a unique digital identity "MY-800-2024-001" to the cooperative and configures personalized parameters: soil monitoring frequency is once per hour, drone multispectral image acquisition is twice per week, and soil EC and pH values ​​are monitored twice daily. The system automatically deploys the corresponding data processing pipeline according to the template configuration and creates an independent on-chain data partition at the blockchain layer.

[0082] During the data acquisition phase, the physical sensing layer equipment conducted monitoring according to its configured parameters. Specific data collected by the environmental monitoring sensor group included: soil moisture sensors recorded soil volumetric water content fluctuating between 25% and 30%; soil temperature sensors showed the cultivated layer temperature remained between 18 and 22°C; soil EC value sensors monitored conductivity within the range of 0.8-1.2 mS / cm; and soil pH sensors recorded pH values ​​stable between 6.0 and 6.5. Multispectral drones performed aerial photography missions every Monday and Thursday, and the collected image data showed that the konjac leaf area index increased from 1.2 in the early stages to 3.8 at its peak, and the normalized difference vegetation index (NDVI) of the canopy reached 0.75. Daily image data collected by fixed high-definition cameras was used to monitor the growth status of the konjac plant, and early symptoms of disease were detected three times using image recognition technology.

[0083] During the data processing and analysis phase, the data asset management platform cleans and standardizes the collected raw agricultural data. The yield prediction model, based on growth data, predicts a yield of 240 tons for the current season. The pest and disease identification model indicates a "moderate" risk level for soft rot, and the growth status assessment model gives a comprehensive growth index score of 82. Based on these analysis results, the system generates an asset valuation report, predicting a total asset value of 5 million yuan.

[0084] In the data notarization stage, the asset on-chain gateway receives the verified asset data packet, generates a data fingerprint "7d8e9f0a1b2c3d4e5f6a7b8c9d0e1f2" using the SHA-256 algorithm, and uploads the verified asset data packet to the IPFS distributed storage system to obtain the content identifier CID "QmPh4N8tYyJkLmNoPqRsTuVwXyZ". The transaction generation module packages this information to generate an on-chain transaction data packet, submits it to the multi-tenant blockchain network through the blockchain interface, and finally obtains the transaction hash "0x234bcd5678ef9012ab34cd56ef789012ab345cde", completing the trusted notarization.

[0085] During the token issuance phase, the smart contract factory deploys the issuance contract and automatically issues "Konjac Revenue Right Token" (MYT) based on the evaluation results of the stored evidence. The total amount of 5 million tokens is MYT, with each token corresponding to a financing amount of 1 yuan.

[0086] During the monitoring and early warning phase, the system continuously monitors asset status. When environmental monitoring data shows that rainfall exceeds 50mm for three consecutive days, the system automatically triggers an environmental early warning; when the pest and disease identification model detects leaf spot symptoms, the system immediately issues a health warning; when market price fluctuations exceed 15%, the system triggers a value warning. All early warning information is pushed to relevant parties in real time through multiple channels.

[0087] During the transaction execution phase, investors participate in token subscription after completing KYC verification through the platform. All transaction data is recorded on the blockchain in real time.

[0088] During the revenue distribution phase, the actual yield of konjac reached 252 tons, exceeding expectations by 5%. RFID scanners in the storage monitoring system recorded the warehousing process, and temperature and humidity sensors ensured the storage environment met standards. Ultimately, the konjac was sold at 31,000 yuan per ton, generating a total revenue of 7.812 million yuan. The revenue distribution contract was automatically executed.

[0089] During the traceability verification stage, a blockchain anti-tamper label is affixed to the final product packaging. Consumers can scan the QR code to query complete traceability information, including environmental data storage records, growth image AI analysis reports, pest and disease control records, harvest and storage time, quality inspection reports, etc. All information is verified for authenticity through blockchain hash values.

[0090] Regarding regulatory compliance, regulatory agencies monitor project operations in real time through a regulatory view. Statistics show that seven alerts were triggered, all of which were addressed promptly, forming a complete audit trail.

[0091] Implementation Results: Through the implementation of this system, the konjac planting cooperative successfully digitized its assets, significantly improving financing efficiency. Investors can view asset status in real time through the platform, making investment decisions based on reliable data and greatly enhancing transparency. This project fully demonstrates the technical effectiveness of this invention in addressing trust establishment, dynamic valuation, and business process optimization in the process of agricultural asset digitization.

