Date of Graduation

5-2020

Document Type

Thesis

Degree Name

Bachelor of Science in Industrial Engineering

Degree Level

Undergraduate

Department

Industrial Engineering

Advisor/Mentor

Parnell, Gregory S.

Committee Member/Reader

Pohl, Edward A.

Committee Member/Second Reader

Ham, Richard

Abstract

The Department of Homeland Security (DHS) requested an Engineering Research and Development Center study incorporating modeling and simulation to determine the selection, amount, and optimal location of sensor suites along the U.S. Border. The study objective is to maximize the probability of detection and apprehension of illegal elements attempting to enter. A study on intruders and their preferences were conducted to create an intruder preference value map to determine the preferred intruder routes taken after crossing the border. The results of this research were integrated into another study on the selection and simulation of sensor suites.

Intruder context and preferences were researched to determine the relevant terrain characteristics to avoid detection after crossing the border. An initial scenario was created to include the remote Chinati Peak region (along the Texas-Mexico border) for dismounted intruders with no information on current sensors. Geospatial data representing terrain characteristics and metadata of the region were combined on a common value scale based on decision analysis techniques using the ArcGIS Python library (ArcPy) to create an intruder preference map. The weights were adjusted to represent different types of intruders or intrusion scenarios.

The intruder preference map was then used to create routes for intruders in the Chinati peak region. Starting locations for intruders were created based on the U.S.-Mexico border and ending locations were created an arbitrary distance away, e.g. 30 miles. The ArcGIS Distance Accumulation function was used to create a least-cost route from each starting point to each ending point based on the intruder preference map. The mesh of probable routes was then output to the sensor selection and simulation model for hot spot analysis. A sensitivity analysis was then conducted by changing the weights of the inputs into the intruder preference map to examine the flexibility of capturing intruder preferences.

Prioritized future work will include new areas of analysis other than the Chinati Peak region, new scenarios, and improvements on the ArcPy model. An automated method for the creation of starting and ending points should be created. A new scenario incorporating the use of vehicles while crossing should be implemented. Obstacles should be incorporated directly into routing rather than using weights. Continued research on quantifying intruder behavior, motivation, and preferences should also be conducted. Corridor analysis and other stochastic approaches should be considered to add uncertainty to the preferred intruder routes.

Keywords

Intruder Behavior; Intruder Preference Map; GIS; Border Security

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