# Real-Time Object Detection Based on UAV Remote Sensing: A Systematic Literature Review
## 1 Introduction
For example, emergency responses can be supported by real-time object detection [7], and people also require UAV real-time object detection for safety reconnaissance and surveillance [19]. However, most of these articles considered and addressed only the algorithm factor of real-time object detection while ignoring how the algorithms can be deployed on UAVs [20]. Other UAV real-time object detection components that have not been fully considered when developing a complete workflow in previous studies, including software and hardware technologies based on the embedded system, need further investigation [10]. One review [21] investigated hardware, algorithms, and paradigms for real-time object detection but was limited to precision agriculture. Another review [22] provided a well-summarized and categorized approach to real-time UAV applications, as well as relevant datasets. However, there was no further discussion on how to implement real-time object detection based on UAVs. From a technological perspective, better-performing miniaturized hardware and the surge of deep learning algorithms both have a positive impact on UAV remote sensing data processing [4]. It is worth reviewing and investigating how these new technologies are applied in UAV real-time object detection tasks. As a result, most of the aforementioned studies focused on real-time detection algorithm investigations. They should have paid more attention to algorithm deployment, which could be critical to successfully implementing UAV object detection in practice. Although reviews also discussed solutions for UAV real-time object detection algorithms deployed on embedded hardware, they were limited to a specific domain. This study aims to fill the gaps in the previous work that paid limited attention to onboard UAV real-time object detection implementation. Furthermore, the entire UAV real-time object detection process will be summarized as a hardware and software framework that can be used for subsequent onboard real-time processing. The hardware and software framework can serve as a reference for researchers working in the UAV real-time data processing field and drive them towards the development of more efficient autonomous UAV systems. Therefore, the first research objective of this paper is to summarize the application scenarios and the targets of real-time object detection tasks based on UAV remote sensing in order to demonstrate the necessity of real-time detection. The second research objective is to investigate the current implementation of real-time object detection based on UAV remote sensing to observe the impact of sensors, computing platforms, algorithms, and computing paradigms on real-time object detection tasks in terms of accuracy, speed, and other critical evaluation metrics. The rest of the paper is organized as follows. Section 2 presents and describes the steps and methodology of our systematic literature review. Then, a general analysis of this systematic review study is provided in Section 3. In Section 4, the quantitative results are visualized and discussed according to the proposed research questions, and Section 5 discusses the current challenges and future opportunities of UAV real-time object detection. Finally, Section 6 concludes the paper.