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Advancing Transportation with Intelligent Solutions
Abstract
This paper explores the advancement of transportation through intelligent solutions enabled by AI-driven engineering. Through case studies and research insights, it investigates how artificial intelligence is revolutionizing traditional transportation practices, including traffic management, vehicle autonomy, and infrastructure optimization. The study highlights the application of AI techniques such as machine learning, computer vision, and natural language processing in improving safety, efficiency, and sustainability in transportation systems. Additionally, it discusses the integration of AI with smart sensors, connected vehicles, and urban mobility platforms to enable real-time traffic prediction, autonomous navigation, and multimodal transportation services. The paper also addresses challenges such as data privacy, cybersecurity, and regulatory compliance in the adoption of AI-driven engineering solutions in transportation. It emphasizes the importance of collaboration, interoperability, and user acceptance in leveraging AI's potential to advance transportation innovation and create smarter, more accessible cities.
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