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http://dx.doi.org/10.3837/tiis.2021.12.013

Sensor Density for Full-View Problem in Heterogeneous Deployed Camera Sensor Networks  

Liu, Zhimin (School of Mathematics and Computational Science, Hunan First Normal University)
Jiang, Guiyan (School of Economics, Wuhan University of Technology)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.15, no.12, 2021 , pp. 4492-4507 More about this Journal
Abstract
In camera sensor networks (CSNs), in order to better identify the point, full-view problem requires capture any facing direction of target (point or intruder), and its coverage prediction and sensor density issues are more complicated. At present, a lot of research supposes that a large number of homogeneous camera sensors are randomly distributed in a bounded square monitoring region to obtain full-view rate which is close to 1. In this paper, we deduce the sensor density prediction model in heterogeneous deployed CSNs with arbitrary full-view rate. Aiming to reduce the influence of boundary effect, we introduce the concepts of expanded monitoring region and maximum detection area. Besides, in order to verify the performance of the proposed sensor density model, we carried out different scenarios in simulation experiments to verify the theoretical results. The simulation results indicate that the proposed model can effectively predict the sensor density with arbitrary full-view rate.
Keywords
Camera sensor networks; full view; sensor density; sensor prediction;
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