The problem Impact Chain solves

Decentralized Platform for Indian Dataset Collection

Our platform revolutionizes the way Indian datasets are funded, collected, and validated — all through decentralized, blockchain-powered technology.

Secure and Transparent Funding

Researchers propose data collection initiatives, and DAO members vote to approve causes. Donors provide funding in crypto, ensuring every donation is traceable and reaches verified NGOs connected to hospitals, old age homes, and orphanages. This eliminates uncertainty and enhances accountability.

Trustworthy Data Collection

NGOs collect datasets related to approved causes and store metadata and hashes on-chain. This makes the data tamper-proof and verifiable, guaranteeing authenticity and reliability for research, analysis, and decision-making.

Decentralized Data Validation

Validators review datasets and stake tokens to endorse their credibility:
If datasets are credible, validators are rewarded with tokens.
If datasets are fraudulent, validators' stakes are slashed.
This incentivized system promotes integrity and ensures only high-quality data is approved.

Community-Driven Governance

All decisions — from approving proposals to allocating funds — are made through decentralized voting by DAO members. This ensures a transparent, democratic process where all stakeholders have a voice.

Incentivized Participation

Contributors, including donors, researchers, and validators, are rewarded with:
NFTs and POAPs for their efforts.
These rewards recognize contributions and encourage active community participation.

Anonymous Donations

For those valuing privacy, the platform supports secure, anonymous crypto donations, ensuring discreet contributions while maintaining transparency on fund usage.

Challenges we ran into

One significant challenge we faced during the project was integrating the Coinbase SDK. We were more familiar with tools like RainbowKit than Wagmi, which made the process more complex and required additional effort to adapt and understand the SDK’s intricacies.

Additionally, there was a scarcity of testnet MATIC tokens for the Polygon PoS testnet, which delayed our ability to test features effectively. We resolved this by exploring various faucets and requesting support from the developer community to acquire sufficient testnet funds.

Another major hurdle was creating a DAO. Integrating all components with governance tokens and ensuring smooth functionality was more challenging than anticipated. We had to spend considerable time debugging, fine-tuning smart contracts, and coordinating between various tools to make everything work seamlessly. Despite these challenges, our persistence and reliance on documentation and community support helped us overcome the issues successfully.

We also planned to integrate our AI model, which was fully developed and ready for deployment. The goal was to enhance the platform with AI-driven insights and functionalities, adding another layer of innovation to the project. Unfortunately, as we progressed, the sheer volume of tasks, unexpected complexities, and persistent bugs made it difficult to allocate the time and resources needed for this integration. The debugging process for smart contracts, SDK adaptations, and governance token implementations demanded our full attention, leaving little room to properly incorporate the AI model. Despite our best efforts, we had to prioritize core functionalities to ensure a seamless user experience. Nevertheless, we remain committed to integrating the AI model in future iterations, confident that it will significantly enhance the platform's capabilities.

Additional Features

AI Model Integration: We intended to integrate an AI model for dataset analysis and prediction, allowing for automated insights and recommendations. This could have enhanced the decision-making process, helping contributors and validators quickly assess the value of datasets.

Chatbot Integration: A chatbot was planned to assist users in navigating the platform, answer common questions, and provide real-time updates. This would have added a layer of user engagement and streamlined interactions.

Consensus Mechanisms: While we implemented basic voting functionality, we couldn’t fully implement a robust decentralized consensus mechanism. A more dynamic, fair voting system for proposal validation and decision-making would ensure better governance and fairness across the platform.

Governance Tokens: We started developing governance tokens, but time constraints limited their implementation. Improving the tokenomics and creating a more detailed system for governance and rewards could significantly enhance user engagement and incentivization.

Multi-Chain Capability: We envisioned expanding the platform to support multiple blockchains, such as Polygon and Ethereum, to increase accessibility and scalability. This would have helped reach a broader audience and improved cross-chain data integrity.

Anon Aadhar Integration: We wanted to integrate Anon Aadhar to validate users without compromising their privacy. This could have provided a seamless identity verification process for users while maintaining security.

Graph and Subgraph Implementation: We planned to integrate graphs and subgraphs to make data querying more efficient. This would have enabled better performance in querying datasets, making it easier for users to find valuable information.

Future Scope: Beyond the hackathon, the project has immense scope for growth, including better AI-driven validation, enhanced consensus mechanisms, and a stronger business model.