# AVSS: Airborne Video Surveillance System
## 2 Related Work  
In this section, the work that has similarity to the UAV surveillance system are introduced. Many researches have been conveyed in a UAV network area, but most researches lack implementations. According to [1], the definition of a flying ad-hoc network (FANET) is a \"new form of mobile ad-hoc network (MANET) in which the nodes are UAVs\". FANET is set apart from other networks with characteristics such as: a higher mobility than any traditional networks, the aerial environment, and importance of connectivity [2]. The characteristics of the network adopted in UAV surveillance system are similar to those of FANET definition. Yet, most researches on FANET are theoretical as they are difficult to implement. As there are countless vehicle ad-hoc network papers but only a handful of papers include implementations, the UAV surveillance system is one of the handful of papers with an actual network implementation.  
Many of wireless surveillance systems such as Vigil [3] consist of static nodes. Vigil is a real-time distributed wireless surveillance system with edge computing nodes (ECNs). Vigil's ECNs locally process each camera's video data and upload only analytic information with significant video frames to the cloud. While Vigil utilizes wireless resources efficiently, its surveillance area is limited because of the static nodes. To overcome this limitation, we deploy UAVs as nodes of the surveillance system, while providing stable network connections with UAVs and users. [PERSON] et al. tried to provide consistent video streaming over HTTP [4]. To realize the consistent streaming, authors state that consistent video streaming requires a rate adaption algorithm.  
In the work by [PERSON] et al. on CCTV evaluation index [5], the authors devised a method to evaluate the quality of the CCTV image. The index is mainly represented as the ratio between the actual length of an object and its projected length on the image. We have taken out some factors in the work that are not applicable in our work and incorporated camera quality for the index. [PERSON] et al. conducted a full, comprehensive survey of multiple unmanned vehicle surveillance [6]. This comprehensive survey of the field provides a full background information on video surveillance, and it states the application of ad-hoc network to a persistent surveillance is limited. However, we have built our system on an ad-hoc network while providing persistent network with video streaming service. Our work has network traffic control and video rate adaptation algorithm, which helps the application of otherwise difficult ad-hoc networking. For UAV surveillance, many issues exist: camera angle, UAV mission planning, image stabilization, and more. [PERSON] et al. proposed control mechanism for UAV-based surveillance in complex urban area [7]. [PERSON] et al. considered a gimbaled camera which has capability of pan and tilt for UAV surveillance and solved the problem of mission planning [8]. [PERSON] et al. suggested real-time aerial image stabilization system [9]. With the system, the ground station receives data and video stream from the UAV, and conducts the stabilization process. Our work do not include above features, but it can adopt the above and improve overall performance.