Date of Graduation

5-2024

Document Type

Thesis

Degree Name

Bachelor of Science in Data Science

Degree Level

Undergraduate

Department

Data Science

Advisor/Mentor

Specking, Eric

Committee Member

Schubert, Karl

Second Committee Member

Parnell, Gregory

Third Committee Member

Curry, Rob

Abstract

Heat related injuries are a significant problem for the United States Armed Forces. There were over 11,000 confirmed cases of heat-related illnesses that were diagnosed at more than 230 military installations from 2018-2022. These injuries are primarily due to hyperthermia (i.e., abnormally high body temperature) resulting from extreme environmental temperatures, high humidity, medications, or excessive physical work or exercise. Fort Moore has the most heat related injuries of any installation in the U.S. Department of Defense since it is home to one of the largest U. S. Army training posts with most training involving intensive outdoor activity in high heat and humidity. Data was collected by collaborating with Fort Moore’s Heat Center to acquire an initial dataset of 2,723 observations for 2017 to 2022. Despite the concerning rise in heat-related injuries, current research investigating the causes and implementing statistical approaches for decision-making within the military remains limited. This research aims to address this gap. The methodology involves conducting an exploratory analysis to identify conditions under which heat-related injuries occur during army training events. Subsequently, predictive models were developed to estimate the probability of a training event resulting in a heat stroke. Furthermore, optimization techniques were implemented to construct a prescriptive model that provides guidance in making optimal training schedules that minimize the probability of heat stroke occurring during training events. The potential benefits of the research would be to better utilize statistical methods to tailor decision-making guidelines, leading to more effective reduction of heat-related injuries compared to existing guidelines. In the future, it would be beneficial to receive data that contains the health and conditioning of the soldiers who experience a heat related injury. Access to this data would provide additional important insights into heat related injuries during military training.

Keywords

Heat Related Injury; Wet-Bulb Globe Temperature; Risk Assessment; Binary Classification; Scheduling Optimization

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Available for download on Wednesday, April 30, 2025

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