PUBLISHED PAPERS #09.2
| Zahra Seyidgizi, Shahriyar Guliyev. Artificial Intelligence and Smart Roads: The Renewed Silk Road |
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| Abstract. The Silk Road project is aimed at economic prosper- ity and achieving success in an entirely different facets of trading for the participating states. In land by railway and highways, and in sea by ports, the world will connect in a single trade space. The management of this system will be implemented harnessing AI, which is the profit of the new technological age. For building contemporary transportation IS, the most cutting-edge approach is data-driven paradigm leveraging ANNs. Concerning system security, inference servers are deployed on-premise as opposed to cloud-based solutions. The architectural framework relies on multiphase ML methodologies, encompassing Faster R-CNN CV models for analysis of on-road imagery data, Transformer Foundational Models of NLP, LLMs, GenAI are employed to enhance driver awareness, regarding aspects as traffic and mete- orological conditions, monitoring driver/vehicle safety operations. DRL techniques, exemplified by Deep Q-Networks, alongside the incorporation of hybrid models are utilized optimizing traffic load. To adhere to best practices, the adoption of a RAG employing Vector Databases enables real-time actuation of data within ANN models. The entire system is powered by monocrystalline cell solar- powered green technology, emphasizing sustainability. AI-enabled emergency control mechanisms are integrated for long-distance traveling vehicles, ensuring the implementation of enhanced safety mechanisms. |
| Keywords: Smart Roads, The Renewed Silk Way, Trading Facets, Foundational Models, DRL, Deep Q-Networks, GenAI, LLM, Faster R-CNN, RAG, Vector Database, Economic Prosperity, Land Transportation, Sea Ports, Data-driven Decision-Making, Information System Security, Traffic Optimization, Emergency Control Mechanisms |
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