Design and deploy : iterative methods in adapting mobile technologies for data acquisition : a case study in St. Louis, Missouri

Abstract

Advancements in mobile technology provide the opportunity to explore not only how data gathering (e.g., surveying) can be eased through digital input mechanisms, but also how such devices can bring new resolution to data gathered. This thesis covers the development history of an Android-based application, Flocktracker. Flocktracker incorporates techniques capitalizing on standard modern locational sensors on Android devices, demonstrating how data ranging from vehicle speeds to locations, directions, and on-board conditions can be relatively easily gathered. The research then deploys Flocktracker to explore the spatiotemporal dynamics of onboard security perception, as reported by users, along the 70 bus line in St. Louis. Over a brief, three-day period in March, an on-board survey was implemented via Flocktracker. Based on this field work, the thesis presents aspects of the route data collected (origin-destination, ridership, speed, uploads activity by time of day), as well as a multivariate, ordered logit model of users' reported security perceptions, incorporating additional spatial data (e.g., on crime). Results from this model indicate the user-reported security perceptions relate significantly to highly localized aspects of a route, such as proximity to homicides, public disorder, property crimes, vacancies, vehicle speed, and relative location along the route.