Egocentric interaction as a tool for designing ambient ecologies—The case of the easy ADL ecology

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Abstract

The visions of ambient intelligence demand novel interaction paradigms that enable designers and system developers to frame and manage the dynamic and complex interaction between humans and environments populated with physical (real) and virtual (digital) objects of interest. So far, many proposed approaches have adhered to a device-centric stance when including virtual objects into the ambient ecology; a stance inherited from existing interaction paradigms for mobile and stationary interactive devices. In this article, we introduce egocentric interaction as an alternative approach, taking the human agent’s body and mind as the center of reference. We show how this interaction paradigm has influenced both the conception and implementation of the easy ADL ecology, comprising of smart objects, a personal activity-centric middleware attempting to simplify interaction given available resources, ambient intelligence applications aimed at everyday activity support, and a human agent literally in the middle of it all.

Introduction

With the advancement in computing, communication, sensing, actuation, interface and interaction technologies, the boundaries between physical and virtual (or computing) worlds are becoming transparent with the possibilities of seamless integration of the two worlds. Ambient intelligence [1] refers to the vision of integrating computational intelligence within human environments and the artifacts that it contains, such that, human-centered services are offered to satisfy human agents’ immediate needs. Ambient ecology [2] could be considered as the infrastructure through which ambient intelligence can be realized. It comprises of an inter-connected collection of heterogeneous components like smart objects [3], middleware components, and ambient intelligence applications, virtual objects that are part of such applications and are accessed through the smart objects, artificial agents, and human agents with a collective goal of supporting human agents’ activities, lifestyle and well-being.

The visions of ambient intelligence introduce several challenges in framing and managing human interaction with computing systems. The computing systems are expected to be context-aware [4], knowing a human agent’s current situation, activity, and interaction context especially in the physical world in facilitating human–computer interaction. Traditional interaction approaches like the WIMP (windows, icons, menus and pointing devices) interaction paradigm is not aware of a human agent’s physical context. It offers interaction through limited information channels and is overall obsolete for ambient ecologies. Several approaches like tangible user interfaces [5], ambient displays [6], surface computing [7], etc. are device-centric, while approaches like perceptual user interfaces [8], attentive user interfaces [9], affective user interfaces [10], activity-based computing [11], etc. focus on specific aspects of a human agent. Embodied interaction [12] focuses on human embodiment in an environment in facilitating interaction while reality-based interaction [13] provides a comprehensive framework for emerging trends in human–computer interaction inspired from the functioning of the real world. While such approaches are valuable from an ambient ecology context, they do not consider a human agent as a whole within an ambient ecology. This conceptual article introduces egocentric interaction as an alternative approach toward the modeling of ambient ecologies with the unique feature of taking the human agent’s body and mind as center of reference, as opposed to more common device-centric approaches in facilitating human–environment interaction.

A first assessment of the viability of the concepts is made through our experience in building a prototypical ambient ecology, named the easy ADL ecology, based on egocentric interaction principles. Outline of the article: Section 2 describes egocentric interaction and its principles; Section 3 presents the situative space model; Section 4 describes the easy ADL ecology comprising of smart objects, a personal activity-centric middleware, and ambient intelligence applications providing everyday activity support; Section 5 outlines the interaction management rules and techniques for facilitating human interaction within the ambient ecology; and Section 6, finally, makes some brief concluding remarks.

Section snippets

Principles of egocentric interaction

The easy ADL ecology to be presented in Section 4 is designed and implemented based on the principles of egocentric interaction. There are many research efforts that can be seen as working toward a new way of understanding and framing interaction between a human agent and their environment. The reason for this interest and direction in the research society is not hard to see. Important new advances in technology — communication, sensor, presentation, and actuation technology, together with the

A situative space model

When applying the general principles of egocentric interaction in the design of the ambient ecology, we chose to concretize and synthesize some of the principles into a situative space model, which could immediately be implemented into the personal activity-centric middleware. The situative space model is described in detail elsewhere [30] and only a summarized account of it is provided in this article, enough to explain the design rationale behind the development of the smart objects

The easy ADL ecology

In this section we present an ambient ecology based on egocentric interaction: the easy ADL ecology. It comprises smart objects (i.e. physical objects augmented with ambient intelligence technology, see Section 4.1), a wearable computer running a personal activity-centric middleware (refer to Section 4.2), a set of ambient intelligence applications containing virtual objects (refer to Section 4.3), and a human agent literally in the middle of it all. The virtual objects are accessible to the

Interaction management rules and techniques

The interaction manager provides access to virtual objects within the easy ADL ecology on the basis of interaction management rules that answer the important questions of if, when, where and how a virtual object should be made present and accessible on request by (a) the human agent or (b) an ambient intelligence application. The rules are prioritized according to which question they address with the if question having the highest priority, followed by the when question, the where question, and

Concluding remarks

In this article, we have presented the concepts of egocentric interaction, a novel interaction paradigm for the design and use of ambient intelligence applications. Egocentric interaction is a paradigm that is literally human-centered and based on a mobile human agent’s dynamically changing possibilities and propensities to perceive and act in an environment. To capture this flow of changes, a simplified, implementable situative space model has been developed in conjunction with an ambient

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