  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.
