TY  - CONF
Y1  - 2020///
TI  - Solving Surveillance Coverage Demand Based on Dynamic Programming
AV  - none
N1  - cited By 3; Conference of 15th IEEE Sensors Applications Symposium, SAS 2020 ; Conference Date: 9 March 2020 Through 11 March 2020; Conference Code:164022
SN  - 9781728148427
A1  - Altahir, A.A.
A1  - Asirvadam, V.S.
A1  - Sebastian, P.
A1  - Hamid, N.H.
PB  - Institute of Electrical and Electronics Engineers Inc.
KW  - Efficiency; Maps; Planning; Sensor arrays
KW  -  Coverage efficiencies; Dynamic programming algorithm; Greedy search; Installation costs; Near-optimal; Risk mappings; Security-critical; Visual sensor
KW  -  Dynamic programming
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095564106&doi=10.1109%2fSAS48726.2020.9220039&partnerID=40&md5=baa0f9354d298c3d97fa09a605345f85
ID  - scholars13386
N2  - Typical visual sensor planning approaches install visual sensors arrays to increase the amount of coverage and/or decrease the installation cost. These planning approaches operate with no stress on coverage demand, thus, optimizing the visual sensor placement based on equally significance grids. This paper addresses the visual sensor coverage efficiency based on a combination of risk mapping and dynamic programming. The improved coverage efficiency is obtained by utilizing a prior routine to highlight the security critical regions. Then, a dynamic programming algorithm is used to compute a near optimal coverage solution. The result of the dynamic programming is evaluated with respect to global greedy search outcomes. The comparison reveals the reliability of the visual sensor planning using risk maps and dynamic programming. © 2020 IEEE.
ER  -