GreenLand: A Secure Land Registration Scheme for Blockchain and AI-Enabled Agriculture Industry 5.0

Aim:

        Our study aims to introduce a Blockchain-Enabled Land Registration System powered by AI to ensure secure, transparent, and tamper-proof land ownership records in agriculture, enhancing trust and reducing fraud in the agricultural sector.

Abstract:

         This project aims to develop a secure and transparent land registration system for the agricultural sector using blockchain and AI technologies. Land ownership is a critical aspect of sustainability and development in agriculture, but the current land registration systems are often vulnerable to fraud and manipulation. By utilizing blockchain, we ensure that land records are immutable and tamper-proof, providing a trustworthy system for verifying ownership. AI models such as logistic regression, support vector machines, and random forests are used to detect and identify fraudulent data before it is entered into the blockchain. Only verified, non-fraudulent land data is stored on the blockchain, minimizing unnecessary computational load. Smart contracts are incorporated for land data validation, ensuring efficiency, accuracy, and security in the process. Additionally, non-fraudulent land information is securely stored on the Interplanetary File System (IPFS), and its hash is recorded on the blockchain, ensuring both accessibility and protection. The entire system undergoes a rigorous assessment for performance, including evaluating AI accuracy, blockchain scalability, and smart contract vulnerability, guaranteeing a robust and efficient solution. The AgriSafe system aims to provide a transparent, fraud-resistant method for land registration, which fosters trust among stakeholders and significantly reduces the risks of land disputes and ownership fraud in agriculture.

Existing System:

         The existing system utilizes blockchain and AI-based technologies to address land registration challenges in agriculture. Blockchain is used to store land records in an immutable and secure manner, ensuring that ownership is verifiable and protected. The system incorporates AI models such as logistic regression, support vector machines, and random forests to detect and classify fraudulent land data before it is recorded. Only verified, non-fraudulent data is stored, which reduces computational load and ensures the integrity of the land registry. Smart contracts are employed for data validation, improving efficiency and security. Additionally, non-fraudulent land data is stored on the Interplanetary File System (IPFS), with its hash recorded on the blockchain to ensure data protection and easy access. The system also includes performance assessments for AI accuracy, blockchain scalability, and smart contract security testing, aiming to provide a reliable land registration solution.

Disadvantages:

        The existing system still relies on traditional AI models, such as logistic regression and support vector machines, which may not handle complex and large-scale data as effectively. It lacks real-time monitoring capabilities, making it slower to detect fraud and address issues promptly. Additionally, the system’s scalability may be limited, and the integration with external registries or GIS could be challenging, affecting its ability to adapt to future growth and changing regulations.

Proposing System:

        The proposed system enhances the existing system solution by integrating advanced features for stronger land registration, improved performance, and broader applicability across agriculture and other industries. AI models, including XGB and LGBM, will improve fraud detection and handle more complex data. A real-time monitoring system will detect and alert authorities to potential fraud, ensuring quicker intervention. Dynamic smart contracts will adapt to changing laws and improve data validation. Interoperability with external land registries and GIS will enhance accuracy.

           Scalability improvements, such as sharding, will handle increased data volume. Decentralized identity management ensures privacy and security for landowners. Advanced vulnerability detection tools will enhance smart contract security. AI will also promote sustainable land practices. The system will feature an intuitive interface for better user experience and easier access to land records. These improvements ensure a more secure, efficient, and scalable solution for land registration.

Advantages:

          The proposed system offers enhanced security and fraud detection through advanced AI models such as XGB and LGBM, along with real-time monitoring, allowing for quicker intervention. It provides greater adaptability with dynamic smart contracts and interoperability with external databases, improving accuracy in land records. The system’s scalability and decentralized identity management ensure robust performance, privacy, and a seamless user experience for landowners and authorities alike.