[0092] The above-described one or more technical solutions in the embodiments of the present invention have at least one or more of the following technical effects: This invention provides an IoT and blockchain-based RDA support system and method for agricultural production. The system includes a physical sensing layer comprising multiple physical sensing devices and a blockchain tamper-proof tag, wherein the physical sensing devices are used to collect raw agricultural data; a data link and platform layer, which is communicatively connected to the physical sensing layer and includes a data asset management platform, a data asset management toolkit, and a template configuration library, wherein the data asset management platform processes the raw agricultural data to obtain verified asset data packages; and a blockchain and tokenization layer, which is also communicatively connected to the data link and platform layer, and includes an asset on-chain gateway, a multi-tenant blockchain network, and a smart contract factory, wherein the asset on-chain gateway verifies the raw agricultural data. The subsequent asset data package undergoes data calculation to achieve trusted evidence storage. The application and interaction layer communicates with the blockchain and tokenization layer. This layer includes a tenant management portal, a farmer and cooperative workbench, an investor service platform, and a regulatory agency view. The application and interaction layer provides customized interactive interfaces for users with different roles and supports multi-tenant parallel access and business collaboration. This solves the technical problems of trust transfer between the physical and digital worlds, lagging dynamic asset valuation and risk monitoring, and fragmented and inefficient business processes in existing technologies. It establishes a trusted data bridge, enables dynamic asset valuation and real-time risk monitoring, significantly improves risk pricing capabilities and market efficiency, and achieves automated and closed-loop management of business processes, greatly improving operational efficiency and reducing operational risks and costs.

[0093] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the invention.

[0094] Obviously, those skilled in the art can make various modifications and variations to the embodiments of the present invention without departing from the spirit and scope of the embodiments of the present invention. Thus, if these modifications and variations to the embodiments of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention also intends to include these modifications and variations.

Claims

1. A planting RDA support system based on the Internet of Things and blockchain, characterized in that, The system includes: The physical sensing layer includes multiple physical sensing devices and a blockchain tamper-proof tag, wherein the multiple physical sensing devices are used to collect raw agricultural data. The data link and platform layer is communicatively connected to the physical sensing layer. The data link and platform layer includes a data asset management platform, a data asset management toolbox, and a template configuration library. The original planting data is processed through the data asset management platform to obtain a verified asset data package. The blockchain and tokenization layer is communicatively connected to the data link and platform layer. The blockchain and tokenization layer includes an asset on-chain gateway, a multi-tenant blockchain network, and a smart contract factory. The asset on-chain gateway performs data calculations on the verified asset data packets to achieve trusted evidence storage. The application and interaction layer communicates with the blockchain and tokenization layer. The application and interaction layer includes a tenant management portal, a farmer and cooperative workbench, an investor service platform, and a regulatory agency view. The application and interaction layer provides customized interactive interfaces for users with different roles and supports multi-tenant parallel access and business collaboration.

2. The agricultural RDA support system based on the Internet of Things and blockchain as described in claim 1, characterized in that, The plurality of physical sensing devices specifically include: The environmental monitoring sensor group includes soil moisture sensor, soil temperature sensor, soil EC value sensor, soil pH value sensor, air temperature and humidity sensor, light intensity sensor and carbon dioxide concentration sensor installed in the field, and is connected to the data asset management platform via LoRa, Zigbee or 4G, 5G network. Each sensor's data packet contains a tenant identifier to ensure data isolation. A crop growth monitoring device includes a multispectral drone and a fixed high-definition camera set up in the field. The multispectral drone is used to perform aerial photography and collect multispectral images, and the fixed high-definition camera is used to collect images of crop growth status. The intelligent water and fertilizer integrated device includes a controller, an irrigation valve, a fertilizer pump, and a flow sensor. The controller is used to control the start and stop of the irrigation valve and the fertilizer pump, and the flow sensor is used to monitor the irrigation amount and fertilizer amount in real time. A warehouse monitoring device, which is installed in a grain warehouse or cold storage, includes a temperature and humidity sensor and an RFID scanner for inventory counting. The temperature and humidity sensor is used to collect environmental data, and the RFID scanner is used to automatically scan and record inventory changes when goods enter or leave the warehouse. An agricultural machinery tracking device is installed on the agricultural machinery and has a built-in GPS module and operation status.

3. The agricultural RDA support system based on the Internet of Things and blockchain as described in claim 1, characterized in that, The data asset management platform includes: Tenant management is used for tenant authentication, access control, and resource allocation. Each tenant has independent data storage space and computing resources. The template engine is used to store and manage multiple agricultural industry templates, each template containing data collection specifications, data processing rules, and business logic configurations; A data access gateway is used to receive data uploaded by the physical sensing layer and route the data to the corresponding processing pipeline according to the tenant identifier. The data processing engine is used to clean, format, and perform quality checks on the collected raw agricultural data to ensure that the data conforms to the template specifications.

4. The agricultural RDA support system based on the Internet of Things and blockchain as described in claim 2, characterized in that, The data link and platform layer also includes: The data asset management toolkit includes: A yield prediction model is used to dynamically predict the future yield of each plot based on the tenant's historical data, real-time environmental data, and crop growth model, using an LSTM neural network algorithm. A pest and disease identification model, which analyzes images transmitted by the multispectral drone and the fixed high-definition camera through a convolutional neural network to automatically identify signs of pests and diseases and assess the health risk level of assets; A growth status assessment model, which uses machine learning algorithms to classify and quantify crop growth and output a growth index score; The template configuration library is used to store multiple predefined agricultural industry templates. Each agricultural industry template includes data collection parameter configuration, analysis model parameter settings, business rule definitions, and report template customization. Tenants can select or customize exclusive templates according to their own needs.

