# Livestock Management on Grazing Field: A FANET Based Approach
## 1 Introduction  
Unmanned Aerial Vehicles (UAVs) can revolutionize livestock herding and management. As a result, there is an increasing scientific interest in using UAVs to manage livestock. UAVs can be used to control livestock grazing areas and remote sensing of these animals. In recent years, most governments have defined livestock grazing areas/fields or paths, with the effectiveness of most herding operations relying on the extraction of information from aerial pictures [1]. In a farm context, UAVs are typically operated at human height or a low to medium altitude, giving them the same or wider angles of view as humans. As established by the regulatory body, grazing field mapping can be used for UAV operations due to the similarity of viewpoint with people at eye level. However, some computational and scientific issues are unique to UAV operations. One of these issues is the minimum time coverage of ground regions utilizing a group of unmanned air vehicles (UAVs) dubbed Flying Adhoc Network (FANET) outfitted with image sensors [2]. As a result, this research proposes a way for using UAVs to cover and sense ground areas. The paper will concentrate on practical issues arising only during vehicle deployment. The number of UAVs utilized in the task, for example, is determined by the area's size and layout, the UAV's maximum flight time and, more crucially, the time required to prepare and launch the UAV. Figure 1 depicts the conceptual diagram. The operation of multiple UAVs to achieve adequate coverage is dependent on the mode of communication amongst the UAVs. It is critical to ensure that the communication efficiency among sensor-equipped devices is at the highest level to accomplish a flawless operation of UAV-based livestock management [3]. TheseUAVs' communication is typically affected by the speed of the UAVs within the grazing field. Nonetheless, with the high speed of UAVs, a high coverage area is said to be achieved because the UAVs are moving at a faster speed.  
Some studies have used aerial pictures (satellite imagery) and UAV-based communication systems to examine farm animal tracking and monitoring for applications such as grazing distribution monitoring, pasture usage, domestic livestock management, and livestock behavior. Grazing distribution monitoring has attracted increased attention, intending to manage individual animals through continuous and real-time monitoring of their perimeter coverage during grazing as well as their health, welfare, output, and environmental effects. The data collected during the livestock monitoring procedure contributes to the long-term viability of the agroecosystem by providing herders with timely and reliable information about how their animals behave on the farm [4]. Nonetheless, it is known that satellite usage is applicable for animal tracking and monitoring through space-retrieved imagery that can analyze cattle productivity on different pastures. However, the use of drones is justified when the angle matters. Some uses of drones for livestock management include spotting trespassing hunters, farming illegal activities, and controlling herder operations.  
The contributions of this paper are as follows:  
1. We designed and proposed a deployment scheme that considered the geographic coordinates of the grazing field for practical implementation. To our knowledge, this has not been adequately treated before.
2. The proposed deployment scheme focused on achieving an optimal coverage time and interconnections for efficient grazing field surveillance.
3. We also proposed a task-sharing protocol between the multiple UAVs for effective task sharing and cooperation.  
Section 2 presents a review of some of the pertinent literature works. Section 3 presents the methodology used to present the proposed solution, which shows the step-by-step approach and the conducted simulation. In Section 4, the obtained result is presented together with the analysis. Finally, Section 5 presents the conclusion drawn from the results and concludes the report.