, Microsoft Research
, Lancaster University
, IBM T.J. Watson Research Center
Pages: pp. 33-34
In pervasive computing, content in the form of inferred context often aims to automatically trigger actions in the environment, such as notifying someone about nearby friends. However, sometimes people just want to share pervasively generated content with other people, which is one topic of this special issue.
People have a fundamental need to matter. Internet technology such as instant messaging, Facebook, and Twitter meets part of this need, letting people update their friends, in parallel, about what they're doing or thinking. Pervasive computing has the potential to automate this process by taking data from our everyday lives and elevating it to meaningful updates to share with others. This special issue on pervasive content sharing provides several examples of how to use sensing and networking to help people share information.
Based on real-world experiments, "The Use of Mobile Social Presence," by Frank Bentley and Crysta J. Metcalf, explores how people can share their context with each other using their mobile phones. The article begins with a study on how people share context information in normal phone conversations. It then describes studies with three novel prototype systems for sharing real-time context: location transitions, the currently playing song, and photos and videos. The authors find that people already share much context information in everyday phone conversation and that posting other data leads to richer context sharing.
In "An Ecosystem for Learning and Using Sensor-Driven IM Status Messages," Donald J. Patterson and his colleagues describe a new phenomenon in the continuously connected, mobile world—the ability to give frequent, short status updates via services such as Twitter, Facebook, and various instant-messaging clients. This article develops an interesting way to automatically update a person's status using simple sensors built into mobile phones. The idea is that machine learning on sensor data can recognize repeat occurrences of a mobile user's status, enabling automatic generation of status updates.
Whereas the two previous articles concentrate on one-to-many sharing of a person's context, "MobSens: Making Smart Phones Smarter" explores many-to-one sharing for creating an overview of the local environment. Eiman Kanjo and her colleagues present and evaluate prototypes measuring air and noise pollution on phones equipped with gas sensors and microphones. They also discuss sharing asthma data and more qualitative questions and answers about local environmental conditions.
Alexander Kröner and his colleagues' "A Framework for Ubiquitous Content Sharing" introduces a structure for general content sharing among people. The authors explore three pervasive content-sharing applications and use lessons learned from these applications to design SharedLife, a generic framework for pervasive content sharing.
Combined, these articles show how pervasive computing can automate our day-to-day information sharing. If this technology catches on, we envision a time when we can all automatically share our content using mobile devices, secure in the knowledge that we'll continue to matter, at least as long as the batteries last.