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Description
🎯 Objective
Create a complete smart contract for smart-meter-data-ledger that maintains a tamper-proof ledger of smart meter data on the Stellar network using Soroban, enabling transparent tracking of energy usage for billing and analytics.
🏗 Contract Structure
smart-meter-data-ledger/src/
lib.rs // Configuration and contract exports
ledger.rs // Core logic for meter data logging
analytics.rs // Management of data queries and analytics
utils.rs // Shared utilities for validation and timestamps
Makefile // Build and deployment automation
README.md // Contract documentation and usage instructions
🗂 Requirements
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Meter Data Logging
- Implement mechanisms for logging smart meter data, compliant with metering standards.
- Support submission of usage data with timestamps and meter IDs.
- Enable querying of historical meter data for analysis.
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Energy-Specific Features
- Role-based updates: Smart meters submit data, utilities verify.
- Integration hooks for linking to consumption verifier or billing contracts.
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Build and Test
- Must successfully execute
cargo build,stellar contract build, andcargo test.
- Must successfully execute
📦 Key Data Structures
The contract will use maps to associate meter IDs with usage records, each record detailing energy consumption, timestamps, and submitting device addresses. A separate structure will log aggregated analytics, such as total usage per consumer or period, for efficient querying.
🔑 Key Functions
initialize()– Set up the contract with meter and utility configurations.log_data()– Record new meter data with timestamps.verify_data()– Verify submitted data by authorized utilities.get_usage_history()– Query the usage history for a meter.aggregate_usage()– Compute aggregated usage for analytics.
🔗 References
- Soroban Documentation - Contract Development
- Stellar Developers - Data Management
- Rust Book - Structuring Data
- Soroban Storage Guide
- IEC Smart Meter Standards
⏳ ETA
- 3 Days
📌 Additional Notes
- Optimize storage to minimize transaction fees on Soroban for utilities.
- Design for scalability to handle high-frequency meter data.
- Ensure tamper-proof logging to maintain data integrity.
- Support future integration with real-time analytics platforms.
- Include mechanisms for detecting anomalous usage patterns.
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