## 1 Introduction
### Paper Organization  
The rest of the paper is organized as follows: Section 2 outlines the methodology used in this study and provides a summary of the fundamental design aspects identified from the literature. Section 3 provides a brief background discussion on the concept of AoI and the typical UAV-aided WSN/IoT architectures. Section 4 thoroughly examines the fundamental design aspects of AoI minimization in UAV-assisted WSNs/IoT in the literature. Subsequently, Section 5 focuses on pertinent issues related to UAV-assisted WSNs/IoT design aspects for data-gathering applications. Particularly, Section 5 discusses energy efficiency and the affecting factors, Section 5.2 analyses the factors to optimize UAV trajectory, and Section 5.3 discusses the scheduling issues of IoT devices and UAVs. Section 6 discusses other challenges related to AoI minimization in UAV-assisted WSNs/IoT  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Ref** & **Year** & **Focus** \\ \hline
[56] & 2022 & SDN solutions for drone detection and defense \\ \hline
[57] & 2022 & Resource optimization \\ \hline
[58] & 2022 & UAV placement optimization for 5G and beyond \\ \hline
[59] & 2022 & UAV-aided maritime communications \\ \hline
[60] & 2022 & Drone-assisted monitoring of atmospheric pollution \\ \hline
[61] & 2022 & UAV digital technologies for Construction 4.0 \\ \hline
[62] & 2022 & UAV placement and trajectory optimization \\ \hline
[63] & 2022 & UAV deployment and trajectory \\ \hline
[64] & 2022 & Security threats to UAV-aided IoT applications \\ \hline
[65] & 2022 & AI meets UAVs for precision agriculture \\ \hline
[66] & 2022 & UAV placement and trajectory design optimization \\ \hline
[67] & 2022 & Physical layer security for UAVs \\ \hline
[68] & 2023 & UAV formation trajectory planning algorithms \\ \hline
[69] & 2023 & Drone routing for delivery systems \\ \hline \hline \end{tabular}
\end{table}
Table 1: _Cont._  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Ref** & **Year** & **Focus** & **Summary** \\ \hline
[37] & 2021 & \
\begin{tabular}{c} Low-latency \\ cyber-physical \\ systems \\ \end{tabular} &
\begin{tabular}{c} Provides an overview of the current state of the art in the design \\ and optimization of low-latency cyber-physical systems and \\ applications requiring timely status updates. It also describes the \\ various methods and metrics used to evaluate the Age of \\ Information (AoI) in a wide range of systems and explores the \\ use of AoI optimization in cyber-physical applications. \\ \end{tabular} \\ \hline
[36] & 2022 & \
\begin{tabular}{c} Ambient Intelligence \\ (AmI) Internet of \\ Things (IoT) networks \\ \end{tabular} &
\begin{tabular}{c} Provides a review on notations of AoI, parameters affecting AoI \\ in IoT systems, and techniques for modeling AoI. No special \\ attention was given to UAV-assisted IoT. \\ \end{tabular} \\ \hline
[35] & 2023 & \begin{tabular}{c} Wireless \\ communication \\ networks in general \\ \end{tabular} & \begin{tabular}{c} The paper provides a comprehensive survey of the Age of \\ Information (AoI) in wireless networks and reviews current \\ progress from an optimization perspective. This includes AoI \\ definitions, optimal sampling policies, packet management \\ strategies, scheduling policies, and potential future research \\ directions for AoI research. \\ \end{tabular} \\ \hline This paper & 2023 & \
\begin{tabular}{c} Design considerations \\ in age-aware UAV-IoT \\ \end{tabular} &
\begin{tabular}{c} The paper provides a comprehensive survey of the design aspects \\ of Age of Information (AoI)-aware UAV-assisted IoT and \\ its architectures. \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table}
Table 2: Summary of AoI optimization surveys.  
as well as proposes some future research directions. Finally, Section 7 concludes this paper. The complete meanings of the abbreviations and acronyms are provided in Abbreviations.