##plugins.themes.bootstrap3.article.main##

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.

References

  1. Saad M. CCTV-Where Did It All Begin? [Internet] 2022 Available from: https://www.get-licensed.co.uk/get-daily/cctv-history/
     Google Scholar
  2. Ratcliffe J. Video Surveillance of Public Places. Center for Problem-Oriented Policing, Inc. 2011.
     Google Scholar
  3. Skogan WG. The Future of CCTV. Criminology & Public Policy. 2019: 161-166.
     Google Scholar
  4. IT Explained: CCTV. [Internet] 2022 Available from: https://www.paessler.com/it-explained/cctv
     Google Scholar
  5. Bischoff P. Surveillance camera statistics: which cities have the most CCTV cameras? [Internet] 2021 Available from: https://www.comparitech.com/vpn-privacy/the-worlds-most-surveilled-cities/
     Google Scholar
  6. Lee G. Cities are becoming ‘smart’, but what does that actually mean? [Internet] 2021 Available from: https://www.investmentmonitor.ai/analysis/smart-cities-covid-cybersecurity.
     Google Scholar
  7. Sorri A. How does surveillance help make a smarter, safer city? [Internet] 2020 Available from: https://www.axis.com/blog/secure-insights/surveillance-smarter-safer-city/
     Google Scholar
  8. Philippines Video Surveillance Market (2020-2026). 6Wresearch. [Internet] 2020 Available from: https://www.6wresearch.com/industry-report/philippines-video-surveillance-market-2020-2026
     Google Scholar
  9. Nair SA. Terrorism in the Philippines in 2020. Institute of Peace and Conflict Studies. 2021.
     Google Scholar
  10. Ornedo JM. Manila’s CCTV cameras now have facial recognition capability. [Internet] 2020 Available from: https://www.gmanetwork.com/news/topstories/metro/728528/manila-s-cctv-cameras-now-have-facial-recognition-capability/story/
     Google Scholar
  11. Sarne VB. Manila City now has a total of 27 cameras for no-contact apprehension. [Internet] 2021 Available from: https://visor.ph/traffic/manila-city-now-has-a-total-of-27-cameras-for-no-contact-apprehension/
     Google Scholar
  12. Cornish DB, Clarke RV. Opportunities, Precipitators, and Criminal Decisions: A Reply to Wortley's Critique of Situational Crime Prevention. Crime Prevention Studies. 2003: 41-96.
     Google Scholar
  13. Welsh BC, Farrington DP. Public Area CCTV and Crime Prevention: An Updated Systematic Review and Meta-Analysis. Justice Quarterly. 2009: 716-745.
     Google Scholar
  14. Piza EL, Welsh BC, Farrington DP, Thomas AL. CCTV Surveillance for Crime Prevention: A 40-Year Systematic Review with Meta-Analysis. Criminology & Public Policy. 2019: 135-159.
     Google Scholar
  15. Ashby MPJ. The Value of CCTV Surveillance Cameras as an Investigative Tool: An Empirical Analysis. European Journal on Criminal Policy and Research. 2017: 441-459.
     Google Scholar
  16. Manalo DM, Mapoy K, Villano KK, Reyes KD, Bautista MA. Status of Closed Circuit Television Camera Usage in Batangas City: Basis for Enhancement. College of Criminology Research Journal. 2015: 1-12.
     Google Scholar
  17. Cuevas QP, Corachea JP, Escabel EB, Bautista MA. Effectiveness of CCTV Cameras Installation College of Criminology Research Journal. 2016: 35-48.
     Google Scholar
  18. Department of Justice. DOJ: Rape charge against Vhong Navarro dismissed. [Internet] 2014 Available from: https://www.officialgazette.gov.ph/2014/04/10/doj-rape-charge-against-vhong-navarro-dismissed/
     Google Scholar
  19. Piza EL, Caplan JM, Kennedy LW. Analyzing the Influence of Micro-Level Factors on CCTV Camera Effect. Journal of Quantitative Criminology. 2014: 237-264.
     Google Scholar
  20. Altahir A, Asirvadam VS, Hamid N, Sebastian P, Saad N, Dass S. Optimizing Camera Placement Based on Task Modeling. 2018.
