Smart Parking System

Abstract

1. Introduction

An AI-powered parking management system with real-time license plate detection, interactive parking grid, and a conversational AI assistant — all in a premium dark-themed web interface.

Real-time overview with occupancy donut chart, activity feed, and recent detections.

Session info, zone bar charts, and scrollable activity log table.

2. Objective

Smart Parking System using Computer Vision and OCR to automatically detect vehicle license plates, identify Indian states, and manage parking spaces in real time. Built with Python, OpenCV, Tesseract OCR, Flask, and SQLite, featuring live video streaming, automatic slot allocation, and a web-based dashboard.

This project demonstrates how JavaScript can be applied to a real-world Internet of Things (IoT) problem.

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Node.js (LTS) and npm
• A modern web browser
• VS Code or any code editor
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/AakashBhat1/smart-parking-system-.git
cd smart-parking-system-

# Clone the repository
git clone https://github.com/yourusername/smart-parking-system.git
cd smart-parking-system

# Create virtual environment
python -m venv venv

# Activate it
# Windows:
venv\Scripts\activate
# macOS/Linux:
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Pull the lightweight model (~500MB)
ollama pull qwen3:0.6b

# Ollama runs automatically in the background on most systems.
# If not, start it manually:
ollama serve

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Add a mobile dashboard using Blynk or Firebase
• Store readings in a cloud database for history charts
• Add alerts via SMS / Telegram when thresholds are crossed

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. Which microcontroller / board and sensors are used and why?
2. How does the device send data (Wi-Fi, MQTT, HTTP, Bluetooth)?
3. Where is the sensor data stored and visualised?
4. How is power consumption managed?
5. How would you secure the device and its communication?

9. Source Code & License

This project is developed by AakashBhat1 and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.