A Mobile Approach to Food Expiration Date Determination Using OCR and On-Cloud Image Classification

The issue of food waste is more relevant than ever, both for emerging and developed economies. Information technologies have the potential to contribute to reducing this problem, and our research aims to present a viable prototype that uses on-cloud image classification and specific OCR techniques. The result of our study is a low-cost, high-performance mobile application prototype that paves the way for further research. We used advanced application integration concepts, including mobile architectures, Firebase machine learning components, and OCR techniques to highlight how close food products are to their expiration date. In contexts with no printed date, the system computes an indicative shelf-life estimate from conservative category priors. These estimates are not safety judgments and do not replace manufacturer date labels or national food-safety guidance. These results give our article clear elements of authenticity and contribution to the field of knowledge, improving the economic efficiency of warehouses and food stores. The implications of our study are technical, economic, and social.