Industrial IoT Solution for Smart Manufacturing
A multi-line manufacturing facility sought to digitize its operations by capturing real-time data from machines, electrical panels, and the shop-floor
Read more →- Energy monitoring
- Modbus
- Raspberry Pi
Smart Energy Monitoring System for Industrial Power Distribution
A multi-level energy meter dashboard using Raspberry Pi, RS-485, and real-time data analytics.
Case study ·
- 18%lower peak load
- 20+meters visible in real time
- 8Raspberry Pi edge units
Project overview
The brief
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
What needed solving
- 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
What changed for the client
- 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)
Results as reported on this client project. Outcomes vary with each plant, process and data set.
Technologies used
The stack behind the project
- 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
About this project
What problem did the Smart Energy Monitoring System for Industrial Power Distribution project solve?
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. No centralized view of power consumption at different panel levels. Manual logging of meter readings led to errors and inconsistent tracking.
What did Kelectron build?
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 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.
What results were achieved?
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)
Which technologies were 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.
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