UC Berkeley

With the proliferation of sensor equipped smart phones, and

augmented reality applications fast appearing, the mobile phone is

becoming something much more than a scaled-down, connected IO and

processing device. In addition to these standard PC traits, a cell

phone is situated in an environment, mobile, and typically

co-located with a user. These traits make the cell-phone ideally

suited to track and understand the impact that the environment has

on individuals, communities and cities, as well as to understand how

humans effect their environment.

In this dissertation, I explore the possibility of building a

societal-scale, mobile sensing system to monitor pollution and other

environmental factors, using low cost-sensors embedded into mobile

phones. I will discuss several hardware platforms we used to study

mobile sensing over the course of three field campaigns, models of

pollution dispersion, sensor characterization and its impact on

model parameters, automatic calibration and increasing precision in

densely sampled regions.