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

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.

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Publication Details

Journal
IEEE Internet of Things Magazine
Published
2024-11-04
DOI
https://doi.org/10.1109/iotm.001.2400045
Citations
2
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.70
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article

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

Sherali Zeadally, Waleed Ejaz, Sana Sharif
2 citations
IEEE Internet of Things Magazine
IoT and Edge/Fog Computing
0.70
article

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

Sherali Zeadally, Waleed Ejaz, Sana Sharif
article en
2 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.

IEEE Internet of Things MagazineVol. 8(1)
University of Kentucky (US), Lakehead University (CA)
Openalex Percentile: Top 27%
IoT and Edge/Fog Computing
0.70
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Resource Optimization in UAV-Assisted IoT Networks: The Role of Generative AI — Sherali Zeadally, Waleed Ejaz, et al. · IEEE Internet of Things Magazine (2024) | TGRS Research Map | TGRS