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Smart light technology offers new dynamic and interactive capabilities that extend the potential of traditional lighting systems of attracting people and affecting their mood, emotions, and behavior. Our research explores smart lights in the context of shopping windows. The paper describes an extensive empirical study that has been performed for 5 weeks in a fashion store located a top-level shopping area in Milan (Italy). The data automatically collected from over 1 million people passing by or stopping in front of the 3 shopping windows of the store in three different lighting conditions (static, dynamic, and interactive) enable us to provide some empirical evidence of the potential of smart light technology to enhance the shopping experience in brick-and-mortar stores

The StreetSmart Project develops information services that integrate multiple (touch and touchless) interaction paradigms on personal devices and large public displays. It exploits personalization techniques in order to offer new engaging user experiences involving large amounts of multimedia contents.

It is well known that human reasoning and decision-making are strongly influenced by psychological aspects. Recent works explore the adoption of personality traits to provide personalized recommendations. In this article, we report experimental results obtained with implicit recognition of Big Five personality traits from users’ text reviews. Hence, we present a personality-based recommender system with the analysis of the overall users’ satisfaction regarding the list of recommended items, showing promising results