大语言模型在可持续智慧城市中的作用：应用、挑战与未来方向
The Role of LLMs in Sustainable Smart Cities: Applications, Challenges, and Future Directions
AI总结：
本文探讨深度学习、联邦学习、物联网、区块链、自然语言处理和大语言模型在优化智慧城市ICT流程中的应用潜力，并分析其面临的主要挑战与未来发展方向。
摘要：
智慧城市是持续提升城市生活水平的关键组成部分，通过可持续和可扩展的创新促进城市区域的快速扩张，同时高效管理资源。在此背景下，随着人工智能（AI）、物联网（IoT）、大数据分析以及雾计算和边缘计算等新兴技术日益普及，智慧城市应用面临各种挑战，包括机密和敏感数据可能遭到未经授权泄露的风险。新兴技术的无缝集成在维持其动态发展步伐方面发挥了至关重要的作用。本文探讨了深度学习（DL）、联邦学习（FL）、物联网、区块链、自然语言处理（NLP）和大语言模型（LLMs）在优化智慧城市内信息通信技术（ICT）流程方面的巨大潜力和应用。我们旨在突出这些技术作为基础要素的巨大潜力，它们在技术上加强智慧城市的实现和进步，强调它们在这一变革性城市环境中推动创新的重要意义。我们的论述最后探讨了深度学习、联邦学习、物联网、区块链、自然语言处理和大语言模型在这些背景下所面临的艰巨挑战，并对潜在的未来方向提出了见解。
英文摘要：
Smart cities stand as pivotal components in the ongoing pursuit of elevating urban living standards, facilitating the rapid expansion of urban areas while efficiently managing resources through sustainable and scalable innovations. In this regard, as emerging technologies like Artificial Intelligence (AI), the Internet of Things (IoT), big data analytics, and fog and edge computing have become increasingly prevalent, smart city applications grapple with various challenges, including the potential for unauthorized disclosure of confidential and sensitive data. The seamless integration of emerging technologies has played a vital role in sustaining the dynamic pace of their development. This paper explores the substantial potential and applications of Deep Learning (DL), Federated Learning (FL), IoT, Blockchain, Natural Language Processing (NLP), and large language models (LLMs) in optimizing ICT processes within smart cities. We aim to spotlight the vast potential of these technologies as foundational elements that technically strengthen the realization and advancement of smart cities, underscoring their significance in driving innovation within this transformative urban milieu. Our discourse culminates with an exploration of the formidable challenges that DL, FL, IoT, Blockchain, NLP, and LLMs face within these contexts, and we offer insights into potential future directions.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
