Paper Info
Title
Drone-Aided Border Surveillance with an Electrification Line Battery Charging System.
Abstract
This paper proposes to develop a drone-aided border surveillance system with electrification line battery charging systems (DABS-E). Currently, mobile and fixed border surveillance systems such as truck-mounted video recording units, agent portable surveillance units, aerostats, and fixed towers are often used to enhance the comprehensive situational awareness along the U.S. border lines. However, a few drawbacks of the existing systems include limited operating capability, blind spots, physical fatigue of field agents, and lack of fast-responding situational awareness capability. The use of drones and mobile technologies are an ideal way to overcome these issues in border patrol activities. Even though drones bring numerous technical advantages (i.e., short response time, being able to access dangerous areas, and no on-board pilot required) for the border patrol mission, a relatively short flight duration is the main concern for the full implementation for patrol at this time. Therefore, this paper proposes a new concept that is built on electrification line (E-line) systems to wirelessly charge drones during the flight to extend flight duration. As a result, extra power can be provided for drones without the need of landing, stopping or returning back to ground control centers. To accomplish our goal, this paper proposes an optimization model and algorithm to schedule drone flights for a DABS-E. Through a numerical example, this paper shows the feasibility of our proposed method and corresponding economic benefits.
Year
DOI
Venue
2018
10.1007/s10846-017-0767-3
Journal of Intelligent and Robotic Systems
Keywords
Field
DocType
Border patrol, Drone, Wireless power transfer, Remote surveillance system, Battery charging
Mobile technology,Wireless power transfer,Physical Fatigue,Situation awareness,Computer security,Response time,Control engineering,Drone,Engineering,Battery (electricity),Electrification
Journal
Volume
Issue
ISSN
92
3-4
0921-0296
Citations 
PageRank 
References 
4
0.46
4
Authors
2
Name
Order
Citations
PageRank
Seon Jin Kim1192.46
Gino J. Lim211516.51