An Ecosystem for Learning and Using Sensor-Driven IM Status Messages

Authors:
Donald J. Patterson;Xianghua Ding;Samuel J. Kaufman;Kah Liu;Andrew Zaldivar
Affiliations:
University of California, Irvine.;University of California, Irvine;University of California, Irvine,;University of California, Irvine;University of California, Irvine
Venue:
IEEE Pervasive Computing
Year:
2009

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Abstract

This article presents a prototype system (Nomatic) that automatically infers users' place, activity, and availability from sensors on their handheld devices or laptop computers and then reports this information to their instant-messaging contacts. Rather than trying to interpret users' context independently from their needs, the authors attempt to support users in repeating their own labeling behavior in similar situations. They present additional Nomatic-based applications that support their view that sustained status setting behavior depends on a complete communications ecosystem that provides for easy status entry, a variety of perception channels, and intrinsic motivation.