EnergiX Copilot

Where every kilowatt counts. An AI-powered smart system that monitors, predicts, and optimizes industrial energy consumption in real-time — built for Industry 4.0.

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Theme: Industry 4.0

Industries waste up to 30% of energy through idle machines, inefficient operations, and unpredictable demand spikes. EnergiX Copilot tackles this head-on with a smart monitoring & optimization system powered by machine learning.

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What It Does

• Anomaly Detection — Identifies abnormal energy consumption patterns across machines in real-time
• Efficiency Classification — Rates machine performance and pinpoints energy waste
• Demand Forecasting — Predicts future energy demand to enable proactive load balancing
• Smart Recommendations — Generates actionable insights to cut energy costs
• Live Dashboard — Visualizes plant-wide energy health with interactive charts and KPIs

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Architecture

┌─────────────┐     ┌──────────────┐     ┌─────────────┐
│  Frontend   │────▶│  FastAPI     │────▶│  ML Models  │
│  React +    │◀────│  Backend     │◀────│  Isolation  │
│  Tailwind   │     │              │     │  Forest +   │
│  Recharts   │     │              │     │  XGBoost    │
└─────────────┘     └──────────────┘     └─────────────┘

Tech Stack

Layer	Technology
Frontend	React, Vite, Tailwind CSS, Recharts, Framer Motion
Backend	FastAPI, Uvicorn
ML	XGBoost, Isolation Forest, Scikit-learn
Data	Pandas, NumPy, Synthetic industrial datasets

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Quick Start

Prerequisites

• Python 3.10+
• Node.js 18+
• npm
• PostgreSQL 14+ (optional — system falls back to CSV files if unavailable)

1. Database Setup (Optional but Recommended)

# Ensure PostgreSQL is running, then build the database
python database/build_db.py

Default credentials: postgres / energix123 on localhost:5432

2. Backend Setup

# Create and activate virtual environment
python -m venv venv
source venv/bin/activate   # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r backend/requirements.txt

# Start the API server
uvicorn backend.app:app --reload --port 8000

3. Frontend Setup

cd frontend

# Install dependencies
npm install

# Start the development server
npm run dev

The app will be available at http://localhost:3000

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Architecture

┌─────────────┐     ┌──────────────┐     ┌─────────────┐
│  Frontend   │────▶│  FastAPI     │────▶│  ML Models  │
│  React +    │◀────│  Backend     │◀────│  Isolation  │
│  Tailwind   │     │              │     │  Forest +   │
│  Recharts   │     │              │     │  XGBoost    │
└─────────────┘     └──────┬───────┘     └─────────────┘
                           │
                    ┌──────▼───────┐
                    │  PostgreSQL  │
                    │  (optional,  │
                    │   falls back │
                    │   to CSV)    │
                    └──────────────┘

Tech Stack

Layer	Technology
Frontend	React, Vite, Tailwind CSS, Recharts, Framer Motion
Backend	FastAPI, Uvicorn
Database	PostgreSQL + SQLAlchemy ORM (optional)
ML	XGBoost, Isolation Forest, Scikit-learn
Data	Pandas, NumPy, Synthetic industrial datasets

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Key Features

• Real-time monitoring of machine-level energy consumption
• AI-driven alerts for anomalies and inefficiencies
• Predictive demand forecasting for proactive planning
• Scenario simulation to test "what-if" conditions
• Actionable recommendations to reduce energy waste
• PostgreSQL Integration for persistent state (optional — falls back to CSV)
• Loading states across all pages for better UX

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API Endpoints

Method	Endpoint	Description
GET	/api/health	Health check
GET	/api/machines	List all machines
GET	/api/machines/{id}	Get machine details
GET	/api/alerts	List alerts (filterable)
POST	/api/alerts/{id}/acknowledge	Acknowledge an alert
GET	/api/recommendations	List recommendations
POST	/api/recommendations/{id}/apply	Apply a recommendation
POST	/api/recommendations/{id}/dismiss	Dismiss a recommendation
GET	/api/dashboard-summary	Get dashboard overview
POST	/api/analyze	Run anomaly detection
POST	/api/classify-efficiency	Run efficiency classification
POST	/api/forecast	Run demand forecasting

Full API docs available at http://localhost:8000/docs when server is running.

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🏭 Built For

🚀 GNA Hackathon 4.0

Industry 4.0 — Smart Manufacturing & Energy Optimization

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👥 Team Krantikaris

Team Members
👨‍💻 Ayush (Data Guy + Simulator builder)
👨‍💻 Dev Prakash Pandey (Data Guy + Simulator builder)
👨‍💻 Divyanshu Kumar (Frontend designer)
👨‍💻 Krishna Swarup (Frontend builder)
👨‍💻 Manish Tiwari (Leader)

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