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Internet of Things-Based Physical Security Systems for Smart Cities in Saudi Arabia: A Vision 2030 Framework
Subject area: Science,Engineering and Technology · Area of research: Internet of Things
Abstract
The rapid digitalisation of cities in Saudi Arabia is leading to a greater number of connected cameras, access-control devices, environmental sensors, edge gateways and city platforms being used for the protection of people, buildings and critical infrastructure. While these systems can enhance situational awareness, they also turn physical security into a cyber-physical issue in which compromised identities, networks, analytics or actuators can have real-world effects. This review draws on peer-reviewed evidence published between 2020 and 2025 to look at how Internet of Things technologies can support physical security in Saudi smart cities while remaining resilient, privacy-conscious and operationally governable. Thirty studies verified by DOI were examined using a structured integrative approach that included topics such as smart-city security, IoT architectures, video analytics, intrusion detection, distributed trust, federated learning, digital twins, emergency response and Saudi urban governance. The synthesis highlights five interdependent capability areas: trusted sensing, edge intelligence, resilient connectivity, secure city platforms and coordinated response. It concludes that the technical effectiveness of these systems is more a matter of managing device identity, software provenance, data minimisation, model assurance, interoperability and multi-agency operating procedures than of adding more sensors. A framework aligned with Vision 2030 is suggested, focusing on risk-based zoning, zero-trust device governance, privacy-preserving analytics, resilient edge-cloud orchestration, integrated command workflows and lifecycle assurance. The framework views physical security as an adaptive public-service capability rather than as a set of separate surveillance products. The research priorities are Saudi field trials, climate-resilient sensing, common evaluation benchmarks, measuring privacy impacts and carrying out a longitudinal assessment of human-centred security outcomes.
References
[1] Alqahtany AM. Smart cities as a pathway to sustainable urbanism in the Arab world: A case analysis of Saudi cities. Sustainability. 2025;17:1525. https://doi.org/10.3390/su17041525
[2] Alamoudi AK, Abidoye RB, Lam TYM. Implementing smart sustainable cities in Saudi Arabia: A framework for citizens' participation towards Saudi Vision 2030. Sustainability. 2023;15:6648. https://doi.org/10.3390/su15086648
[3] Alamoudi AK, Abidoye RB, Lam TYM. An evaluation of stakeholders' participation process in developing smart sustainable cities in Saudi Arabia. Smart and Sustainable Built Environment. 2024;13(5):1074–1095. https://doi.org/10.1108/SASBE-08-2022-0170
[4] Mutambik I, Almuqrin A, Alharbi F, Abusharhah M. How to encourage public engagement in smart city development: Learning from Saudi Arabia. Land. 2023;12:1851. https://doi.org/10.3390/land12101851
[5] Laufs J, Borrion H, Bradford B. Security and the smart city: A systematic review. Sustainable Cities and Society. 2020;55:102023. https://doi.org/10.1016/j.scs.2020.102023
[6] Rizi MHP, Seno SAH. A systematic review of technologies and solutions to improve security and privacy protection of citizens in the smart city. Internet of Things. 2022;20:100584. https://doi.org/10.1016/j.iot.2022.100584
[7] Rahman MA, Asyhari AT, Leong LS, Satrya GB, Hai Tao M, Zolkipli MF. Scalable machine learning-based intrusion detection system for IoT-enabled smart cities. Sustainable Cities and Society. 2020;61:102324. https://doi.org/10.1016/j.scs.2020.102324
[8] Ismagilova E, Hughes L, Rana NP, Dwivedi YK. Security, privacy and risks within smart cities: Literature review and development of a smart city interaction framework. Information Systems Frontiers. 2022;24(2):393–414. https://doi.org/10.1007/s10796-020-10044-1
[9] Hernandez-Ramos JL, Martinez JA, Savarino V, Angelini M, et al. Security and privacy in Internet of Things-enabled smart cities: Challenges and future directions. IEEE Security & Privacy. 2021;19(1):12–23. https://doi.org/10.1109/MSEC.2020.3012353
[10] Syed AS, Sierra-Sosa D, Kumar A, Elmaghraby A. IoT in smart cities: A survey of technologies, practices and challenges. Smart Cities. 2021;4(2):429–475. https://doi.org/10.3390/smartcities4020024
[11] Bauer M, Sanchez L, Song J. IoT-enabled smart cities: Evolution and outlook. Sensors. 2021;21:4511. https://doi.org/10.3390/s21134511
[12] AlSalem TS, Almaiah MA, Lutfi A. Cybersecurity risk analysis in the IoT: A systematic review. Electronics. 2023;12:3958. https://doi.org/10.3390/electronics12183958
[13] Altulaihan E, Almaiah MA, Aljughaiman A. Cybersecurity threats, countermeasures and mitigation techniques on the IoT: Future research directions. Electronics. 2022;11:3330. https://doi.org/10.3390/electronics11203330
[14] Paul R, Ghosh N, Sau S, Chakrabarti A, Mohapatra P. Blockchain based secure smart city architecture using low resource IoTs. Computer Networks. 2021;196:108234. https://doi.org/10.1016/j.comnet.2021.108234
[15] Majeed U, Khan LU, Yaqoob I, Kazmi SMA, Salah K, Hong CS. Blockchain for IoT-based smart cities: Recent advances, requirements, and future challenges. Journal of Network and Computer Applications. 2021;181:103007. https://doi.org/10.1016/j.jnca.2021.103007
[16] Ferreira CMS, Garrocho CTB, Oliveira RAR, Silva JS, Cavalcanti CFMDC. IoT registration and authentication in smart city applications with blockchain. Sensors. 2021;21:1323. https://doi.org/10.3390/s21041323
