Advertising Image Design Skills of E-Commerce Products in the Context of the Internet of Things

Abstract

E-commerce companies often use image advertising as a marketing approach to introduce potential customers to the goods or services that the business offers. People’s tastes are becoming more diverse and diverse in their range of variance. It is difficult for standard e-commerce commercials that aim their message at everyone to get the results they are looking for. The most significant obstacle that must be conquered in e-commerce is figuring out how to properly communicate an image advertisement to the ideal client for e-commerce in the optimal setting. This is a problem that must be resolved. As a result, in this work, we developed a unique commercial fuzzy picture advertising recommendation system for e-commerce items looking at it from the standpoint of the Internet of things (IoT). Customers who shop online may have their location and browsing history collected by Internet of Things devices. A multiadaptive k-nearest neighbour technique is used to predict the customers’ interests. After that, the suggested system is used to provide customized picture adverts to customers based on the customers’ interests and the locations of their devices. The proposed model’s effectiveness was assessed by using variables such as suggestion efficiency, Ad satisfaction rate, execution time, and click-through rate (CTR). According to the findings, the integrated Internet of Things advertising suggestion system that was developed is effective for targeted image advertising and enhancing client happiness.