Advanced GIS: Transportation – Sensors – and the Smart City

Whether they are inside our smartphones, embedded in our appliances, attached to buildings and utilities or flying above our heads – sensors are contributing an unprecedented amount of real-time “big data” that has the potential to alter the way cities function and how we move around within them.

This course will explore how sensors can be employed for the collection and visualization of transportation data. The objective of the course is to expose students to sensor technologies that facilitate the ubiquitous collection of data pertaining to individual movement and perceptions as related to transportation behavior. In particular we will focus on a new bike sensor currently being installed on our campus. Students will learn about the technology of sensors, the type of data they produce, how such data can be used, and the societal issues that sensors impose on individuals. Course assignments will allow students to collect sensor-derived data from smart phones, weather stations and bike counters that collectively will help to answer questions regarding sustainable modes of transportation. Students will learn how to design and deploy a project that makes use of a variety of sensors – featuring our campus bike sensor- to explore bicycling transportation at the University of Oregon.

Please visit the following site to see the creative visualizations developed by students in the class. These students went above and beyond to explore the use of D3 to create custom data visualizations, pulling directly from the sensors in the bike counter as well as a weather sensors we set up during the class. Bike Counter @ UO.

The development of this course was facilitated by the generous support from the National Institute of Transportation and Communities.

Tableau’s data visualization software is provided through the Tableau for Teaching program.