AI-Driven Data Engineering for Intelligent Transportation Systems

Abstract

The rapid advancement of artificial intelligence (AI) has profoundly impacted various sectors, including transportation. Intelligent Transportation Systems (ITS) are increasingly leveraging AIdriven data engineering to enhance operational efficiency, safety, and user experience. This paper explores the integration of AI with data engineering techniques to optimize ITS. We present a framework for data acquisition, processing, and analysis in real-time transportation environments, emphasizing the role of AI in improving traffic management, predictive maintenance, and autonomous vehicle systems. Through a detailed review of current methodologies and applications, we highlight the benefits and challenges associated with AI-driven data engineering in ITS. Case studies illustrate successful implementations, demonstrating improvements in traffic flow, reduction in accidents, and enhanced route optimization. This paper provides a comprehensive overview of AI technologies and their application to data engineering in ITS, offering insights into future research directions and potential innovations.