Summary of The Role Of Llms in Sustainable Smart Cities: Applications, Challenges, and Future Directions, by Amin Ullah et al.
The Role of LLMs in Sustainable Smart Cities: Applications, Challenges, and Future Directions
by Amin Ullah, Guilin Qi, Saddam Hussain, Irfan Ullah, Zafar Ali
First submitted to arxiv on: 7 Feb 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper explores the potential applications of various emerging technologies in optimizing ICT processes within smart cities. Specifically, it examines the role of Deep Learning (DL), Federated Learning (FL), Internet of Things (IoT), Blockchain, Natural Language Processing (NLP), and Large Language Models (LLMs) in sustaining the rapid development of urban areas while efficiently managing resources through sustainable innovations. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Smart cities are growing rapidly, but they face challenges like data security. This paper looks at how new technologies like AI, IoT, big data, and edge computing can help make smart cities better and more efficient. It focuses on six key technologies: Deep Learning, Federated Learning, IoT, Blockchain, NLP, and LLMs. These technologies have the potential to strengthen smart cities and drive innovation. |
Keywords
» Artificial intelligence » Deep learning » Federated learning » Natural language processing » Nlp
