3. Automated Data Validation
Automated data validation is a key component of Edma’s energy tracking system, ensuring that only accurate, tamper-proof, and verified energy data is recorded on the blockchain. By leveraging IoT sensors, smart contracts, and AI-driven anomaly detection, Edma maintains high data integrity and fraud prevention.
Key Components of Automated Data Validation
1. Multi-Layer Data Verification
Cross-checks energy data from multiple IoT devices to prevent discrepancies.
Uses timestamp synchronization to validate real-time energy production records.
Ensures data consistency before allowing blockchain storage.
2. AI-Powered Anomaly Detection
Machine learning models detect outliers and fraudulent energy claims.
Identifies unexpected fluctuations in energy output.
Flags suspicious activity for manual review or automated rejection.
3. Blockchain Smart Contract Enforcement
Smart contracts validate energy data before issuing Energy Tracking Tokens (ETT) and Clean Energy Coins (CLE).
Uses predefined threshold rules to approve or reject data submissions.
Ensures compliance with ESG and industry regulations.
4. Decentralized Oracle Integration
Chainlink oracles fetch external energy market data for verification.
Smart meters submit energy reports that must be confirmed by multiple nodes.
Reduces reliance on a single point of failure and enhances data trustworthiness.
How Automated Validation Works in Edma
Smart meters submit encrypted energy data to validation nodes.
AI models analyze the data for inconsistencies or fraudulent activity.
Smart contracts cross-check the data with blockchain-stored parameters.
Verified data is recorded on-chain, triggering the issuance of ETT & CLE.
By integrating AI-driven anomaly detection, smart contract validation, and decentralized oracles, Edma ensures that only accurate, verifiable, and tamper-proof energy data is used within its ecosystem.
Last updated
