JustETH
Just ETH is an innovative, food rating app with dynamic voting power by redefining restaurant ratings through blockchain and AI.
About
The problem it solves Tamper-Proof Reviews with Blockchain: By leveraging blockchain technology, all reviews and ratings are securely recorded on an immutable ledger. This prevents tampering, deletion, or manipulation of reviews, ensuring that all feedback is genuine and trustworthy. Dynamic Voting Power: The app introduces a dynamic voting system where each user's influence on restaurant ratings is adjusted based on several factors. Food Preference Similarity, Spending Habits, Review Reliability, AI Confidence Level. Artificial Intelligence Integration: AI algorithms personalize user experiences by recommending dishes and restaurants that match their stored preferences. AI also assists in analyzing reviews for authenticity and sentiment, enhancing the overall reliability of the platform. Transparency and Fairness: With open algorithms and blockchain-backed data, JustETH ensures that the rating process is transparent. Users can see how ratings are calculated, and businesses receive fair evaluations based on genuine customer feedback rather than opaque or biased criteria. Community-Driven Reviews: Emphasizing collective input through dynamic voting power and quadratic funding principles, the app values the opinions of many over a few. This democratizes the rating process, reducing biases and the impact of fraudulent activities. World ID Verification: To combat fake reviews and ensure authenticity, JustETH uses World ID verification to confirm that each review comes from a unique, real person.
How it's made
Challenges we ran into 1. Integrating Ora AI for Sentiment Analysis Problem: As first-time users of Ora AI, we struggled with integrating its sentiment analysis capabilities into our app, particularly due to the large amount of computational resources required, which led to high gas costs on the blockchain. Solution: We optimized our smart contracts to be more gas-efficient and offloaded heavy computations to off-chain processes where possible. This approach reduced gas consumption and allowed us to successfully implement Ora AI's features without compromising performance. 2. Implementing Internet Computer Protocol (ICP) Problem: Working with ICP for the first time presented a steep learning curve, especially in deploying canisters and understanding the cycles concept for shop listings. Solution: We dedicated time to study ICP's documentation and engaged with the developer community for guidance. Through collaboration and persistent learning, we became proficient in deploying canisters and managing cycles, enabling us to effectively utilize ICP for our app. 3. Configuring The Graph for Data Retrieval Problem: Setting up The Graph to efficiently index and retrieve blockchain data was challenging due to complex subgraph configurations and synchronization issues. Solution: We streamlined our subgraphs by focusing on indexing only essential data needed for reviews and user profiles. By optimizing our configurations and queries, we improved synchronization and achieved efficient data retrieval for our application.