AI Enhanced Barcode Generator and Scanner for Robust and Secure Data Encoding in Education

The increasing digitization of educational institutions has created a demand for secure, accurate, and efficient methods of managing academic records and student information. Conventional barcode and QR code systems are widely used for identification and data sharing; however, their performance is typically affected by poor lighting conditions, image blur, damaged codes, and limited data validation capabilities. To address these challenges, this paper proposes an AIEnhanced Barcode Generator and Scanner for Robust and Secure Data Encoding in Education. The proposed framework integrates computer vision-based preprocessing, deep learning-driven feature extraction and barcode recovery, intelligent data validation, and secure data encoding within a mobile platform. TensorFlow Lite enables realtime on-device AI inference, ensuring efficient processing and enhanced privacy. The system was trained and evaluated using the Synthetic Barcode Dataset, BarCodeNet, Kaggle Barcode Detection datasets, ICDAR/SynthText datasets, and a custom educational barcode dataset. Experimental results indicate that the proposed approach improves barcode recognition and decoding accuracy by approximately 20–30