This chapter explores features, concepts, and provides guidelines concerning the role and applicability of smart data captured in a non-intrusive way, in the inference and contextualization of human behavior and interaction. The chapter starts by introducing aspects related to human interaction, for instance, how to define and to best model physical and psychological proximity; models for social awareness and social contextualization. The next part of the chapter deals with interaction inference and interaction contextualization, namely: classification models that best suit the inference of behavior in the vere of smart data; challenges in regards to small data capture and behavior inference derived from small data, in particular when considering decentralized, mobile cyber-physical systems; guidelines to model interaction based on pervasive wireless sensing systems, including available middleware and systems (tools). The chapter then provides information concerning specific applicability use-cases, namely, Points of Interest detection via smart data, and how smart data can be used to boost social interaction in a pervasive, non-intrusive way. The chapter concludes with a set of recommendations.

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