Vehicle Parking Slot Vacancy Detection Using Machine Learning

Vehicle Parking Slot Vacancy Detection Using Machine Learning

A T Sathya Narayana Reddy1, Chandana N M2, Moksha Kamble3,

N C Supritha4, Shravani V5

Department of Information Science and Engineering, Rao Bahadur Y Mahabaleshwarappa Engineering College

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Abstract: Urbanization has significantly increased vehicle density in cities, intensifying the demand for intelligent parking systems. This project introduces a real-time Parking Slot Vacancy Detection system utilizing computer vision and the Mask R-CNN model to identify and segment occupied and vacant parking slots from live video feeds. The system defines parking slot boundaries and uses deep learning for instance-level object detection. It provides a user-friendly web interface for real-time monitoring and slot booking. The solution is scalable, adaptable to various environments, and integrates easily with existing surveillance infrastructure—supporting smarter urban mobility and sustainable traffic management.

Key Words: Parking Slot Detection, Mask R-CNN, Machine Learning, Computer Vision, Real-Time Monitoring, Smart City