Derleme
BibTex RIS Kaynak Göster

Akıllı şehirlerde önleyici güvenlik: Sensör ağları ve CCTV’nin etkinliği üzerine nitel bir değerlendirme

Yıl 2025, Sayı: 50, 469 - 496, 07.01.2026
https://doi.org/10.31198/idealkent.1766696

Öz

Bu çalışma, akıllı şehir teknolojilerinin suç önleme ve soruşturma süreçlerindeki rolünü kriminolojik ve kriminalistik perspektiflerden ele almaktadır. Yoğun kentleşmenin doğurduğu güvenlik sorunlarına yanıt olarak geliştirilen akıllı şehir altyapıları, sensör sistemleri, kapalı devre televizyon (CCTV), nesnelerin interneti (IoT), plaka tanıma sistemleri ve yapay zekâ destekli gözetim araçları aracılığıyla suçla mücadelede yeni imkânlar sunmaktadır. Kriminolojik açıdan, bu teknolojiler durumsal suç önleme, rutin faaliyetler kuramı ve suç sıcak noktaları yaklaşımları çerçevesinde değerlendirilmektedir. Teknolojinin sunduğu veri analitiği ve erken uyarı sistemleri, devriye planlamasında öngörücü polislik anlayışını desteklemekte, suçun mekânsal dağılımına ilişkin stratejik müdahale fırsatları yaratmaktadır. Kriminalistik düzlemde ise, dijital delil niteliğindeki görüntü ve sensör verilerinin zaman-mekân doğrulaması, delil zinciri güvenliği ve adli bilişim yöntemleri ile adli süreçlerde kullanımı analiz edilmektedir. Ayrıca bu çalışmada teknolojilerin teknik, etik ve hukuki sınırlarına da dikkat çekilmektedir. Mahremiyet ihlalleri, algoritmik önyargılar, toplumsal eşitsizliklerin pekişmesi ve delil geçerliliğine dair sorunlar, akıllı güvenlik sistemlerinin meşruiyetini ve etkinliğini tartışmalı hale getirmektedir. Sonuç olarak, akıllı şehir güvenliğinin teknolojik, şeffaf, adil ve katılımcı yönetişim anlayışıyla şekillendirilmesi gerekliliği vurgulanmaktadır.

