Date of Graduation

5-2026

Document Type

Thesis

Degree Name

Bachelor of Science in Data Science

Degree Level

Undergraduate

Department

Data Science

Advisor/Mentor

Dr. Karl Schubert

Committee Member

Dr. Tianjiao Adams

Second Committee Member

Dr. Kelly Sullivan

Abstract

The purpose of this paper is to analyze patterns between public safety and streetlighting for the City of Sugar Land, TX so that they may better protect their citizens.  The data involved come from the City of Sugar Land’s public works division and include type and location for all the attributes. The method of doing so involved visualizing the patterns of streetlights and their closest light readings to visualize which streetlights are underperforming using the Shiny package in R. Statistical tests were also used to quantify the association between lighting, crime occurrence, and crosswalks. From this, and the literature review, there is no significant evidence that the City of Sugar Land’s lighting quality has had a major impact on public safety. Ideally, more mathematical modeling will be used to analyze this problem in the future.

Keywords

Geospatial; Data Science; Statistics; Public Works

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