Title

Integrating Raspberry Pi and drone technology for student-led primary data collection in an advanced GIS class

Date

6-1-2017 11:00 AM

End Time

1-6-2017 1:00 PM

Location

WUC Pacific Room

Department

Earth Science

Session Chair

Melinda Shimizu

Session Title

Applications of Geospatial Technology

Faculty Sponsor(s)

Melinda Shimizu

Presentation Type

Poster session

Abstract

The Raspberry Pi is an ultra-small kit computer designed for education. While it generally has a small amount of resources on board, the computer appeals to students, educators, and hobbyists alike because of its General Purpose Input/Output (GPIO) pins. These pins can be attached to sensors (a variety of which can be found online,) and data can be read easily with only a few lines of code. Directly out of the box, the potential for innovation is immense. This poster outlines the process of using a drone, Raspberry Pi, and components to collect spatial data for and advanced GIS class. The methods presented here serve as a model for other programs or classes that might similarly benefit by empowering students to collect and analyze their own primary spatial data.

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Jun 1st, 11:00 AM Jun 1st, 1:00 PM

Integrating Raspberry Pi and drone technology for student-led primary data collection in an advanced GIS class

WUC Pacific Room

The Raspberry Pi is an ultra-small kit computer designed for education. While it generally has a small amount of resources on board, the computer appeals to students, educators, and hobbyists alike because of its General Purpose Input/Output (GPIO) pins. These pins can be attached to sensors (a variety of which can be found online,) and data can be read easily with only a few lines of code. Directly out of the box, the potential for innovation is immense. This poster outlines the process of using a drone, Raspberry Pi, and components to collect spatial data for and advanced GIS class. The methods presented here serve as a model for other programs or classes that might similarly benefit by empowering students to collect and analyze their own primary spatial data.