     Google Scholar
  21. Mavrinac A, Chen X. Modeling Coverage in Camera Networks: A Survey. International Journal of Computer Vision. 2013: 205-226.
     Google Scholar
  22. Hörster E, Lienhart R. On the optimal placement of multiple visual sensors. Proceedings of the 4th ACM International Workshop on Video Surveillance and Sensor Networks. 2006: 111-120.
     Google Scholar
  23. Liu J, Sridharan S, Fookes C. Recent Advances in Camera Planning for Large Area Surveillance: A Comprehensive Review. ACM Computing Surveys. 2017: 1-37.
     Google Scholar
  24. Slavı́k P. A Tight Analysis of the Greedy Algorithm for Set Cover. Journal of Algorithms. 1997: 237-254.
     Google Scholar
  25. Dantzig GB. Linear Programming. Institute for Operations Research and the Management Sciences. 2002: 42-47.
     Google Scholar
  26. Taha HA. Operations Research: An Introduction. Pearson Education. 2017.
     Google Scholar
  27. Lu X-S, Huang H-J, Long J. Camera Location Optimisation for Traffic Surveillance in Urban Road Networks with Multiple User Classes. International Journal of Systems Science. 2012: 1-12.
     Google Scholar
  28. Google Street View. Google. [Internet] Available from: https://goo.gl/maps/dWcExZGth74bb4Ny7
     Google Scholar
  29. Google Street View. Google. [Internet] Available from: https://goo.gl/maps/MRpJpKPgpedseaS49
     Google Scholar
  30. Google Street View. Google. [Internet] Available from: https://goo.gl/maps/YiCxMFi5Bp7f5JPS9
     Google Scholar
  31. Google Street View. Google. [Internet] Available from: https://goo.gl/maps/SVMyFwmBn2EmiDu79
     Google Scholar
  32. Google Street View. Google. [Internet] Available from: https://goo.gl/maps/vZg7BNa6rBo69LFh8
     Google Scholar
  33. Google Street View. Google. [Internet] Available from: https://goo.gl/maps/Y6vkNLH2iyPNA2j2A
     Google Scholar
  34. Google Street View. Google. [Internet] Available from: https://goo.gl/maps/yaAAJuVPgvbAR7BB8
     Google Scholar
  35. Google Street View. Google. [Internet] Available from: https://goo.gl/maps/D9CUqFpR3dhavVot8
     Google Scholar
  36. Google Street View. Google. [Internet] Available from: https://goo.gl/maps/wU47HMoLd9F4AkGA8
     Google Scholar
  37. Google Street View. Google. [Internet] Available from: https://goo.gl/maps/uPxgsSrtNczMJgcq7
     Google Scholar
  38. Google Street View. Google. [Internet] Available from: https://goo.gl/maps/UP6u2eARHGYonRXi8
     Google Scholar
  39. Google Street View. Google. [Internet] Available from: https://goo.gl/maps/41dhbmpiTyXeG4xw5
     Google Scholar
  40. Google Street View. Google. [Internet] Available from: https://goo.gl/maps/LQRZ6MsXUiEG3B9YA
     Google Scholar
  41. Google Street View. Google. [Internet] Available from: https://goo.gl/maps/cn5qeozEPwEdr4XTA
     Google Scholar
  42. Google Street View. Google. [Internet] Available from: https://goo.gl/maps/aanCmcpRP37uZNNV7
     Google Scholar
  43. Google Street View. Google. [Internet] Available from: https://goo.gl/maps/EyAKy5mmxVwrWfYcA
     Google Scholar
  44. Google Street View. Google. [Internet] Available from: https://goo.gl/maps/h89vcvVyzcEzjEaR8
     Google Scholar
  45. Google Street View. Google. [Internet] Available from: https://goo.gl/maps/ibrTzoH4ZXNc9QHb8
     Google Scholar
  46. Google Street View. Google. [Internet] Available from: https://goo.gl/maps/cgchSG2xK7tQLeeg8
     Google Scholar
  47. Manila’s CCTV cameras now have facial recognition capability. [Internet] 2020 Available from: https://www.gmanetwork.com/news/topstories/metro/728528/manila-s-cctv-cameras-now-have-facial-recognition-capability/story/
     Google Scholar


Most read articles by the same author(s)