Detecting Tunnels for Border Security based on Fiber Optical Distributed Acoustic Sensor Data using DBSCAN

被引：4
作者：
Aslangul, Suleyman Alpay [1 ]
机构：
[1] ASELSAN Mehmet Akif Ersoy, UGES Div, ASELSAN Homeland Secur Programs Dept, Mah 296 Cad 16, TR-06370 Yenimahalle Ankara, Turkey
来源：
PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON SENSOR NETWORKS (SENSORNETS) | 2020年
关键词：
Smart Border Security; Homeland Security; Intrusion Detection; DAS Fiber Optic Sensors; Data Mining; DBSCAN; Standard Deviation; Software; Situational Awareness; Machine Learning;
D O I：
10.5220/0008869600780084
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The Border Situational Awareness may consist of many different features. Mainly, these features focus on detecting intrusion activities. New generation security systems are collecting important amount of data obtained from sensors. In general, the alarm confirmation mechanism is visual identification using cameras and Video Management Systems. On the other hand, this approach may not be enough to identify an invisible tunnel digging activity underground for trespassing the border. This paper is suggesting a new method to detect tunnels by using statically filtered alarm data and DBSCAN algorithm. In this particular case MIDAS (R) Fiber Optic based Distributed Acoustic Sensor (DAS) system is used, which is designed by ASELSAN Inc. The proposed approach is evaluated and positive results are seen on diverse areas of the Turkish borders.
引用
收藏
页码：78 / 84
页数：7
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