Smartphone-Based Visitor Analytics
Abstract
A visitor study is the interdisciplinary study of humans in a public learning environment, such as a park, zoo, or aquarium. Researchers collect visitor information in many ways: by enlisting participants to fill out a survey or visit diary, by directly observing visitors, or by handing out GPS devices. For example, a zoo wants to discover when certain areas are the most crowded, so they place employees in those areas to keep track of visitor counts. While this method can be effective in determining visitor counts, it requires paying employees and researchers hourly, having an idea already of what days are the most popular, and buying supplies to record data. Also, the study is limited to the most popular days and usually restricted by a budget. In this thesis we present a new method that has never been done before in the form of a smartphone application that provides a continuous source of information for collection. We developed the client software, an Android smartphone app that allows visitors to enrich their experience at the Bronx Zoo. We also built the server, a Linux Fedora 18 server that carries out visitor analytics and stores information in the database of visitor information. The client provides visitors with a map of the zoo, their current location, and pertinent information about the zoo (exhibits, restrooms, restaurants, etc.). By using this app, we obtain GPS traces from the visitors’ smartphones, which allow us to precisely track and store their movements throughout the zoo. We will use this information, combined with demographics that we collect via a survey on the smartphone, to provide analytics to the Wildlife Conservation Society about how the zoo is utilized. With this detailed GPS data we to provide analytics that are far more comprehensive than most previous visitor studie
Subject Area
Computer science
Recommended Citation
Grosner, Andrew, "Smartphone-Based Visitor Analytics" (2013). ETD Collection for Fordham University. AAI13853143.
https://research.library.fordham.edu/dissertations/AAI13853143
