Integration of AI and IoT for Smart and Secure Mobility

Abstract

The convergence of Artificial Intelligence (AI) and the Internet of Things (IoT) presents transformative opportunities for enhancing mobility in urban environments. Smart and secure mobility systems enable real-time traffic optimization, predictive maintenance, passenger safety monitoring, and robust cybersecurity frameworks. This paper proposes an integrated AI-IoT framework tailored for urban transport, focusing on safety, efficiency, and security. Through simulated deployments and case studies, we analyze the architecture, implementation strategies, and performance of the system, highlighting improvements in traffic flow efficiency (up to 28%), predictive fault detection (87% accuracy), and enhanced security measures. Figures and tables illustrate the system architecture, IoT sensor network, AI-driven analytics pipeline, and comparative results against baseline methods. The paper concludes with guidelines for scalable deployment, privacy-preserving data strategies, and future research directions in secure urban mobility.