Vehicle Movement Analysis and Insight Generation in College Campus using Edge AI

Overview

This project utilizes Edge AI to provide detailed insights into vehicle movement and parking behaviors on college campuses. By leveraging real-time image processing and data analytics, the solution aims to optimize campus management and enhance security measures.

For a comprehensive understanding of our solution, including detailed descriptions of the solution’s features, process flow, and architecture, please refer to our Project Report. The report provides in-depth insights into our methodologies, technical implementations, and future directions for our vehicle movement analysis and insight generation project on college campuses.

Key Features

• Vehicle Movement Analysis: Analyzes the movement patterns of vehicles to manage campus security effectively.
• Parking Occupancy Monitoring: Monitors parking slot availability and occupancy status.
• Number Plate Detection: Uses Easy OCR for detecting vehicle number plates and identifying authorized and unauthorized vehicles.
• Vehicle Counting: Counts incoming and outgoing vehicles to track traffic flow.
• Integration with MySQL Database: Stores and manages data related to vehicle movements and parking slots.

Technologies Used

• Python
• YOLO (v5 and v8)
• OpenCV
• Easy OCR
• NumPy
• Pandas
• Matplotlib
• MySQL
• Anaconda
• VS Code

Contributors

• Potharaju Sai Kishore
• MD Zaheer Pasha
• Challagundla Yamini
• Panav Kumar Sahu
• Hrishikesh Reddy Papasani