Files in this item

FilesDescriptionFormat

application/pdf

application/pdfMEDHURST-THESIS-2020.pdf (16MB)
(no description provided)PDF

Description

Title:Photogrammetry, cloud storage, virtual reality, and augmented reality to guide radiation measurement planning and visualization process
Author(s):Medhurst, Erik Andrew
Advisor(s):Uddin, Rizwan; Huff, Kathryn
Department / Program:Nuclear, Plasma, & Rad Engr
Discipline:Nuclear, Plasma, Radiolgc Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):photogrammetry, cloud storage, virtual reality, augmented reality, radiation measurement, visualization
Abstract:Localizing a radiation source in an urban environment is a challenge in nuclear nonproliferation and radiation detection. One approach to localize a source is to send a mobile radiation sensor network into an area of interest to collect count rate measurements at many locations in an attempt to find the radiation source. However, there are numerous temporal and spatial factors that cause changes in background count rate measurements, and these factors make it challenging to analyze the collected data. Displaying these measurements in a virtual environment has contextualized them and helps a user determine if environmental factors are introducing false positives. A virtual model has been shown to visualize collected measurements in near real-time, but not in real-time. The ability for a user to quickly address alarm measurements is hampered by this lack of real-time data access as well as due to poor quality virtual models. Another challenge in radiation detection is sampling an environment to assess the status of an area following a radiological or nuclear incident. Following an incident, environmental samples must be collected and analyzed to identify the radioactive substances present and assess the environmental damages. Incident response must be rapid and the sample collection must occur without error. A software named Visual Sample Plan (VSP) has been developed by Pacific Northwest National Laboratory (PNNL) to help guide the sample collection process and statistically inform decisions. This thesis begins with an overview of the radiation source search and environmental sampling problems and how they have been addressed. Next, earlier work that has attempted to address each of these problems and the motivation for these responses is discussed. Finally, new work extending the prior solutions is discussed. To address the radiation source search problem, a method to create higher quality 3D models is explored, and an alternate method to store and retrieve data in the cloud using DynamoDB is implemented. By implementing VSP in Augmented Reality (AR), opportunities for error are further limited. This thesis concludes with suggestions for future work to approach robust solutions to each problem.
Issue Date:2020-05-15
Type:Thesis
URI:http://hdl.handle.net/2142/108067
Rights Information:Copyright 2020 Erik Medhurst
Date Available in IDEALS:2020-08-26
Date Deposited:2020-05


This item appears in the following Collection(s)

Item Statistics