Building Intrusion Detection with a Wireless Sensor Network

Wälchli, Markus; Braun, Torsten

doi:10.1007/978-3-642-11723-7_41

Cited by 4 publications

(2 citation statements)

References 20 publications

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“…In particular, collecting multiple video streams imposes high demands on storage, online monitoring, and video analysis. The WSN (wireless sensor network) technology provides means to develop such a system with low costs [1]. The WSN can run standalone or it can be used to trigger external surveillance system like a video system.…”

Section: Introductionmentioning

confidence: 99%

WSN-Based Height Estimation of Moving Object in Surveillance Systems

Shim¹,

Lim

2016

Mobile Information Systems

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In the WSN- (wireless sensor network-) based surveillance system to detect undesired intrusion, all detected objects are not intruders. In order to reduce false alarms, human detection mechanism needs to determine if the detected object is a human. For human detection, physical characteristics of human are usually used. In this paper, we use the physical height to differentiate an intruder from detected objects. Using the measured information from sensors, we estimate the height of the detected object. Based on the height, if the detected object is decided as an intruder, an alarm is given to a control center. The experimental results indicate that our mechanism correctly and fast estimates the height of the object without complex computation.

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Section: Introductionmentioning

confidence: 99%

WSN-Based Height Estimation of Moving Object in Surveillance Systems

Shim¹,

Lim

2016

Mobile Information Systems

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“…In recent times, the use of WSN's has been extended to detect time-related anomalies [4] with a mobile robot using a technique called fuzzy Adaptive Resonance Theory (ART) neural network. Enhancements were made to make the anomaly detector a self-learning detector [5] that addresses detection and monitoring of abnormal behavior inside the buildings.…”

Section: Introductionmentioning

confidence: 99%

Intruder detection in public space using suspicious behavior phenomena and wireless sensor networks

Suthaharan

Bandari

2012

Proceedings of the 1st ACM International Workshop on Sensor-Enhanced Safety and Security in Public Spaces

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Automatic detection of intruders in a public space is an important requirement for the safety of innocent citizens. Recently suspicious behavior based automatic detection models are proposed to address this problem. Wireless Sensor Networks (WSN) is adopted in the implementation and the evaluation of these models. In this paper we propose a WSN-based trajectory enhanced graphical model to detect the intruders in public space. In our model a supervised learning approach is used to estimate the threshold for speed parameter of the suspicious and unsuspicious tracks. The threat levels are increased when a person's trajectory deviates from an unsuspicious track, where it is closer to a suspicious track. Suspicious behavior of a person is detected using a threat level parameter that depends on the speed and direction of the subject. We show using the synthetic data that, the model is capable of detecting human intruders based on the suspicious behavior, and it is worth applying the model to real data sets and investigate its performance further.

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Building Intrusion Detection with a Wireless Sensor Network

Cited by 4 publications

References 20 publications

WSN-Based Height Estimation of Moving Object in Surveillance Systems

WSN-Based Height Estimation of Moving Object in Surveillance Systems

Intruder detection in public space using suspicious behavior phenomena and wireless sensor networks

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