SMASH: A Semantic-Enabled Multi-agent Approach for Self-adaptation of Human-Centered IoT

Hamed Rahimi, Iago Felipe Trentin, Fano Ramparany, Olivier Boissier

Abstract: As the number of IoT applications increases, IoT devices are becoming more and more ubiquitous. Therefore, they need to adapt their functionality in response to the uncertainties of their environment to achieve their goals. In Human-centered IoT, objects and devices have direct interactions with human beings. Self-adaptation of such applications is a crucial subject that needs to be addressed in a way that respects human goals and human values. This paper presents SMASH: a multi-agent approach for self-adaptation of IoT applications in human-centered environments. SMASH agents are provided with a 4-layer architecture based on the BDI agent model that integrates human values with goal-reasoning, planning, and acting. It also takes advantage of a semantic-enabled platform called Home’In to address interoperability issues among non-identical agents and devices with heterogeneous protocols and data formats. This approach is compared with the literature and is validated by developing a scenario as the proof of concept. The timely responses of SMASH agents show the feasibility of the proposed approach in human-centered environments.