Project Overview
Helios IoT Energy Portal is an enterprise time-series analytics dashboard aggregating real-time data from over 5,000 distributed wind and solar grid units. By utilizing IoT sensors and predictive ML models, Helios enables energy grid providers to forecast power supply fluctuations and optimize load distributions dynamically.
Challenges
Time-series data collected from thousands of smart grid units produces massive volumes of write operations. Safely ingesting, processing, and rendering this high-frequency telemetry on client screens without introducing interface lag was a major technical roadblock.
Solutions We Engineered
- High-Velocity Ingestion: Implemented a Go-based ingestion microservice capable of batching millions of data writes per minute.
- Time-Series DB Tuning: Implemented customized partition retention policies inside InfluxDB, improving database read response times by 40%.
- Predictive Power Analytics: Designed an integrated ML training worker that provides 24-hour supply forecasts based on live meteorological data.
Tech Stack Used
- Telemetry Ingest: Go (Golang), gRPC, MQTT
- Database: InfluxDB, TimescaleDB
- Frontend Panel: Astro, React, Chart.js
- Machine Learning: TensorFlow, Python, FastAPI
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