Kaynakça

  • Ali, W. B. (2016). Big data-driven smart policing: Big data-based patrol car dispatching. Journal of Geotechnical and Transportation Engineering, 1(2), 1–18. https://jgtte.com/issues/2/Issue%202%20-%204.pdf
  • Alotibi, G. (2024). A high abstract digital forensic readiness metamodel for securing smart cities. IEEE Access, 12, 187427–187443. https://doi.org/10.1109/ACCESS.2024.3483173
  • Ardabili, B. R., Pazho, A. D., Noghre, G. A., Katariya, V., Hull, G., Reid, S., & Tabkhi, H. (2024). Exploring public's perception of safety and video surveillance technology: A survey approach. Technology in Society, 78, 102641. https://doi.org/10.1016/j.techsoc.2024.102641
  • Baranwal, A. (2025). IoT-based environmental sensing solutions for smart city monitoring. Smart City Insights, 2(1), 1–16. https://doi.org/10.22105/sci.v2i1.28
  • Bokhari, S. A. A., & SeungHwan, M. (2024). Smart city governance, stakeholder’s satisfaction, and crime prevention: Moderating impact of institutional and technological innovation. Authorea Preprints.
  • Chandana, R. K., & Ramachandra, A. C. (2022). Real-time object detection system with YOLO and CNN models: A review (arXiv:2208.00773). arXiv. https://arxiv.org/abs/2208.00773
  • Choi, H. S., & Song, S. K. (2022). Direction for a transition toward smart sustainable cities based on the diagnosis of smart city plans. Smart Cities, 6(1), 156–178. https://doi.org/10.3390/smartcities6010009
  • Clarke, R. V. G. (1992). Situational crime prevention: Successful case studies.
  • Cohen, L. E., & Felson, M. (1979). Social change and crime rate trends: A routine activity approach. American Sociological Review, 44(4), 588–608. https://doi.org/10.2307/2094589
  • Daraghmi, Y. A., & Shawahna, I. (2023). Digital forensic analysis of vehicular video sensors: Dashcams as a case. Sensors, 23(17), 7548. https://doi.org/10.3390/s23177548
  • Demirbaş, M. (2023). Türkiye'de suç korkusunun analizi: Türkiye Cumhuriyeti vatandaşları ve Suriyeliler arasında suç korkusu. Ankara: Adalet Yayınevi.
  • Demirbaş, M., Kavsıracı, O., Çelik, A., Akıncıoğlu, N. U., & Peker, H. S. (2025). Fear of crime in traffic: An analysis of gender-based perceptual differences in the case of İzmir. OPUS Journal of Society Research, 22(5), 1133–1145. https://doi.org/10.26466/opusjsr.1741867
  • Demirhan, D. Ç. (2024). Türkiye’nin akıllı şehir dönüşüm stratejisi: Kapsayıcı politikalar bağlamında bir analiz. Yönetim Bilimleri Dergisi, 22(Özel Sayı: Endüstri 4.0 ve Dijitalleşmenin Sosyal Bilimlerde Yansımaları), 1499–1522. https://doi.org/10.35408/comuybd.1516495
  • Ditton, J. (2000). Public attitudes towards open-street CCTV in Glasgow. British Journal of Criminology, 40(4), 692–709. https://doi.org/10.1093/bjc/40.4.692
  • Dubravova, H., Bures, V., & Velf, L. (2024). Drones as an example of the use of smart technologies in cooperation with the state security forces in the context of the smart cities concept in the Czech Republic. Procedia Computer Science, 237, 229–236. https://doi.org/10.1016/j.procs.2024.05.100
  • Ensign, D., Friedler, S. A., Neville, S., Scheidegger, C., & Venkatasubramanian, S. (2018). Runaway feedback loops in predictive policing. In S. A. Friedler & C. Wilson (Eds.), Proceedings of the 1st Conference on Fairness, Accountability and Transparency (pp. 160–171). Proceedings of Machine Learning Research, 81. PMLR. https://proceedings.mlr.press/v81/ensign18a.html
  • Forrester, L., & Ruiz, C. (2024). Classical theories of criminology: Deterrence. In Introduction to Criminology and Criminal Justice.
  • Igonor, O. S., Amin, M. B., & Garg, S. (2025). The application of blockchain technology in the field of digital forensics: A literature review. Blockchains, 3(1), 5. https://doi.org/10.3390/blockchains3010005
  • Jiang, Y., Li, H., Feng, B., Wu, Z., Zhao, S., & Wang, Z. (2022). Street patrol routing optimization in smart city management based on genetic algorithm: A case in Zhengzhou, China. ISPRS International Journal of Geo-Information, 11(3), 171. https://doi.org/10.3390/ijgi11030171
  • Jonasova, E. (2024). Smart city opportunities and risks for law enforcement. Public Security and Public Order, 35, 164–170. https://doi.org/10.13165/PSPO-24-35-12
  • Khanna, P., & Khanra, S. (2023). Citizen empowerment through smart surveillance: Evidence from Indian smart cities. Digital Policy, Regulation and Governance, 25(4), 385–401. https://doi.org/10.1108/DPRG-11-2022-0141
  • Kounadi, O., Ristea, A., Araujo Jr., A., & Leitner, M. (2020). A systematic review on spatial crime forecasting. Crime Science, 9(1), 7. https://doi.org/10.1186/s40163-020-00116-7
  • Lillis, D., Becker, B., O’Sullivan, T., & Scanlon, M. (2016). Current challenges and future research areas for digital forensic investigation (arXiv:1604.03850). arXiv. https://arxiv.org/abs/1604.03850
  • Lim, H., Kim, C., Eck, J. E., & Kim, J. (2016). The crime-reduction effects of open-street CCTV in South Korea. Security Journal, 29(2), 241–255. https://doi.org/10.1057/sj.2013.10
  • Lucien, L. R. (2024). Challenges of trustworthy digital evidence and its chain of custody on cloud computing environment: A systematic review. In Proceedings of the 26th International Conference on Enterprise Information Systems (ICEIS 2024) (pp. 240–246). SCITEPRESS – Science and Technology Publications. https://doi.org/10.5220/0012702800003690
  • Marsap, G. (2023). Afet yönetimi ve kentlerde afetler açısından geliştirilen gelecek odaklı dinamik yönetim anlayışları. JENAS Journal of Environmental and Natural Studies, 5(3), 237–251. https://doi.org/10.53472/jenas.1389621
  • Miller, C. M. (2022). A survey of prosecutors and investigators using digital evidence: A starting point. Forensic Science International: Synergy, 6, 100296. https://doi.org/10.1016/j.fsisyn.2022.100296
  • Piza, E. L., Caplan, J. M., & Kennedy, L. W. (2014). Analyzing the influence of micro-level factors on CCTV camera effect. Journal of Quantitative Criminology, 30(2), 237–264. https://doi.org/10.1007/s10940-013-9202-5
  • Piza, E. L., Welsh, B. C., Farrington, D. P., & Thomas, A. L. (2019). CCTV surveillance for crime prevention: A 40-year systematic review with meta-analysis. Criminology & Public Policy, 18(1), 135–159. https://doi.org/10.1111/1745-9133.12419
  • Reynald, D. M. (2016). Guarding against crime: Measuring guardianship within routine activity theory. Routledge
  • Roka, S., Diwakar, M., Singh, P., & Singh, P. (2023). Anomaly behavior detection analysis in video surveillance: A critical review. Journal of Electronic Imaging, 32(4), 042106. https://doi.org/10.1117/1.JEI.32.4.042106
  • Sherman, L. W., Gartin, P. R., & Buerger, M. E. (1989). Hot spots of predatory crime: Routine activities and the criminology of place. Criminology, 27(1), 27–56. https://doi.org/10.1111/j.1745-9125.1989.tb00862.x
  • Villa, C., & Jacobsen, C. (2020). The application of photogrammetry for forensic 3D recording of crime scenes, evidence and people. In G. N. Rutty (Ed.), Essentials of autopsy practice: Reviews, updates and advances (8th ed., pp. 1–18). Springer. https://doi.org/10.1007/978-3-030-24330-2_1
  • Xu, R., Razavi, S., & Zheng, R. (2023). Edge video analytics: A survey on applications, systems and enabling techniques. IEEE Communications Surveys & Tutorials, 25(4), 2951–2982. https://doi.org/10.1109/COMST.2023.3323091
  • Zhang, K., Ni, J., Yang, K., Liang, X., Ren, J., & Shen, X. S. (2017). Security and privacy in smart city applications: Challenges and solutions. IEEE Communications Magazine, 55(1), 122–129. https://doi.org/10.1109/MCOM.2017.1600267CM
  • Zhang, S., Qin, X., Zhen, F., Huang, Y., & Kong, Y. (2023). Do surveillance cameras improve perceived neighborhood safety? A case study of Nanjing, China. Cities, 140, 104423. https://doi.org/10.1016/j.cities.2023.104423

