2024/05/06 by Sana Sharif, Sherali Zeadally, Sharif, Sana +3 · 1 citation
Computer Science · Engineering · #Distributed Control Multi-Agent Systems #FOS: Computer and information sciences #FOS: Electrical engineering #IoT and Edge/Fog Computing #Networking and Internet Architecture (cs.NI) #Systems and Control (eess.SY) #UAV Applications and Optimization #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2405.03863
openalex publication_date 2024/05/06 · openalex created_date 2024/05/11 · openalex updated_date 2026/07/28
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 discuss challenges and future research directions associated with generative AI for resource optimization in UAV-assisted networks.