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<p>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. The findings of the study suggest that these technologies have the potential to act as foundational elements that technically strengthen the realization and advancement of smart cities and drive innovation within this transformative&#xa0;urban&#xa0;milieu. However, there are certain formidable challenges that DL, FL, IoT, blockchain, NLP, and LLMs face within these contexts with potential future directions. The study has implications for researchers working on developing sustainable smart cities.</p>

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Toward sustainable smart cities: applications, challenges, and future directions

  • 期刊论文

  • 发表日期：

    2025年6月27日

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  • Amin Ullah,
  • Saddam Hussain Khan,
  • Irfan Ullah,
  • Tariq Mahmood,
  • Samra Nawazish,
  • Zafar Ali,
  • Amjad Rehman

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. The findings of the study suggest that these technologies have the potential to act as foundational elements that technically strengthen the realization and advancement of smart cities and drive innovation within this transformative urban milieu. However, there are certain formidable challenges that DL, FL, IoT, blockchain, NLP, and LLMs face within these contexts with potential future directions. The study has implications for researchers working on developing sustainable smart cities.