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Journal Article
Hybrid Sensor Network-Based Indoor Surveillance System for Intrusion Detection
- Authors
- Hasil Park, Jinho Park, Heegwang Kim, Sung Q Lee, Kang-Ho Park, Joonki Paik
- Issue Date
- 2018-06
- Citation
- Symmetry, v.10 no.6, pp.1-17
- ISSN
- 2073-8994
- Publisher
- MDPI AG
- Language
- English
- Type
- Journal Article
- Project Code
- 17MB1200, Commerciallization of security module using sound field sensor , Kang-Ho Park
- Abstract
- This paper presents a novel hybrid sensor-based intrusion detection system for low-power surveillance in an empty, sealed indoor space with or without illumination. The proposed system includes three functional steps: (i) initial detection of an intrusion event using a sound field sensor; (ii) automatic lighting control based on the detected event, and (iii) detection and tracking the intruder using an image sensor. The proposed hybrid sensor-based surveillance system uses a sound field sensor to detect an abnormal event in a very low-light or completely dark environment for 24 h a day to reduce the power consumption. After detecting the intrusion by the sound sensor, a collaborative image sensor takes over an accurate detection and tracking tasks. The proposed hybrid system can be applied to various surveillance environments such as an office room after work, empty automobile, safety room in a bank, and armory room. This paper deals with fusion of computer-aided pattern recognition and physics-based sound field analysis that reflects the symmetric aspect of computer vision and physical analysis.
- KSP Keywords
- Computer Vision(CV), Detection and tracking, Hybrid Sensor Network, Image Sensor, Indoor Space, Intrusion detection system(IDS), Intrusion event, Lighting control, Low light, Low-Power, Office room
This work is distributed under the term of Creative Commons License (CCL)
(CC BY)
(CC BY)
