Research on the Internet of Things (IoT) has devoted many efforts to technological aspects. Little social and practical benefits have emerged so far. IoT devices, so-called smart objects , are becoming even more pervasive and social, leading to the need to provide non-technical users with innovative interaction strategies for controlling their behavior. In other words, the opportunities offered by IoT can be amplified if new approaches are conceived to enable non-technical users to be directly involved in “composing” their smart objects by synchronizing their behavior. To fulfill this goal, this article introduces a model that includes new operators for defining rules combining multiple events and conditions exposed by smart objects, and for defining temporal and spatial constraints on rule activation. The article also presents the results of an elicitation study that was conducted to identify possible visual paradigms for expressing composition rules. Prototypes implementing the resulting visual paradigms were compared during a controlled experiment and the one that resulted most relevant for our goals was used in a study that involved home-automation experts. Finally, the article discusses some design implications that came out from the performed studies and presents the architecture of a platform supporting rule definition and execution.

Large interactive displays are increasingly placed in public (or semipublic) locations, including museums, shops, various city settings, and offices. This article discusses the evolution of such displays by looking at their use and analyzing how they are changing the concept of human-computer interaction through new modalities. By surveying the literature on systems using these displays, relevant features were identified and used as classification dimensions. The analysis provided may inform the design and development of future installations. A discussion on research challenges concludes the article.

The rapid growth in interest in Artificial Intelligence (AI) has been a significant driver of research and business activities in recent years. This raises new critical issues, particularly concerning interaction with AI systems. This article first presents a survey that identifies the primary issues addressed in Human-Centered AI (HCAI), focusing on the interaction with AI systems. The survey outcomes permit to clarify disciplines, concepts, and terms around HCAI, solutions to design and evaluate HCAI systems, and the emerging challenges; these are all discussed with the aim of supporting researchers in identifying more pertinent approaches to create HCAI systems. Another main finding emerging from the survey is the need to create Symbiotic AI (SAI) systems. Definitions of both HCAI systems and SAI systems are provided. To illustrate and frame SAI more clearly, we focus on medical applications, discussing two case studies of SAI systems.