Preventive security in smart cities: Effectiveness of sensor networks and CCTV

Yıl 2025, Sayı: 50, 469 - 496, 07.01.2026
https://doi.org/10.31198/idealkent.1766696

Öz

This study examines the role of smart city technologies in crime prevention and investigation from both criminological and criminalistic perspectives. In response to security challenges associated with rapid urbanization, smart city infrastructures—such as sensor systems, Closed-Circuit Television (CCTV), the Internet of Things (IoT), license plate recognition systems, and AI-powered surveillance tools—offer new opportunities for crime control. From a criminological perspective, these technologies are evaluated within the frameworks of situational crime prevention, routine activity theory, and crime hotspot analysis. Their analytical capacities and early warning mechanisms support predictive policing practices and enable targeted, spatially informed interventions. From a criminalistic standpoint, the study addresses the evidentiary value of digital data, including visual and sensor-based outputs, focusing on issues of spatiotemporal verification, chain of custody integrity, and the application of digital forensic techniques in judicial proceedings. At the same time, the study highlights key technical, ethical, and legal challenges, including privacy concerns, algorithmic bias, the reproduction of social inequalities, and problems related to the admissibility of digital evidence. Overall, the findings underscore that urban security in smart cities should be understood not merely as a technological innovation, but as a complex socio-political domain requiring transparent, just, and participatory governance models.

