Abstract: Unstaffed retail stores have become more popular in recent years, and they have had a huge impact on traditional shopping habits. Unmanned retail containers play an important role in this area; they can have a significant impact on the consumer shopping experience, while conventional methods based on weighing sensors are unable to detect what the customer is taking. This paper proposes a smart unstaffed retail shop scheme based on image processing, with the goal of determining if the unstaffed retail shopping style can be implemented. An end-to-end classification model trained by the method is developed for SKU counting and recognition based on a data set of images in different scenarios containing different types of stock keeping unit (SKU), and the proposed solution in this study is able to achieve 97.7% counting accuracy and 98.7% recognition accuracy on the test dataset, indicating that the system is efficient.Keywords:- Cashless Economy, Security, Distributed Database, Visual Cryptography, Hash Algorithm, etc.