IoT-aware online shopping system enhanced with gaze analysis

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 (campaign) 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 these requirements, a self-organized IoT (Internet of Things) aware systems is proposed for online shopping. In our approach, awareness is achieved by monitoring/analyzing the data of user's behavior, in particular the eye gaze. The particular focus here is the analysis of the users' eye gaze with the objective to derive insights about products the user is interested in or not and adapt the system accordingly by presenting other products with similar attributes, hiding products with less interesting attributes and building a user's interest model by integrating all the positive preferences