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Proceedings Paper

Cost optimization of a sky surveillance visual sensor network
Author(s): Naeem Ahmad; Khursheed Khursheed; Muhammad Imran; Najeem Lawal; Mattias O'Nils
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Paper Abstract

A Visual Sensor Network (VSN) is a network of spatially distributed cameras. The primary difference between VSN and other type of sensor networks is the nature and volume of information. A VSN generally consists of cameras, communication, storage and central computer, where image data from multiple cameras is processed and fused. In this paper, we use optimization techniques to reduce the cost as derived by a model of a VSN to track large birds, such as Golden Eagle, in the sky. The core idea is to divide a given monitoring range of altitudes into a number of sub-ranges of altitudes. The sub-ranges of altitudes are monitored by individual VSNs, VSN1 monitors lower range, VSN2 monitors next higher and so on, such that a minimum cost is used to monitor a given area. The VSNs may use similar or different types of cameras but different optical components, thus, forming a heterogeneous network. We have calculated the cost required to cover a given area by considering an altitudes range as single element and also by dividing it into sub-ranges. To cover a given area with given altitudes range, with a single VSN requires 694 camera nodes in comparison to dividing this range into sub-ranges of altitudes, which requires only 88 nodes, which is 87% reduction in the cost.

Paper Details

Date Published: 2 May 2012
PDF: 15 pages
Proc. SPIE 8437, Real-Time Image and Video Processing 2012, 84370U (2 May 2012); doi: 10.1117/12.924344
Show Author Affiliations
Naeem Ahmad, Mid Sweden Univ. (Sweden)
Khursheed Khursheed, Mid Sweden Univ. (Sweden)
Muhammad Imran, Mid Sweden Univ. (Sweden)
Najeem Lawal, Mid Sweden Univ. (Sweden)
Mattias O'Nils, Mid Sweden Univ. (Sweden)

Published in SPIE Proceedings Vol. 8437:
Real-Time Image and Video Processing 2012
Nasser Kehtarnavaz; Matthias F. Carlsohn, Editor(s)

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