Authors :
Farzana M.; Dr. K. Arun Kumar
Volume/Issue :
Volume 11 - 2026, Issue 5 - May
Google Scholar :
https://tinyurl.com/2s477kc6
Scribd :
https://tinyurl.com/jbfv88bu
DOI :
https://doi.org/10.38124/ijisrt/26May859
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
Food wastage caused by the consumption, storage, or negligent disposal of expired products remains a critical
global issue affecting households, retailers, public health systems, and supply-chain ecosystems. More than 1.05 billion tons
of food are wasted annually, leading to massive financial losses and environmental harm. A major reason for this wastage is
poor visibility of expiry dates, human error, and lack of automated inventory systems. This project proposes an AI-driven
Smart Expiry Date Detection System utilizing OCR (Tesseract + OCR.space), barcode decoding (pyzbar), FastAPI backend,
MongoDB Atlas cloud database, an automated alert scheduler, and a Streamlit user interface. The system extracts expiry
dates from images, decodes barcode metadata, stores product details, and generates real-time expiry alerts. Research
findings from the IEEE paper “Real-Time Expiry Alert System for Safer Retail using Barcode and QR Code Recognition”
validate hybrid detection (OCR + barcode decoding) as the most accurate and resource-efficient method, achieving up to
97.3% OCR accuracy, 99.5% barcode decoding accuracy, and sub-200ms response time. The proposed system significantly
reduces food waste, improves consumer safety, and ensures intelligent inventory management. It reflects a comprehensive
engineering approach across AI, computer vision, backend development, and cloud deployment.
References :
- T. Khan, “A Cloud-Based Smart Expiry System Using QR Code,” 2018 IEEE International Conference on Electro/Information Technology (EIT), 2018.
- T. Khan, “Expiry Date Digit Recognition using Deep Learning,” IEEE National Aerospace and Electronics Conference (NAECON), 2019.
- M. R. Hyder and T. Khan, “Automatic Expiry Date Notification System Interfaced with Smart Speaker,” International Journal of Engineering Science Invention, vol. 9, no. 7, 2020.
- V. Krishanamurthy et al., “Smart Expiry Tracker and Product Recommender using Google ML Kit OCR Engine,” IEEE Conference Proceedings, 2024.
Food wastage caused by the consumption, storage, or negligent disposal of expired products remains a critical
global issue affecting households, retailers, public health systems, and supply-chain ecosystems. More than 1.05 billion tons
of food are wasted annually, leading to massive financial losses and environmental harm. A major reason for this wastage is
poor visibility of expiry dates, human error, and lack of automated inventory systems. This project proposes an AI-driven
Smart Expiry Date Detection System utilizing OCR (Tesseract + OCR.space), barcode decoding (pyzbar), FastAPI backend,
MongoDB Atlas cloud database, an automated alert scheduler, and a Streamlit user interface. The system extracts expiry
dates from images, decodes barcode metadata, stores product details, and generates real-time expiry alerts. Research
findings from the IEEE paper “Real-Time Expiry Alert System for Safer Retail using Barcode and QR Code Recognition”
validate hybrid detection (OCR + barcode decoding) as the most accurate and resource-efficient method, achieving up to
97.3% OCR accuracy, 99.5% barcode decoding accuracy, and sub-200ms response time. The proposed system significantly
reduces food waste, improves consumer safety, and ensures intelligent inventory management. It reflects a comprehensive
engineering approach across AI, computer vision, backend development, and cloud deployment.
