🏙 Chandigarh Smart City Digital Twin

Intelligent Urban Analytics using Python & NumPy

A data-driven Smart City simulation that analyzes traffic, parking, flood risk, WiFi coverage, EV charging demand, emergency response, and city-wide decision making using Python and NumPy.

📸 Project Preview

📖 Project Overview

The Chandigarh Smart City Digital Twin is an intelligent urban analytics platform developed using Python, NumPy, and Matplotlib. It simulates multiple smart city services such as traffic management, parking optimization, flood monitoring, WiFi coverage, EV charging infrastructure, emergency response, and an integrated decision engine.

The project demonstrates how numerical computing and data analytics can be used to solve real-world urban challenges through simulation, visualization, and intelligent recommendations.

✨ Features

• 🚗 Traffic Analytics
• 🅿 Smart Parking Optimization
• 🌧 Flood Risk Assessment
• 📡 WiFi Coverage Analysis
• ⚡ EV Charging Analytics
• 🚑 Emergency Response System
• 🧠 Smart Decision Engine
• 🏙 Integrated Smart City Dashboard
• 📊 Professional Data Visualizations
• 📈 City Health Score

🛠 Technologies Used

Technology	Badge	Purpose
Python		Core programming language used to build the Smart City Digital Twin.
NumPy		Performs numerical computing, matrix operations, and data analysis.
Matplotlib		Generates professional charts, graphs, and dashboard visualizations.
Jupyter Notebook		Interactive environment used for development, analysis, and documentation.

🏗 Project Architecture

The Smart City Digital Twin integrates multiple urban analytics modules to monitor city operations, generate insights, and support intelligent decision-making.

🏗 Project Architecture

                        Chandigarh Smart City

                               │
        ┌──────────────────────┼──────────────────────┐
        │                      │                      │
        ▼                      ▼                      ▼
   🚗 Traffic             🅿 Parking           🌧 Flood Risk
        │                      │                      │
        └──────────────┬───────┴──────────────┬───────┘
                       ▼                      ▼
                📡 WiFi Coverage      ⚡ EV Charging
                       │                      │
                       └──────────────┬───────┘
                                      ▼
                          🚑 Emergency Response
                                      │
                                      ▼
                         🧠 Smart Decision Engine
                                      │
                                      ▼
                   📊 Integrated Smart City Dashboard
                                      │
                                      ▼
                    💡 Smart Recommendations & Insights

🔄 Project Workflow

The project follows a complete analytics workflow from data collection to visualization and smart recommendations.

🏗 Project Architecture

Input Data
    │
    ▼
NumPy Arrays
    │
    ▼
Data Analysis
    │
    ▼
Visualization
    │
    ▼
Decision Engine
    │
    ▼
Recommendations
    │
    ▼
Integrated Smart City Dashboard

📂 Project Structure

Chandigarh-Smart-City-Digital-Twin
│
├── README.md
├── requirements.txt
├── LICENSE
│
├── notebooks
│   └── SmartCity_Twin.ipynb
│
├── screenshots
│   ├── dashboard.png
│   ├── traffic.png
│   ├── parking.png
│   ├── flood.png
│   ├── wifi.png
│   ├── ev.png
│   └── emergency.png
│
└── assets
    └── architecture.png

📸 Dashboard Screenshots

🏙 Integrated Smart City Dashboard

🚗 Traffic Analysis

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🅿 Parking Analysis

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🌧 Flood Risk Analysis

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📡 WiFi Coverage Analysis

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⚡ EV Charging Analysis

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🚑 Emergency Response Analysis

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🧠 Smart Decision Engine

⚙ Installation

Clone the repository

git clone https://github.com/Shubhh23/Chandigarh-SmartCity-Digital-Twin.git

Navigate to the project

cd Chandigarh-SmartCity-Digital-Twin

Install dependencies

pip install -r requirements.txt

▶ Run the Project

Launch Jupyter Notebook

jupyter notebook

Open

SmartCity_Twin.ipynb

Run all cells to generate the complete Smart City Dashboard and analytics.

🚀 Future Scope

Future versions of this project can include:

• 🤖 AI-based Traffic Prediction
• 🌦 Live Weather API Integration
• 🗺 Google Maps / OpenStreetMap Integration
• 📡 IoT Sensor Integration
• 🚁 Drone-based Smart City Monitoring
• 📹 CCTV-based Vehicle Detection
• 📊 Power BI Interactive Dashboard
• 🧠 Machine Learning Models
• 📱 Mobile Application
• ☁ Cloud-based Deployment

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🌆 Project Identity

👨‍💻 Author

Shubh Chak

IT Student | UIET, Panjab University

Aspiring Data Analyst | Python | NumPy | SQL | Power BI

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