Kaynakça

  • Ali, W. B. (2016). Big data-driven smart policing: Big data-based patrol car dispatching. Journal of Geotechnical and Transportation Engineering, 1(2), 1–18. https://jgtte.com/issues/2/Issue%202%20-%204.pdf
  • Alotibi, G. (2024). A high abstract digital forensic readiness metamodel for securing smart cities. IEEE Access, 12, 187427–187443. https://doi.org/10.1109/ACCESS.2024.3483173
  • Ardabili, B. R., Pazho, A. D., Noghre, G. A., Katariya, V., Hull, G., Reid, S., & Tabkhi, H. (2024). Exploring public's perception of safety and video surveillance technology: A survey approach. Technology in Society, 78, 102641. https://doi.org/10.1016/j.techsoc.2024.102641
  • Baranwal, A. (2025). IoT-based environmental sensing solutions for smart city monitoring. Smart City Insights, 2(1), 1–16. https://doi.org/10.22105/sci.v2i1.28
  • Bokhari, S. A. A., & SeungHwan, M. (2024). Smart city governance, stakeholder’s satisfaction, and crime prevention: Moderating impact of institutional and technological innovation. Authorea Preprints.
  • Chandana, R. K., & Ramachandra, A. C. (2022). Real-time object detection system with YOLO and CNN models: A review (arXiv:2208.00773). arXiv. https://arxiv.org/abs/2208.00773
  • Choi, H. S., & Song, S. K. (2022). Direction for a transition toward smart sustainable cities based on the diagnosis of smart city plans. Smart Cities, 6(1), 156–178. https://doi.org/10.3390/smartcities6010009
  • Clarke, R. V. G. (1992). Situational crime prevention: Successful case studies.
  • Cohen, L. E., & Felson, M. (1979). Social change and crime rate trends: A routine activity approach. American Sociological Review, 44(4), 588–608. https://doi.org/10.2307/2094589
  • Daraghmi, Y. A., & Shawahna, I. (2023). Digital forensic analysis of vehicular video sensors: Dashcams as a case. Sensors, 23(17), 7548. https://doi.org/10.3390/s23177548
  • Demirbaş, M. (2023). Türkiye'de suç korkusunun analizi: Türkiye Cumhuriyeti vatandaşları ve Suriyeliler arasında suç korkusu. Ankara: Adalet Yayınevi.
  • Demirbaş, M., Kavsıracı, O., Çelik, A., Akıncıoğlu, N. U., & Peker, H. S. (2025). Fear of crime in traffic: An analysis of gender-based perceptual differences in the case of İzmir. OPUS Journal of Society Research, 22(5), 1133–1145. https://doi.org/10.26466/opusjsr.1741867
  • Demirhan, D. Ç. (2024). Türkiye’nin akıllı şehir dönüşüm stratejisi: Kapsayıcı politikalar bağlamında bir analiz. Yönetim Bilimleri Dergisi, 22(Özel Sayı: Endüstri 4.0 ve Dijitalleşmenin Sosyal Bilimlerde Yansımaları), 1499–1522. https://doi.org/10.35408/comuybd.1516495
  • Ditton, J. (2000). Public attitudes towards open-street CCTV in Glasgow. British Journal of Criminology, 40(4), 692–709. https://doi.org/10.1093/bjc/40.4.692
  • Dubravova, H., Bures, V., & Velf, L. (2024). Drones as an example of the use of smart technologies in cooperation with the state security forces in the context of the smart cities concept in the Czech Republic. Procedia Computer Science, 237, 229–236. https://doi.org/10.1016/j.procs.2024.05.100
  • Ensign, D., Friedler, S. A., Neville, S., Scheidegger, C., & Venkatasubramanian, S. (2018). Runaway feedback loops in predictive policing. In S. A. Friedler & C. Wilson (Eds.), Proceedings of the 1st Conference on Fairness, Accountability and Transparency (pp. 160–171). Proceedings of Machine Learning Research, 81. PMLR. https://proceedings.mlr.press/v81/ensign18a.html
  • Forrester, L., & Ruiz, C. (2024). Classical theories of criminology: Deterrence. In Introduction to Criminology and Criminal Justice.
  • Igonor, O. S., Amin, M. B., & Garg, S. (2025). The application of blockchain technology in the field of digital forensics: A literature review. Blockchains, 3(1), 5. https://doi.org/10.3390/blockchains3010005
  • Jiang, Y., Li, H., Feng, B., Wu, Z., Zhao, S., & Wang, Z. (2022). Street patrol routing optimization in smart city management based on genetic algorithm: A case in Zhengzhou, China. ISPRS International Journal of Geo-Information, 11(3), 171. https://doi.org/10.3390/ijgi11030171
  • Jonasova, E. (2024). Smart city opportunities and risks for law enforcement. Public Security and Public Order, 35, 164–170. https://doi.org/10.13165/PSPO-24-35-12
