IEMAS - Industrial Energy Monitoring & Analytics System

Overview

IEMAS is an enterprise-grade Industrial IoT platform designed to monitor and analyze energy consumption from Schneider Energy Meters in industrial environments. The system provides real-time data collection, storage, visualization, and AI-powered analytics through a modular architecture that scales from 1 to 20+ meter installations.

Architecture

Schneider Energy Meters (Modbus RTU/TCP) / Realistic Meter Simulator
           ↓
    ESP32 Devices (Edge Layer) / Python HTTP Client
           ↓
    FastAPI Backend (Python)
           ↓
  Supabase PostgreSQL Database
           ↓
  Next.js Dashboard (TypeScript/React)
           +
    Gemini AI Assistant

Tech Stack

Backend

• Framework: FastAPI (Python 3.11+)
• ORM: SQLAlchemy
• Validation: Pydantic
• Database: PostgreSQL (via Supabase or local asyncpg)
• AI: Google Gemini AI

Frontend

• Framework: Next.js 16.2.9 (App Router with Turbopack)
• Language: TypeScript
• Styling: Tailwind CSS v4
• Data Fetching: TanStack Query
• Charts: Recharts v3
• Icons: Lucide React

Realistic Meter Simulator

• Core: Python 3.11+ Modbus RTU/TCP Simulator Engine
• Features: Electrical parameter models, machine operation cycles, HTTP sender

Project Structure

IEMAS/
├── backend/                    # FastAPI backend service
│   ├── app/
│   │   ├── main.py             # Application entry point
│   │   ├── database.py         # Database connection
│   │   ├── models/             # Pydantic & SQLAlchemy models
│   │   └── routers/            # API route handlers
│   └── requirements.txt        # Python dependencies
│
├── frontend/                   # Next.js dashboard
│   ├── app/                    # App Router pages
│   ├── components/             # React components (RealtimeChart, Analytics, etc.)
│   ├── lib/                    # API clients and utilities
│   ├── hooks/                  # Custom React hooks
│   └── package.json            # Node dependencies
│
├── realistic_meter_simulator/  # Python-based IoT sensor simulator
│   ├── main.py                 # Simulator entry point
│   ├── simulator.py            # Modbus / IoT device engine
│   ├── electrical_parameters.py# Voltage/Current/Power logic
│   └── simulator_config.json   # Simulation environment config
│
├── firmware/                   # ESP32 firmware (Arduino/ESP-IDF)
├── database/                   # Database schema & migrations
└── docker-compose.yml          # Multi-container orchestration

Getting Started

1. Database Setup

Create a PostgreSQL database (e.g. Supabase) and run the SQL schema located in database/schema.sql.

2. Backend Setup

cd backend
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt

# Configure environment variables
cp .env.example .env
# Edit .env with your PostgreSQL credentials

# Run development server
uvicorn app.main:app --reload --host 0.0.0.0 --port 8000

Backend will be available at http://localhost:8000

3. Frontend Setup

cd frontend
npm install

# Run development server with Turbopack
npm run dev

Frontend will be available at http://localhost:3000

4. Running the Simulator

To test the system locally without physical edge devices, you can use the Realistic Meter Simulator:

# In the project root:
python -m realistic_meter_simulator.main

This will start generating simulated Modbus data and pushing it to the backend via HTTP.

Features

Real-Time Data Collection

• Automatic meter readings via Modbus / REST APIs
• Full simulation suite for synthetic operational testing
• Exponential backoff retry logic

AI-Powered Analytics

• Natural language queries via Gemini AI
• Energy trend analysis and reporting
• Peak consumption insights

Industrial UI Design

• Responsive SCADA-inspired interface
• Real-time Recharts visualizations
• High-contrast status indicators

API Endpoints

• GET /api/readings - Get filtered historical readings
• GET /api/readings/latest - Get real-time latest reading per meter
• POST /api/readings - Receive meter reading from Edge/Simulator
• GET /api/meters - List all configured meters

Development Roadmap

• Phase 1: Project scaffolding and infrastructure setup
• Phase 2: Backend data models and API endpoints
• Phase 3: Database integration and authentication
• Phase 4: Alert system and WebSocket real-time updates
• Phase 5: ESP32 firmware development (Simulated)
• Phase 6: Frontend dashboard and routing
• Phase 7: Real-time meter visualization
• Phase 8: Alert notification system
• Phase 9: AI assistant integration
• Phase 10: System monitoring dashboard
• Phase 11: End-to-end integration and testing
• Phase 12: Production deployment preparation

License

Proprietary - Industrial Energy Monitoring & Analytics System