A Comparison of LOS Detection Probability Area for DEM and DSM

Song, Hyun-Seung; Park, Wang-Yong; Park, Hyun-Chun; Lee, Young Lim

doi:10.7848/ksgpc.2011.29.2.165

Cited by 1 publication

(1 citation statement)

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“…As it is highly probable that the TOD which is located in the low area cannot have a large visible area (Song et al, 2011),…”

Section: Initial Solutionmentioning

confidence: 99%

A Genetic Algorithm to Solve the Optimum Location Problem for Surveillance Sensors

Kim

et al. 2016

Journal of the Korean Society of Surveying, Geodesy, Photogramm

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Due to threats caused by social disasters, operating surveillance devices are essential for social safety. CCTV, infrared cameras and other surveillance equipment are used to observe threats. This research proposes a method for searching for the optimum location of surveillance sensors. A GA (Genetic Algorithm) was used, since this algorithm is one of the most reasonable and efficient methods for solving complex non-linear problems. The sensor specifications, a DEM (Digital Elevation Model) and VITD (Vector Product Interim Terrain Data) maps were used for input data. We designed a chromosome using the sensor pixel location, and used elitism selection and uniform crossover for searching final solution. A fitness function was derived by the number of detected pixels on the borderline and the sum of the detection probability in the surveillance zone. The results of a 5-sensor and a 10-sensor were compared and analyzed. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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“…As it is highly probable that the TOD which is located in the low area cannot have a large visible area (Song et al, 2011),…”

Section: Initial Solutionmentioning

confidence: 99%