Abstract
This article explores the transformative role of AI-powered predictive maintenance and intelligent transit management in optimizing public transportation systems. The article examines how artificial intelligence, machine learning, and IoT sensors are revolutionizing maintenance schedules, reducing system failures, and enhancing operational efficiency across buses, trains, and metro networks. Through comprehensive analysis of metropolitan transit systems worldwide, the article demonstrates significant improvements in service reliability, cost reduction, and passenger experience. The article highlights how AI-driven solutions address critical challenges in urban mobility while presenting a framework for future smart city transportation infrastructure. The article also evaluates implementation challenges, including data integration, system reliability, and security considerations, while exploring emerging technologies that promise to further enhance transit system performance.
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