Machine Learning-Driven Optimization for Real...

Machine Learning-Driven Optimization for Real-Time Car Parking Slot Detection

Author Name : Varun Reddy Javvaji, Ravipati Venkata Sai Jaswanth, Sreenivasan S, Ansh Dabral, Pratyush Banerjee, Atharva Yogesh Honrao, Omprakash G Matur

ABSTRACT Parking space congestion has become a significant challenge in modern society due to the rapid increase in the number of cars without a corresponding rise in parking availability. This study utilizes Instance Segmentation techniques and Deep Learning to address congestion issues, particularly at critical bottlenecks like parking areas. The proposed model identifies all the initially available parking spots within a defined region, processes this data in real-time, determines whether slots are occupied or vacant, and provides accurate information about available parking spaces. The system is designed to locate free parking areas not only for cars but also for twowheelers. With a mask identification accuracy exceeding 92.33% and a boundary detection accuracy of 98.4%, the model demonstrates high robustness.