Optimization of shopping product strategy using automatic billing and machine learning enabled smart trolley

• Published in: IOP conference series. Materials Science and Engineering 2020-08, Vol.912 (6), p.62008
• Main Authors: Vidhya Kamala Lakshmi, S, Elatchiya, R V, Balamurugan, S, Shanmugam, Vignesh
• Format: Article
• Language: English
• Subjects: Customer services; Customers; Load cells; Machine learning; Optimization; Shopping; Theft; Trolleys
• ISSN: 1757-8981; 1757-899X
• DOI: 10.1088/1757-899X/912/6/062008

This paper is about a smart trolley (Fute cart-fute means smart, cart means trolley) which can provide fast and comfortable shopping experience to shopping customer. The trolley has attached barcode scanner to scan the products dropped, load cell to detect the weight of the products dropped and raspberry pi to integrate all these components using python. Fute cart is designed in such a way that it undergoes machine learning process with the history of data available. So with these data, it is possible to form relation between a product sale and its relative position in the shop. Also from the history of data, it is possible to categorise the products as complementary, mutually exclusive and dependent products based on the sequence based prediction. This kind of strategic arrangement and prediction increased the profit rate of the surveyed shop by 21%. The trolley also has theft detection system. Fute cart serves to be beneficial for both the customers and shopkeepers. It gives fast and informative shopping experience to the customers. Also for the shopkeeper, it reduces the cost of appointing an operator and it provides theft detection service and customer attractive product arrangement ideas.