LandChain
Blockchain based land registry project which enhances transparency and prevents corruption in land dealings by automatically tracking low priced deals
Created on 25th February 2024
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LandChain
Blockchain based land registry project which enhances transparency and prevents corruption in land dealings by automatically tracking low priced deals
The problem LandChain solves
The blockchain-based land registry project addresses several critical issues in land dealings, particularly in regions like India where corruption and opacity are prevalent in the real estate sector:
Enhanced Transparency: By leveraging blockchain technology, the project ensures that all land transactions are recorded immutably on a transparent and publicly accessible ledger. This transparency helps to mitigate fraudulent activities and reduces the chances of corruption in land dealings.
Prevention of Underreporting and Tax Evasion: One of the significant problems in land transactions is the underreporting of property prices to evade taxes, such as stamp duty. By automatically tracking and flagging suspiciously low-priced deals using machine learning algorithms, the project helps prevent tax evasion and ensures that the government receives its rightful revenue.
Increased Accountability: The system introduces accountability by allowing inquiries to be raised in case of suspiciously low-priced transactions. This discourages fraudulent practices and holds individuals accountable for their actions, thereby promoting honesty and integrity in the real estate sector.
Challenges we ran into
Challenges Encountered:
React-Solidity Integration:
Dealing with errors while connecting the React frontend with Solidity contracts.
Facing difficulties in deploying contracts locally using Hardhat and encountering issues with promises in ethers.js library.
Machine Learning Integration:
Struggling with data preprocessing for the ML model, including handling missing values and ensuring data consistency.
Experimenting with various ML algorithms and hyperparameters to optimize model performance.
Finding ways to integrate ML models with the blockchain system while ensuring data privacy and security.
Overcoming Challenges:
React-Solidity Integration:
Debugging extensively and utilizing developer tools to identify and resolve integration issues.
Seeking guidance from documentation and online communities for troubleshooting solutions.
Machine Learning Integration:
Adopting an iterative approach to model development, starting with simple prototypes and gradually refining them.
Collaborating with domain experts and team members to share knowledge and overcome technical hurdles.
Conducting rigorous testing and validation to ensure the reliability and robustness of ML models.
Tracks Applied (1)