# The Role of LLMs in Sustainable Smart Cities: Applications, Challenges, and Future Directions

arXiv: https://arxiv.org/abs/2402.14596 · HTML: https://mlsanity.com/paper/2402.14596/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Feb 2024.

## Built on by (most cited first, 9 of 9)

- [Large Language Models for UAVs: Current State and Pathways to the Future](https://mlsanity.com/paper/2405.01745/) (2024)
- [Integrating LLMs with ITS: Recent Advances, Potentials, Challenges, and Future Directions](https://mlsanity.com/paper/2501.04437/) (2025)
- [Trust-Oriented Adaptive Guardrails for Large Language Models](https://mlsanity.com/paper/2408.08959/) (2024)
- [Generative AI in Transportation Planning: A Survey](https://mlsanity.com/paper/2503.07158/) (2025)
- [Leveraging Multimodal-LLMs Assisted by Instance Segmentation for Intelligent Traffic Monitoring](https://mlsanity.com/paper/2502.11304/) (2025)
- [Follow-Me AI: Energy-Efficient User Interaction with Smart Environments](https://mlsanity.com/paper/2404.12486/) (2024)
- [Using Large Language Models in Public Transit Systems, San Antonio as a case study](https://mlsanity.com/paper/2407.11003/) (2024)
- [From Transformers to Large Language Models: A systematic review of AI applications in the energy sector towards Agentic Digital Twins](https://mlsanity.com/paper/2506.06359/) (2025)
- [Activation Sparsity Opportunities for Compressing General Large Language Models](https://mlsanity.com/paper/2412.12178/) (2024)

## Abstract (arXiv)

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.