A new intelligent supermarket security system

Abstract

With the rapid development of artificial intelligence in recent years, the application of intelligent security has become increasingly widespread. This paper presents a new intelligent system that uses Convolutional Neural Network (CNN) combined with a high-resolution camera to identify the theft behavior of customers. The CNN extracts relevant information from the theft and non-theft behavior of customers in supermarkets to establish a recognition model. Our results show that, by updating the data sets, the recognition model can be continuously optimized, and the average recognition accuracy finally reaches 83 %. The proposed system can independently identify the theft and non-theft behavior in video surveillance and sound alarm on the theft behavior in time. The advantages of the system are its low cost and high precision, which show excellent commercial value and application prospects.