Seeing Our Signals: Combining location traces and web-based models for personal discovery (original) (raw)

2007, Center for Embedded Network Sensing

A new mobility application Each of us has a complex and reciprocal relationship with our environment. Based on limited knowledge of this interwoven set of influences and consequences, we constantly make choices: where to live, how to go to work, what brands to buy, what to do with our leisure time. These choices evolve into patterns, and these patterns become driving functions of our relationship with the world around us. With increasing ease, devices we carry can sense, process, and transmit data on these patterns for our own use or to share, carefully, with others. In particular, here we will focus on location time series, gathered from GPS-enabled personal mobile devices. From this capacity emerges a new class of hybrid mobile-web applications that, first, enable personal exploration of our own patterns and, second, use the same data to index our life into other available datasets about the world around us. Such applications, revealing the previously unobservable about our own lives, offer an opportunity to employ mobile technology to illuminate the ramifications of our choices on others and the effects of the "microenvironments" we move through on us. This paper proposes and demonstrates how easily gathered location time series data can be used as an index into geospatial models to infer personal environmental impact and exposure. It focuses on three areas of interaction between individuals and the environment: transportation mode choice, overall carbon footprint, and opportunities for healthy eating. This class of applications represents a novel use of mobile systems, web-based mapping, and geospatial data and services. They pose interesting technical challenges and require multidisciplinary research.