A Digital Companion Architecture for Ambient Intelligence

Abstract

Ambient Intelligence (AmI) focuses on creating environments capable of proactively and transparently adapting to users and their activities. Traditionally, AmI focused on the availability of computational devices, the pervasiveness of networked environments, and means to interact with users. In this paper, we propose a renewed AmI architecture that takes into account current technological advancements while focusing on proactive adaptation for assisting and protecting users. This architecture consist of four phases: Perceive, Interpret, Decide, and Interact. The AmI systems we propose, called Digital Companions (DC), can be embodied in a variety of ways (e.g., through physical robots or virtual agents) and are structured according to these phases to assist and protect their users. We further categorize DCs into Expert DCs and Personal DCs, and show that this induces a favorable separation of concerns in AmI systems, where user concerns (including personal user data and preferences) are handled by Personal DCs and environment concerns (including interfacing with environmental artifacts) are assigned to Expert DCs; this separation has favorable privacy implications as well. Herein, we introduce this architecture and validate it through a prototype in an industrial scenario where robots and humans collaborate to perform a task.