This chapter explores the intersection of artificial intelligence (AI) and real-time traffic monitoring in the context of smart cities. Focusing on the imperative need for swift, data-driven decisions in urban transportation, the discussion unravels the core components of real-time traffic systems. It scrutinizes the deployment of AI, particularly machine learning algorithms and computer vision, to enhance the speed and precision of traffic analysis. The integration of Internet of Things (IoT) sensors emerges as a linchpin, ensuring comprehensive data collection. The chapter navigates the symbiotic relationship between AI and IoT, emphasizing communication protocols that underpin seamless connectivity. Real-world case studies amplify the exploration, distilling lessons from cities adept at leveraging AI for dynamic traffic surveillance. Challenges and ethical considerations inherent in real-time monitoring are confronted, encompassing technical hurdles and privacy issues. Looking forward, the chapter extrapolates the trajectory of AI and IoT in traffic management, envisioning novel methodologies and technologies on the horizon. In essence, this chapter serves as a compact yet comprehensive guide, unveiling the transformative potential of AI in real-time traffic monitoring for the sustainable evolution of smart cities.