Author
Listed:
- Rhonil Victor G. Gaylon
(Pamantasan ng Lungsod ng Maynila (University of the City of Manila), Philippines)
- Reyn A. Galapia
(Pamantasan ng Lungsod ng Maynila (University of the City of Manila), Philippines)
- Romie C. Mabborang
(Pamantasan ng Lungsod ng Maynila (University of the City of Manila), Philippines)
- Alvin G. Bansil
(Pamantasan ng Lungsod ng Maynila (University of the City of Manila), Philippines)
Abstract
The installation of CCTV cameras monitoring the street sections of one of the most visited areas of Manila may serve as deterrence against theft, crime, abduction, and even act of lasciviousness. Furthermore, the redundant orientations of some of the units in the system were recognized as possible inhibitors of the efficiency of the local surveillance system. In line with this, the study proposed a model for CCTV camera placement in Intramuros by representing the community as a graph in a 2-dimensional space. The paper presents a two-phase approach in determining the best placements of CCTV cameras. Phase I took care of the ideal installation spots as a set-covering problem while Phase II identified the optimal CCTV orientation using the Proposed algorithm. In Phase I, a binary integer programming model was formulated and solved using the data solver function of Microsoft Excel. The designed algorithm in Phase II was based on greedy heuristics utilizing the results in Phase I to identify the optimal orientation of the CCTV units. Findings suggest that out of the seventeen candidate locations, nine of them are optimal for CCTV installation. A total of twenty-three CCTV units are required to cover all the entry and exit points of the streets in district 5 of Intramuros. The proposed algorithm produced two optimal solutions A and B. Comparison with the existing CCTV system in the district and discussions on each optimal installation suggested that result B is better than A. Recommendations on the results of the study were addressed to the authorities of district 5 for immediate implementation.
Suggested Citation
Handle:
RePEc:epw:comput:v:2:y:2022:i:6:id:10075
DOI: 10.24018/compute.2022.2.6.75
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