Smart City Gnosys
Smart city article details
| Title | Proactive And Data-Centric Internet Of Things-Based Fog Computing Architecture For Effective Policing In Smart Cities |
|---|---|
| ID_Doc | 43228 |
| Authors | Butt A.U.R.; Saba T.; Khan I.; Mahmood T.; Khan A.R.; Singh S.K.; Daradkeh Y.I.; Ullah I. |
| Year | 2025 |
| Published | Computers and Electrical Engineering, 123 |
| DOI | http://dx.doi.org/10.1016/j.compeleceng.2024.110030 |
| Abstract | Smart surveillance is crucial for improving citizen security and ensuring a sustainable environment for routine tasks, particularly within intelligent transportation systems (ITS). However, it can be costly and burden taxpayers. The lack of public interaction makes it difficult for police to arrest and conduct investigations. Additionally, incidents increase due to similar patterns, making smart surveillance essential for reporting and addressing these issues. Smart devices such as sensors or actuators installed on the roads and within vehicles are critical components of any smart surveillance and ITS framework. This integration enhances system agility and facilitates proactive rather than reactive responses. It empowers security agencies to plan more effectively and respond swiftly during emergencies. The incorporation of cloud computing capabilities transforms traditional surveillance and ITS operations. Employing the Internet of Things (IoT) with edge or cloud computing extensions, such as fog computing, modernizes the management of security gadgets for Field Forces. This study investigates a smart surveillance fog-enabled approach to reduce response times for aiding agencies within ITS. By optimizing individual journeys through an RFID-based passing system, incidents are reported promptly to the nearest field force, enhancing overall ITS efficiency. The proactive approach improves resource consumption (energy, CPU, and network usage) compared to traditional reactive methods. The fog-enabled experiments demonstrated a CPU efficiency of approximately 95.76%, significantly outperforming the Cloud-only deployment, achieving a maximum average efficiency of 92.12%. Experimental evaluations in a simulation environment demonstrate that the proposed method significantly outperforms conventional approaches, marking a substantial advancement in IoT-aided ITS. © 2025 Elsevier Ltd |
| Author Keywords | Effective policing; Fog computing; Intelligent transportation system; Internet of Things; Smart cities; Smart surveillance |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
50520  | 0.901 | Chen N.; Chen Y.; Ye X.; Ling H.; Song S.; Huang C.-T. | Smart City Surveillance In Fog Computing | Studies in Big Data, 22 (2017) |
| 9783 | 0.894 | Yang J.-P. | Application Of An Integrated Fog-Iot Framework To A Smart Traffic Surveillance Management System | Journal of Scientific and Industrial Research, 84, 5 (2025) |
| 23904 | 0.885 | Shreedevi K.S.; Chayadevi M.L.; Rajashree S.; Geetha S.; Kusuma P. | Enhancing Public Safety: Surveillance Solutions For Urban Environments | 2nd IEEE International Conference on Advances in Information Technology, ICAIT 2024 - Proceedings (2024) |
| 5708 | 0.883 | Vikas Rai J.; Ashwini K.M. | A Unified Fog Computing Architecture For Next-Generation Smart City Traffic And Crime Management | 2025 International Conference on Artificial Intelligence and Data Engineering, AIDE 2025 - Proceedings (2025) |
| 21854 | 0.883 | Fares S.; Ghoniem N.; Hesham M.; Hesham S.; Hesham N.E.; Shaheen L.; Halim I.T.A. | Edge/Fog-Based Architecture Design For Intelligent Surveillance Systems In Smart Cities: A Software Perspective | 2021 International Mobile, Intelligent, and Ubiquitous Computing Conference, MIUCC 2021 (2021) |
| 46593 | 0.878 | Mehta S.; Singh M. | Revolutionizing Traffic Law Enforcement: Iot-Enabled Vehicle Control Systems For Smart Cities | 2024 IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies, INSPECT 2024 (2024) |
| 39239 | 0.873 | Ribeiro T.; Oliveira P.; Rodrigues M. | Next-Generation Surveillance: Exploring The Intersection Of Artificial Intelligence And Security | Lecture Notes in Networks and Systems, 1066 LNNS (2024) |
| 35128 | 0.872 | Naik F.; Chaudhary S.; Biswas H.; Mishra S.; Alkhayyat A. | Leveraging Smart Computing For Effective Crime Spot Alert System | International Conference on Intelligent and Innovative Practices in Engineering and Management 2024, IIPEM 2024 (2024) |
| 55101 | 0.87 | Peter D.; Alavi A.H.; Javadi B.; Fernandes S.L. | The Cognitive Approach In Cloud Computing And Internet Of Things Technologies For Surveillance Tracking Systems | The Cognitive Approach in Cloud Computing and Internet of Things Technologies for Surveillance Tracking Systems (2020) |
| 33069 | 0.87 | Rahmani M.K.I.; Khan F.; Muzaffar A.W.; Jan M.A. | Internet Of Things-Enabled Optimal Data Aggregation Approach For The Intelligent Surveillance Systems | Mobile Information Systems, 2022 (2022) |