Data sensors are ubiquitous in our daily lives, collecting information about how we move, where we eat, and with whom we communicate. Sensors have also become a strategic and efficient means for collecting data on transportation by recording how people commute in and around urban environments, and if these movements collectively demonstrate signs of sustainable transportation. The objective of our project is to develop and deliver a course on the use of sensors for transportation planning called Advanced GIS: Smart Transportation. We aim to provide a curriculum on how to utilize sensor data and produce data to the public through innovative visualizations. The proposed course will bring together existing NITC funded research with PI’s Bone, Kato, and Schlossberg, NITC funded technology transfer via live sensors that serve as bicycle counters, and NITC funded student activity by means of the LiveMove project. The course will integrate in-class work sessions
  and topic expert discussions with online readings and electronic communications to provide a novel and highly rewarding experience for students. The course will be aim to create small teams of students from a wide variety of majors – working collectively to create a published product.