Core Insights - The East China Air Traffic Management Bureau has successfully launched an intelligent system for air traffic control, marking a significant step in the transformation and upgrade of air traffic control services [1][5] - The intelligent system integrates professional knowledge and business processes in air traffic control, enabling intelligent data analysis, fault simulation, and operational decision support [1][2] Group 1: System Features - The intelligent system is built on advanced large language models and reasoning technologies, allowing it to deeply understand air traffic control knowledge and processes, thereby enhancing operational efficiency [2][5] - It serves as a "multi-faceted expert," breaking down information barriers and converting complex business processes into efficient digital solutions [2][5] Group 2: Application Scenarios - Four major intelligent application scenarios have been customized to enhance operational efficiency, including a qualification inspection application that significantly improves employee learning efficiency by reducing information retrieval time from over 10 minutes to around 1 minute, achieving a 90% efficiency increase [3] - Other applications include automated log analysis for quick historical record retrieval, a rapid Q&A function for technical documents, and an emergency troubleshooting assistant that provides decision-making references based on historical fault cases [3] Group 3: Technical Infrastructure - The system development utilized the Dify platform, which supports low-code development and allows for flexible integration of various models, significantly simplifying the AI application construction process [4] - The vLLM framework was employed for virtualization deployment, achieving high concurrency and low latency, which is crucial for the real-time and safety-critical nature of air traffic control [4] Group 4: Future Directions - The launch of the intelligent system demonstrates the feasibility of large model technology in high-safety industries, with plans for further integration of multimodal capabilities, including voice, image, and video recognition [5] - The technical team aims to enhance the intelligent system's multi-source perception capabilities and promote the comprehensive implementation of various AI application scenarios [5]