Egocentric interaction for ambient intelligence
Abstract: Ambient intelligence refers to the vision of computationally augmented everyday environments that are sensitive, adaptive and responsive to humans and intelligently support their daily lives. Ambient ecologies are the infrastructures of ambient intelligence. To enable system developers to frame and manage the dynamic and complex interaction of humans with ambient ecologies consisting of a mixture of physical (real) and virtual (digital) objects, novel interaction paradigms are needed.Traditional interaction paradigms like the WIMP (windows, icon, menus, and pointing devices) paradigm for desktop computing operate in a closed world, unaware of the physical, social and cultural context. They restrict human perception and action to screen, mouse and keyboard with the assumption that human attention will be fully devoted to interaction with the computer. Emerging interaction paradigms for ambient intelligence are typically centered on specific devices, specific computing environments or specific human capabilities. Also, many of them are driven by technological advancements rather than viewing the human agent as their starting point. A principled, theoretical approach centered in the individual human agent, their situation and activities that are comprehensive and integrated while at the same time instrumental in the design of ambient ecologies has been lacking.This thesis introduces egocentric interaction as an approach towards the modeling of ambient ecologies with the distinguishing feature of taking the human agent’s body, situation and activities as center of reference, as opposed to the more common device-centric approaches in facilitating human-environment interaction. Egocentric interaction is encapsulated in a number of assumptions and principles such as situatedness, the proximity principle, the physical-virtual equity principle, perception and action instead of “input” and “output,” and activity-centeredness. A situative space model is proposed based on some of these principles. It is intended to capture what a specific human agent can perceive and not perceive, reach and not reach at any given moment in time. The situative space model is for the egocentric interaction paradigm what the virtual desktop is for the WIMP interaction paradigm: more or less everything of interest to a specific human agent is assumed and supposed to happen here.In addition, the conception and implementation of the easy ADL ecology based on egocentric interaction, comprising of smart objects, a personal activity-centric middleware, ambient intelligence applications aimed at everyday activity support, and a human agent literally in the middle of it all is described. The middleware was developed to address important challenges in ambient intelligence: (1) tracking and managing smart objects; (2) tracking a human agent’s situative spaces; (3) recognizing human activities and actions; (4) managing and facilitating human-environment interaction; and (5) to ease up the development of ambient intelligence applications. The easy ADL ecology was first simulated in immersive virtual reality, and then set up physically as a living laboratory to evaluate: (1) the technological and technical performance of individual middleware components, (2) to perform a user experience evaluation assessing various aspects of user satisfaction in relation to the support offered by the easy ADL ecology, and (3) to use it as a research test bed for addressing challenges in ambient intelligence. While it is problematic to directly compare the “proof-of-concept” easy ADL ecology with related research efforts, it is clear from the user experience evaluation that the subjects were positive with the services it offered.
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