5. The agricultural RDA support system based on the Internet of Things and blockchain as described in claim 1, characterized in that, The blockchain and tokenization layer also includes: The asset on-chain gateway includes: The data receiving module is used to receive verified asset data packets from the data asset management platform. The verified asset data packets include tenant identifier, asset identifier, timestamp, and business data. The hash calculation module uses the SHA-256 algorithm to perform hash calculations on the verified asset data packet and generates a hash value digital fingerprint. The IPFS storage interface is used to upload the verified asset data packet to the IPFS distributed storage system and obtain a content identifier; Transaction generation, wherein the transaction generation is used to package the hash value digital fingerprint, content identifier, tenant identifier and timestamp to generate an on-chain transaction data package; The blockchain interface module submits the on-chain transaction data packet to the corresponding on-chain partition through the blockchain API and receives the transaction receipt returned by the blockchain network for verification. The multi-tenant blockchain network includes: Consensus management layer, which is used to manage the consensus mechanism among multiple tenants; A data isolation layer, which uses encryption technology and access control policies to ensure the privacy and security of each tenant's data; The cross-chain interaction module supports data exchange and value transfer between tenants under compliance requirements, enabling cross-chain asset circulation. The smart contract factory is based on a template-based design, enabling rapid deployment of customized smart contracts for different tenants. The smart contract factory includes: issuance contract, compliance contract, and revenue distribution contract.

6. The agricultural RDA support system based on the Internet of Things and blockchain as described in claim 1, characterized in that, The application and interaction layer also includes: The tenant management portal includes: The tenant registration and authentication module is used for online registration, identity verification, and permission allocation of new tenants. The template selection and configuration interface provides a visual template selection and parameter configuration tool, and supports tenants to customize exclusive business templates according to their own needs. The resource monitoring and management panel is used to display the tenant's resource usage, system operating status, and business data statistics in real time. The work platform for farmers and cooperatives includes: The asset information management module is used to support farmers in maintaining basic data such as basic land information, crop planting plans, and equipment files. A production monitoring dashboard, which is used to display sensor data, AI analysis results and early warning information in real time; The financing management interface is used to provide financing application, progress tracking, and fund usage management.

7. The agricultural RDA support system based on the Internet of Things and blockchain as described in claim 1, characterized in that, The application and interaction layer also includes: The investor service platform includes: The project discovery engine matches agricultural RDA projects based on investor preferences and risk tolerance using intelligent recommendation algorithms. An asset monitoring panel is used to display the status information, return data and market performance of investment assets in real time. Risk assessment tools, which are used to provide professional investment risk analysis reports; The regulatory agency view includes: The compliance review panel is used to monitor the compliance status of each tenant in real time. The risk warning center is used to receive risk events and abnormal transaction alerts automatically pushed by the system, and supports rapid response and handling. Statistical analysis tools are used to generate multi-dimensional regulatory statistical reports.

8. A method for supporting RDA in agriculture based on the Internet of Things and blockchain, characterized in that, The method includes: Step 1: Initialize system configuration and register tenants; Step 2: Collect raw agricultural data through multiple physical sensing devices and transmit the collected data to the data access gateway via the Internet of Things network; Step 3: Conduct data intelligence analysis and value assessment on the collected raw planting data through the data asset management platform to obtain a verified asset data package; Step 4: Utilize the asset on-chain gateway of the blockchain and tokenization layer to perform trusted data on-chaining and trusted evidence storage; Step 5: Utilize the smart contract factory of blockchain and tokenization layer to complete digital token issuance and asset management; Step 6: Display sensor data and analysis results in real time through the production monitoring dashboard in the application and interaction layer, and issue risk warnings through the risk warning center; Step 7: Investors discover and select investment targets through the investor service platform, complete token transactions, and automatically execute profit distribution operations through the profit distribution contract; Step 8: Regulatory agencies monitor the system's operational status in real time through the regulatory agency view and conduct audit trails; Step 9: Consumers can verify the origin and realize the value by scanning the blockchain tamper-proof label on the product packaging.

9. The agricultural RDA support method based on IoT and blockchain as described in claim 8, characterized in that, Step 4 specifically includes: The asset on-chain gateway receives verified asset data packets, generates hash value data fingerprints through the hash calculation module, stores the verified asset data packets in the IPFS distributed storage system to obtain content identifiers, and then packages the hash value data fingerprints, content identifiers, tenant identifiers, and timestamps into on-chain transaction data packets through the transaction generation module. Finally, the blockchain interface module submits the on-chain transaction data packets to the corresponding partition of the multi-tenant blockchain network. The network confirms the transaction through the consensus mechanism and permanently records the data hash value on the blockchain, completing trusted evidence storage.

10. The agricultural RDA support method based on IoT and blockchain as described in claim 8, characterized in that, Step 6 also includes: When an anomaly is detected, the system automatically triggers a risk warning mechanism. Anomalies in environmental parameters trigger an environmental warning; pest and disease identification triggers a health warning; and market fluctuations trigger a value warning. Warning information is pushed through multiple channels to support rapid response and risk management.

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