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Enhancing Transportation with Intelligent Solutions
Abstract
This paper explores the enhancement of transportation systems through intelligent solutions enabled by AI-driven engineering. Through case studies and research insights, it investigates how artificial intelligence is revolutionizing traditional transportation modes, including road, rail, air, and maritime transport. 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 networks. Additionally, it discusses the integration of AI with autonomous vehicles, traffic management systems, and logistics optimization platforms to enable real-time decision-making, congestion mitigation, and predictive maintenance. The paper also addresses challenges such as regulatory frameworks, ethical considerations, and public acceptance in the adoption of AI-driven engineering solutions in transportation. It emphasizes the importance of collaboration among stakeholders, policy innovation, and investment in infrastructure to harness AI's potential for advancing mobility and connectivity in the transportation sector.
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References
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