Concept Ideation and Further Exploration

This concept was derived from my background in exploring queues, wait times, manufacturing times in my career as a product manage in health care software and background in industrial engineering. Eventually this information would be useful in feeding simulation software for companies or integrating into existing applications.

Github Repository

Occupancy & Wait Time Tracking

A computer vision-based tracking system designed to monitor occupancy levels and waiting times in spaces like waiting rooms, restaurants, and public areas. Using YOLOv8 for object detection and DeepSORT for tracking, this project anonymously tracks individuals, estimates how long they stay, and analyzes movement patterns in defined zones.

Features

• Real-Time Person Tracking – Uses YOLOv8 + DeepSORT to detect and track people in video footage.
• Anonymized Data Processing – Tracks individuals without storing personal data, ensuring privacy compliance.
• Zone-Based Occupancy Analysis – Detects movement within predefined zones (waiting areas, tables, exits).
• Wait Time Calculation – Measures entry & exit times to estimate average wait times per individual.
• Data Visualization – Generates scatter plots, occupancy trends, and wait time analytics using Matplotlib.

Technologies Used

• Python – Main programming language
• OpenCV – Image processing and real-time video handling
• YOLOv8 – Person detection
• DeepSORT – Multi-object tracking
• Pandas – Data processing and handling
• Matplotlib – Visualization of movement patterns and occupancy trends
• Cryptography – Data encryption for privacy

License

Distributed under MIT License. See LICENSE.txt for more information.