  • Khanna, P., & Khanra, S. (2023). Citizen empowerment through smart surveillance: Evidence from Indian smart cities. Digital Policy, Regulation and Governance, 25(4), 385–401. https://doi.org/10.1108/DPRG-11-2022-0141
  • Kounadi, O., Ristea, A., Araujo Jr., A., & Leitner, M. (2020). A systematic review on spatial crime forecasting. Crime Science, 9(1), 7. https://doi.org/10.1186/s40163-020-00116-7
  • Lillis, D., Becker, B., O’Sullivan, T., & Scanlon, M. (2016). Current challenges and future research areas for digital forensic investigation (arXiv:1604.03850). arXiv. https://arxiv.org/abs/1604.03850
  • Lim, H., Kim, C., Eck, J. E., & Kim, J. (2016). The crime-reduction effects of open-street CCTV in South Korea. Security Journal, 29(2), 241–255. https://doi.org/10.1057/sj.2013.10
  • Lucien, L. R. (2024). Challenges of trustworthy digital evidence and its chain of custody on cloud computing environment: A systematic review. In Proceedings of the 26th International Conference on Enterprise Information Systems (ICEIS 2024) (pp. 240–246). SCITEPRESS – Science and Technology Publications. https://doi.org/10.5220/0012702800003690
  • Marsap, G. (2023). Afet yönetimi ve kentlerde afetler açısından geliştirilen gelecek odaklı dinamik yönetim anlayışları. JENAS Journal of Environmental and Natural Studies, 5(3), 237–251. https://doi.org/10.53472/jenas.1389621
  • Miller, C. M. (2022). A survey of prosecutors and investigators using digital evidence: A starting point. Forensic Science International: Synergy, 6, 100296. https://doi.org/10.1016/j.fsisyn.2022.100296
  • Piza, E. L., Caplan, J. M., & Kennedy, L. W. (2014). Analyzing the influence of micro-level factors on CCTV camera effect. Journal of Quantitative Criminology, 30(2), 237–264. https://doi.org/10.1007/s10940-013-9202-5
  • Piza, E. L., Welsh, B. C., Farrington, D. P., & Thomas, A. L. (2019). CCTV surveillance for crime prevention: A 40-year systematic review with meta-analysis. Criminology & Public Policy, 18(1), 135–159. https://doi.org/10.1111/1745-9133.12419
  • Reynald, D. M. (2016). Guarding against crime: Measuring guardianship within routine activity theory. Routledge
  • Roka, S., Diwakar, M., Singh, P., & Singh, P. (2023). Anomaly behavior detection analysis in video surveillance: A critical review. Journal of Electronic Imaging, 32(4), 042106. https://doi.org/10.1117/1.JEI.32.4.042106
  • Sherman, L. W., Gartin, P. R., & Buerger, M. E. (1989). Hot spots of predatory crime: Routine activities and the criminology of place. Criminology, 27(1), 27–56. https://doi.org/10.1111/j.1745-9125.1989.tb00862.x
  • Villa, C., & Jacobsen, C. (2020). The application of photogrammetry for forensic 3D recording of crime scenes, evidence and people. In G. N. Rutty (Ed.), Essentials of autopsy practice: Reviews, updates and advances (8th ed., pp. 1–18). Springer. https://doi.org/10.1007/978-3-030-24330-2_1
  • Xu, R., Razavi, S., & Zheng, R. (2023). Edge video analytics: A survey on applications, systems and enabling techniques. IEEE Communications Surveys & Tutorials, 25(4), 2951–2982. https://doi.org/10.1109/COMST.2023.3323091
  • Zhang, K., Ni, J., Yang, K., Liang, X., Ren, J., & Shen, X. S. (2017). Security and privacy in smart city applications: Challenges and solutions. IEEE Communications Magazine, 55(1), 122–129. https://doi.org/10.1109/MCOM.2017.1600267CM
  • Zhang, S., Qin, X., Zhen, F., Huang, Y., & Kong, Y. (2023). Do surveillance cameras improve perceived neighborhood safety? A case study of Nanjing, China. Cities, 140, 104423. https://doi.org/10.1016/j.cities.2023.104423
Toplam 36 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Kent Sosyolojisi ve Toplum Çalışmaları
Bölüm Derleme
Yazarlar

Niyazi Umut Akıncıoğlu 0000-0002-4605-6195

Gönderilme Tarihi 16 Ağustos 2025
Kabul Tarihi 31 Aralık 2025
Yayımlanma Tarihi 7 Ocak 2026
Yayımlandığı Sayı Yıl 2025 Sayı: 50

Kaynak Göster

APA Akıncıoğlu, N. U. (2026). Akıllı şehirlerde önleyici güvenlik: Sensör ağları ve CCTV’nin etkinliği üzerine nitel bir değerlendirme. İDEALKENT(50), 469-496. https://doi.org/10.31198/idealkent.1766696