Creating a Personalized Recommendation Framework in Smart Shopping by Using IoT Devices

Personalization and recommendation are two important prerequisites that must be incorporated in the Iot environment where smart devices data are generated anywhere and anytime. Both prerequisites are essential to produce a higher satisfaction level of ubiquitous recommender system which matches the preferences of the user. Is the time to improve the quality of traditional ubiquitous recommender system which failed to exploit dynamic and heterogeneous big data in delivering personalized recommendation. In this paper, we create a framework of personalized recommendations in Smart shopping where Iot devices are connected. We proposed a Fog computing architecture to solve the ubiquitous recommendations issues related to Iot challenges. The given model is a multi-layer fog structure which aims to use the multi sources big data in order to propose personalized offers according to the users' profiles and analyze their feedbacks to improve their experiences.