[17] Badidi E, Moumane K, El Ghazi F. Opportunities, applications, and challenges of edge-AI enabled video analytics in smart cities: A systematic review. IEEE Access. 2023;11:80543–80572. https://doi.org/10.1109/ACCESS.2023.3300658
[18] Zahra A, Ghafoor M, Munir K, Ullah A, Abideen ZU. Application of region-based video surveillance in smart cities using deep learning. Multimedia Tools and Applications. 2024;83:15313–15338. https://doi.org/10.1007/s11042-021-11468-w
[19] Wolf K, Dawson R, Mills J, et al. Towards a digital twin for supporting multi-agency incident management in a smart city. Scientific Reports. 2022;12:16221. https://doi.org/10.1038/s41598-022-20178-8
[20] Shorfuzzaman M, Hossain MS, Alhamid MF. Towards the sustainable development of smart cities through mass video surveillance: A response to the COVID-19 pandemic. Sustainable Cities and Society. 2021;64:102582. https://doi.org/10.1016/j.scs.2020.102582
[21] Al-Huthaifi R, Li T, Huang W, Gu J, Li C. Federated learning in smart cities: Privacy and security survey. Information Sciences. 2023;632:833–857. https://doi.org/10.1016/j.ins.2023.03.033
[22] Pandya S, Srivastava G, Jhaveri R, et al. Federated learning for smart cities: A comprehensive survey. Sustainable Energy Technologies and Assessments. 2023;55:102987. https://doi.org/10.1016/j.seta.2022.102987
[23] Ghadi YY, Mazhar T, Shah SFA, et al. Integration of federated learning with IoT for smart cities applications, challenges, and solutions. PeerJ Computer Science. 2023;9:e1657. https://doi.org/10.7717/peerj-cs.1657
[24] Hijazi NM, Aloqaily M, Guizani M, Ouni B, Karray F. Secure federated learning with fully homomorphic encryption for IoT communications. IEEE Internet of Things Journal. 2024;11(3):4289–4300. https://doi.org/10.1109/JIOT.2023.3302065
[25] De Coninck S, Wang WC, Leroux S, Simoens P. Privacy-preserving visual analysis: training video obfuscation models without sensitive labels. Applied Intelligence. 2024;54:6041–6052. https://doi.org/10.1007/s10489-024-05489-9
[26] Sarker IH. Smart city data science: Towards data-driven smart cities with open research issues. Internet of Things. 2022;19:100528. https://doi.org/10.1016/j.iot.2022.100528
[27] Capodieci N, Cavicchioli R, Muzzini F, Montagna L. Improving emergency response in the era of ADAS vehicles in the smart city. ICT Express. 2021;7(4):481–486. https://doi.org/10.1016/j.icte.2021.03.005
[28] Yaacoub JPA, Noura HN, Salman O. Security of federated learning with IoT systems: Issues, limitations, challenges, and solutions. Internet of Things and Cyber-Physical Systems. 2023;3:155–179. https://doi.org/10.1016/j.iotcps.2023.04.001
[29] Gugueoth V, Safavat S, Shetty S. Security of Internet of Things (IoT) using federated learning and deep learning-recent advancements, issues and prospects. ICT Express. 2023;9(5):941–960. https://doi.org/10.1016/j.icte.2023.03.006
[30] Omrany H, Al-Obaidi KM, Hossain M, Alduais NAM, Al-Duais HS, Ghaffarianhoseini A. IoT-enabled smart cities: a hybrid systematic analysis of key research areas, challenges, and recommendations for future direction. Discover Cities. 2024;1:2. https://doi.org/10.1007/s44327-024-00002-w
How to cite this paper
@article{1723952,
author = {Abdulrahman Alshaikhali},
title = {Internet of Things-Based Physical Security Systems for Smart Cities in Saudi Arabia: A Vision 2030 Framework},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {4},
pages = {1671-1685},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1723952.pdf},
abstract = {The rapid digitalisation of cities in Saudi Arabia is leading to a greater number of connected cameras, access-control devices, environmental sensors, edge gateways and city platforms being used for the protection of people, buildings and critical infrastructure. While these systems can enhance situational awareness, they also turn physical security into a cyber-physical issue in which compromised identities, networks, analytics or actuators can have real-world effects. This review draws on peer-reviewed evidence published between 2020 and 2025 to look at how Internet of Things technologies can support physical security in Saudi smart cities while remaining resilient, privacy-conscious and operationally governable. Thirty studies verified by DOI were examined using a structured integrative approach that included topics such as smart-city security, IoT architectures, video analytics, intrusion detection, distributed trust, federated learning, digital twins, emergency response and Saudi urban governance. The synthesis highlights five interdependent capability areas: trusted sensing, edge intelligence, resilient connectivity, secure city platforms and coordinated response. It concludes that the technical effectiveness of these systems is more a matter of managing device identity, software provenance, data minimisation, model assurance, interoperability and multi-agency operating procedures than of adding more sensors. A framework aligned with Vision 2030 is suggested, focusing on risk-based zoning, zero-trust device governance, privacy-preserving analytics, resilient edge-cloud orchestration, integrated command workflows and lifecycle assurance. The framework views physical security as an adaptive public-service capability rather than as a set of separate surveillance products. The research priorities are Saudi field trials, climate-resilient sensing, common evaluation benchmarks, measuring privacy impacts and carrying out a longitudinal assessment of human-centred security outcomes.},
month = {October},
}