Future Integrated Network of Sensing, Computing, and Communication: Low-Altitude Economy under High-Speed Trajectory Tracking Dominated by General Artificial Intelligence
The rapid expansion of the low-altitude economy (LAE)demands highly reliable Unmanned Aerial Vehicle (UAV) systems. However, traditional UAV control engineering suffers from severe time latency inherent in its serial architecture and is significantly amplified in complex urban environments. To address this challenge, 6G-enabled Integrated Sensing, Communication, and Computing (ISCC) architectures are being utilised to reduce transmission delays. Furthermore, Large Language Models (LLMs) are introduced to shift the design paradigm of control engineering, aiming to improve decision timeliness through predictive state estimation and reasoning. This article reviews the advantages of coupling 6G ISCC with LLMs. The synthesis indicates that this integration effectively minimises system latency by substituting iterative mathematical calculations with direct semantic prediction, its transition to real-world deployment faces severe engineering bottlenecks where the intrinsic "black-box" hallucinations of LLMs are paramount. This paper concludes that autonomous UAV operations necessitate a fundamental shift toward Trustworthy and Explainable AI (XAI), coupled with high-fidelity digital twin validation, to guarantee system stability in safety-critical domains.