Paper
3 November 2010 VIGILANT: "situation-aware" quality of information interest groups for wireless sensor network surveillance applications
D. S. Ghataoura, J. E. Mitchell, G. E. Matich
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Abstract
Effective situation awareness is a critical element for decision support in a wide range of military and para-military operational surveillance scenarios. Effective situation awareness in a surveillance scenario can greatly increase operational effectiveness, by improving the quality and timeliness of decisions. In this paper we outline a three level integrated design approach to promote situation awareness. Our approach allows deployed wireless sensor nodes to efficiently self-organise into dynamic clusters, based on a current common perceived threat situation (context). Firstly our distributed predator aware situation assessment system (PORTENT) models, detects and presents, in terms of quality of information (QoI), potential situations occurring within an uncertain environment. Secondly, we utilise a Bayesian belief network to understand the significance associated with the potential situation. Finally in order to obtain a better shared awareness we have developed a "context aware" service protocol that supports group formation and efficient management of sensor network assets. By combining this three level approach, we present our VIGILANT "situation aware" QoI interest group system. Extensive simulations have been undertaken to verify the VIGILANT concept, to demonstrate the effectiveness of our approach, in improving performance for network management efficiency, through utilisation of a shared "context" service provision time and QoI surveillance presentation.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
D. S. Ghataoura, J. E. Mitchell, and G. E. Matich "VIGILANT: "situation-aware" quality of information interest groups for wireless sensor network surveillance applications", Proc. SPIE 7833, Unmanned/Unattended Sensors and Sensor Networks VII, 783310 (3 November 2010); https://doi.org/10.1117/12.864562
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Cited by 1 scholarly publication.
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KEYWORDS
Surveillance

Sensors

Environmental sensing

Environmental monitoring

Sensor networks

Amygdala

Target detection

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