Resource Optimization in UAV-Assisted IoT Networks: The Role of Generative AI

Sana Sharif, Sherali Zeadally, Waleed Ejaz

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

We investigate how generative Artificial Intelligence (AI) can be used to optimize resources in Unmanned Aerial Vehicle (UAV)-assisted Internet of Things (IoT) networks. In particular, generative AI models for real-time decision-making have been used in public safety scenarios. This work describes how generative AI models can improve resource management within UAV-assisted networks. Furthermore, this work presents generative AI in UAV-assisted networks to demonstrate its practical applications and highlight its broader capabilities. We demonstrate a real-life case study for public safety, demonstrating how generative AI can enhance real-time decision-making and improve training datasets. By leveraging generative AI in UAV-assisted networks, we can design more intelligent, adaptive, and efficient ecosystems to meet the evolving demands of wireless networks and diverse applications. Finally, we dis-cuss challenges and future research directions associated with generative AI for resource optimization in UAV-assisted networks.

Original languageEnglish
Pages (from-to)34-41
Number of pages8
JournalIEEE Internet of Things Magazine
Volume8
Issue number1
DOIs
StatePublished - 2025

Bibliographical note

Publisher Copyright:
© 2025 IEEE.

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems

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