Khalid Haseeb1, Imran Qureshi2,*, Naveed Abbas1, Muhammad Ali3, Muhammad Arif Shah4, Qaisar Abbas2
CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 4349-4362, 2025, DOI:10.32604/cmes.2025.072326
- 23 December 2025
Abstract The rapid evolution of smart cities has led to the deployment of Cyber-Physical IoT Systems (CPS-IoT) for real-time monitoring, intelligent decision-making, and efficient resource management, particularly in intelligent transportation and vehicular networks. Edge intelligence plays a crucial role in these systems by enabling low-latency processing and localized optimization for dynamic, data-intensive, and vehicular environments. However, challenges such as high computational overhead, uneven load distribution, and inefficient utilization of communication resources significantly hinder scalability and responsiveness. Our research presents a robust framework that integrates artificial intelligence and edge-level traffic prediction for CPS-IoT systems. Distributed computing for More >