Treffer: A YOLO-Tesseract Module Recognizing System for an Android-based Smart Parking App in Urban On-Street Parking.

This study describes an advanced recognition system embedded in an Android smart parking software application for Makassar City. The system augments the recognition of the parking space and the navigation as well as the payment of the parking fee using a Tesseract OCR module in conjunction with YOLO object detection. The ability of Tesseract OCR to recognize parking spaces, road signs, and vehicle registration plates in real time improves the accuracy of availability updates and assists drivers in finding parking spaces quickly. The application was developed using multiple programming languages, Android Studio, and API integrations for real-time data updates and payment transactions. Iterative testing, including black-box evaluations, ensures cross-device reliability, functionality, and ease of use. Experimental results demonstrated the system's effectiveness in optimizing parking resource utilization. Additionally, user feedback mechanisms refined the app for an evolving user experience. In conclusion, the YOLO-Tesseract recognition system represents a robust solution to urban parking problems. Its core model to improve on-street parking management can be scaled to smart city models worldwide. [ABSTRACT FROM AUTHOR]

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