Collaborative opportunistic sensing with mobile phones

Abstract

Mobile phones include a variety of sensors that can be used to develop context-aware applications and gather data about the user's behavior, including the places he visits, his level of activity and how frequently and with whom he socializes. The collection and analysis of these data has been the focus of recent attention in ubiquitous computing, giving rise to the field known as mobile sensing. In this work, we present a collaborative extension to InCense, a toolkit to facilitate behavioral data gathering from populations of mobile phone users. InCense aims at providing people with little or no technical background with a tool that assists in the rapid design and implementation of mobile phone sensing campaigns. By extending the architecture of InCense to support distributed sensing campaigns we are able to incorporate several strategies aimed at optimizing battery, storage, and bandwidth. These issues represent significant challenges in sensing campaigns that generate considerable amounts of data (i.e., collecting audio) or quickly drain the battery in the device (i.e., GPS), given the limitations of mobile devices. In this work, collaborative sensing is used to decide which mobile phone should capture audio when two or more devices are potentially recording a similar audio signal.