Award Date

8-1-2024

Degree Type

Thesis

Degree Name

Master of Science in Engineering (MSE)

Department

Electrical and Computer Engineering

First Committee Member

Emma Regentova

Second Committee Member

Venkatesan Muthukumar

Third Committee Member

Mei Yang

Fourth Committee Member

Alexander Barzilov

Number of Pages

50

Abstract

In this work, we develop an innovative system for the automated measurement of Water Drop Penetration Time (WDPT) - a parameter that is conventionally used for evaluating soil water repellency (SWR). Increased SWR can be a reason for plant stress and poor crop yields, create a risk of potential water runoff and floods and thus can pose risks to life and property loss. Timely evaluation of soil conditions can save resources and win time for responding to environmental disasters. Manual measurements of WDPT are labor-intensive, subjective, tend to produce variability of outcomes, and also not always available in remote or not easily reachable locations. To overcome these limitations, and perform tests in both lab settings and field deployment, we developed a system for automatically performing a standardized WDPT test, estimating WDPT and evaluating SWR. The experimental system records video clips of the water drop placed on the soil surface from a fixed height and in a fixed small volume using a solenoid valve. The entire process from a drop landing on the soil surface to its complete absorption is modeled as a temporal action and consequently, the WDPT estimation is solved using Temporal Action Localisation (TAL) deep learning models. A number of decisions are made for identifying the most efficient models, and designing the end-to-end processing system for WDPT estimation and SWR evaluation. This research contributes to the National Science Foundation (NSF) EPSCoR project “Harnessing the Data Revolution for Fire Science (HDRFS)” through the seed grant “A Machine Learning Framework for Measuring Water Drop Penetration Time (WDPT) of Fire-Affected Soils.”

Keywords

Machine Learning; Soil Water Repellency; Temporal Action Localization; Water Drop Penetration Time

Disciplines

Computer Engineering | Electrical and Computer Engineering

File Format

pdf

File Size

7600KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

Rights

IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

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