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

Topics: Big Data; Computational Intelligence; Cross-Layer Design; Data Quality and Integrity; Decision Support Systems; Defense and Security; Environment Monitoring; Information Retrieval and Data Mining; Multi-Sensor Data Processing; Optical Sensors; Programming and Middleware; Scheduling, Tasking and Control; Security Threats

Author: Suleyman Alpay Aslangul

Affiliation: ASELSAN Homeland Security Programs Department, UGES Division ASELSAN Mehmet Akif Ersoy Mah. 296. Cad. No: 16 06370 Yenimahalle Ankara/ Turkey aaslangul@aselsan.com.tr

Keyword(s): Smart Border Security, Homeland Security, Intrusion Detection, DAS Fiber Optic Sensors, Data Mining, DBSCAN, Standard Deviation, Software, Situational Awareness, Machine Learning.

Abstract: 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® 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.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Aslangul, S. A. (2020). Detecting Tunnels for Border Security based on Fiber Optical Distributed Acoustic Sensor Data using DBSCAN. In Proceedings of the 9th International Conference on Sensor Networks - SENSORNETS; ISBN 978-989-758-403-9; ISSN 2184-4380, SciTePress, pages 78-84. DOI: 10.5220/0008869600780084

@conference{sensornets20,
author={Suleyman Alpay Aslangul},
title={Detecting Tunnels for Border Security based on Fiber Optical Distributed Acoustic Sensor Data using DBSCAN},
booktitle={Proceedings of the 9th International Conference on Sensor Networks - SENSORNETS},
year={2020},
pages={78-84},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008869600780084},
isbn={978-989-758-403-9},
issn={2184-4380},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Sensor Networks - SENSORNETS
TI - Detecting Tunnels for Border Security based on Fiber Optical Distributed Acoustic Sensor Data using DBSCAN
SN - 978-989-758-403-9
IS - 2184-4380
AU - Aslangul, S.
PY - 2020
SP - 78
EP - 84
DO - 10.5220/0008869600780084
PB - SciTePress

- Science and Technology Publications, Lda.
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