A multi-level energy meter dashboard using Raspberry Pi, RS-485, and real-time data analytics.
Project Overview
A multi-unit industrial complex needed a centralized energy monitoring solution to track real-time power usage across its electrical distribution hierarchy—from state supply meters down to slave panel meters. Kelectron Technologies designed a modular, scalable solution to digitize and visualize this entire energy consumption chain.
Problem Statement
- No centralized view of power consumption at different panel levels.
- Manual logging of meter readings led to errors and inconsistent tracking.
- Difficulty in analyzing historical trends or identifying excess loads.
- Needed a user-friendly web dashboard that could drill down from state board supply to slave meters, with the ability to export historical data and show real-time trends.
Our Solution: Hierarchical Energy Meter Monitoring Platform
Kelectron deployed a Raspberry Pi-based IoT system with a structured data acquisition pipeline to monitor and display real-time and historical usage data across:
State Board → Main Meters → Master Panels → Main Panels → Slave Meters
| Layer | Technology |
|---|---|
| Hardware Interface | RS-485 communication with EM6400 & EM6436H meters |
| Edge Devices | Raspberry Pi 4 with isolated RS485 converters and shielded cables |
| Data Storage | Local MongoDB on RPi; historical data partitioned per meter |
| Backend | FastAPI-based data pipeline to serve structured data |
| Frontend | Responsive web dashboard (HTML, JS) with meter hierarchy navigation and charting |
Implementation Highlights
- Deployed 8 Raspberry Pi units across multiple panels with class-10 SD cards
- Used shielded RS-485 cabling to ensure stable Modbus communication in noisy environments
- Designed a multi-level UI allowing click-through from main meter to nested slave meters
- Provided download options for Excel and CSV for all historical data views
- Integrated dynamic charting for real-time and historical comparison
- Built-in auto-retry and error-handling logic to handle power failures or communication drops
Results & Benefits
- Full visibility across 20+ energy meters in real-time
- Enabled load profiling and energy audits with just a few clicks
- Client identified energy spikes and optimized load balancing, reducing peak load by 18%
- Improved electrical safety and planning by detecting overdraws early
- Foundation laid for future automation (auto alerts, integration with billing systems)
Technologies Used
- Hardware: Raspberry Pi 4, RS-485 isolated modules
- Energy Meters: Schneider EM6400 / EM6436H
- Protocols: Modbus RTU, HTTP
- Software Stack: Python, FastAPI, MongoDB, JavaScript
- Data Features: Real-time polling, historical export, multi-level meter navigation