Date of Graduation

5-2019

Document Type

Thesis

Degree Name

Bachelor of Science in Biological Engineering

Degree Level

Undergraduate

Department

Biological and Agricultural Engineering

Advisor/Mentor

Runkle, Benjamin

Committee Member/Reader

Runkle, Benjamin

Committee Member/Second Reader

Rom, Curt

Committee Member/Third Reader

Costello, Thomas

Abstract

Low-Impact Development (LID) is an attempt to sustainably respond to the potential hazards posed by urban expansion. Green roofs are an example of LID design meant to reduce the amount of runoff from storm events that are becoming more intense and less predictable while also providing insulation to buildings. LID has not yet been widely adopted as it is often a more expensive alternative to conventional infrastructure (Bowman et. al., 2009). However, its benefits are apparent. The University of Arkansas Honors College awarded a grant to research the large green roof atop Hillside Auditorium. One part of this grant is aimed at educating the public on the benefits LID infrastructure and encourage its development. To accomplish this task, a Raspberry Pi was programmed to operate in tandem with a Campbell Scientific CR1000 datalogger to collect, organize and tweet data to the public under the moniker, “Rufus the Roof.” It is believed that personifying the roof allows data to be conveyed in an entertaining manner that promotes education and public engagement in the LID design.

The Raspberry Pi was initially intended to collect data and publish tweets automatically on a live basis. However, automation was not realized due to time constraints and challenges in establishing connection to the datalogger. Instead, a system was developed that allowed the remote transfer of environmental data files from a datalogger on the green roof. Along with remote file transfer protocol, several Python scripts were written that enabled tweets to be published by the Raspberry Pi.

The design was successful. Manual remote file transfer and tweeting was achieved. Full automation remains to be achieved, but the Python scripts are built with the capability to operate automatically. The conditions are in place for future development of the project in order to achieve full autonomy. A fully automated system could open the doors for more widespread public engagement in the value and benefits of Low-Impact Development initiatives.

Keywords

Raspberry Pi; Remote Sensing; Green Roof; Low-Impact Development; Twitter API

Comments

This is a design-based thesis rather than a research-based thesis.

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