Enhanced IoT-Aware Online Shopping System

Abstract

In online business, it is important to construct sale web pages offering attractive services for popular products in order to improve page access as well as purchase rates. Moreover, online shop owners need to hold various types of sales frequently throughout the year to keep customers coming back. Also, online shopping systems have to adapt to its circumstances such as customers' needs and the surrounding economic situations. To cope with this, a self-organized IoT aware system is proposed. Here, awareness is achieved by monitoring / analyzing the data of user's behavior such as gazing, listening, smelling etc. The focus here is the analysis of such as users' eye gaze, listening /smelling activity etc. The aim is to derive insights about products the user is interested in or not and to adapt the system accordingly. This is achieved by presenting product information including sales associates' presence, their voice, and product's smell or even other products with similar attributes, by hiding products with less interesting attributes and by building a user's interest model through integrating all the positive preferences.