SOCIAL Enabling spontaneous social communication in spatially distributed groups by ambient intelligent environments

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Spontaneous and informal communication has a strong impact on the productivity, social identity, and wellbeing of work groups. In spatially collocated teams, such spontaneous communication occurs on a day-to-day basis: People occasionally meet on office floors, at coffee corners, or at lunch. However, today we often encounter spatially distributed work settings that impede casual communication between co-workers, as teams are distributed over branch offices located in different cities and countries. At the same time, existing methods for remote communication, including telephone, e-mail, videoconferencing, or social networks, are mostly targeted at supporting explicit, planned, and formal communication. Consequently, they typically fail to appropriately mimic the complexity of spontaneous and informal interpersonal communication. In the proposed project, we aim to recreate the notion of collocated spontaneous communication in spatially distributed settings. We will approach this problem space by observing, classifying, and formalizing spontaneous communication situations in collocated work group settings. As a next step, we will develop methods to computationally detect similar situations in distributed settings. The detection will be realized by recognizing and interpreting environmental features and behavioral cues using an ambient intelligence environment spanning distributed locations. We will convey detected situations to users using unobtrusive and privacy-preserving multi-modal output, and will develop appropriate interaction methods enabling users to seamlessly engage in distributed communication. Our work will contribute novel insights on computer-supported communication in distributed environments and will advance the state of the art in Pervasive Communication, Ambient Intelligence Environments, Spatial Representation and Reasoning, and multimodal Human- Computer Interaction.