Honors: All College Participants

Title

Artificial Intelligence for Detecting and Tracking Terror Suspects

Academic Level at Time of Presentation

Senior

Major

CSC

Minor

CSC Area

List all Project Mentors & Advisor(s)

Stanley Jointer II, PhD; Jeffrey Osborne, PhD.

Presentation Format

Oral Presentation

Abstract/Description

This thesis shows the details of an artificial intelligence that can be used to track terror suspects in a city. The design relies on spectrometers that can detect the chemical makeup of compounds within its detection range. The artificial intelligence shows which locations throughout the city are likely to be targeted by a suspect, and the user interface shows the danger level of each location near the suspect. The goal of this thesis is to show that this design would make it much more difficult to carry dangerous compounds throughout a city unnoticed. The cities in which this design is implemented would be less likely to be the target of street level terrorist attacks.

Location

Classroom 211, Waterfield Library

Start Date

November 2016

End Date

November 2016

Affiliations

Honors Thesis

This document is currently not available here.

Share

COinS
 
Nov 16th, 1:30 PM Nov 16th, 4:00 PM

Artificial Intelligence for Detecting and Tracking Terror Suspects

Classroom 211, Waterfield Library

This thesis shows the details of an artificial intelligence that can be used to track terror suspects in a city. The design relies on spectrometers that can detect the chemical makeup of compounds within its detection range. The artificial intelligence shows which locations throughout the city are likely to be targeted by a suspect, and the user interface shows the danger level of each location near the suspect. The goal of this thesis is to show that this design would make it much more difficult to carry dangerous compounds throughout a city unnoticed. The cities in which this design is implemented would be less likely to be the target of street level terrorist attacks.