## 2 Related Works
### Study of the State of the Art
To obtain data about yak individual movement and behavior, the yak herd was watched from 5 to 8 days every month in a grazing area of 48.5 hectares. A DJI Phantom 3 UAV was used to take photographs, which were used for data analysis. Results showed that there was no significant difference between ground-counting and UAV-based methods for yak herds, thus providing a relatively cost-effective and noninvasive monitoring toolfor large cattle. Unfortunately, these activities did not involve the development from scratch of a tailored solution for the objective of the presented research, nor security or the development of a secure infrastructure was a development goal sought or conceived from the very beginning. [PERSON] et al. [16] have performed research operations on how to use UAVs as a tool to complement biologging (that is to say, getting precise knowledge about spatial distribution of animals) in spatial ecology studies, especially with regard to the forecasting of animal distribution patterns. In this sense, the authors of this manuscript make use of Unmanned Aerial Systems (UASs) to monitor several individual animals within the Dorana Nature Reserve with GPS collars for them. Afterwards, the UAS registered data is compared to predicted spatial patterns; results offer similar spatial distributions for both cases. Sampling sizes, data features (accuracy, diversity and frequency) or impact are mentioned as parameters that strongly influence experiments of this kind. This reviewed paper proves again that UAVs are a reliable and useful way to gather information about animals scattered in an open field. However, as it was mentioned in other research works, this paper is not oriented towards the enhancement of UASs with security components, nor there is any reference on how to build a tailored solution from scratch for improved animal monitoring. Finally, the scope of this manuscript is different from ours, as it is aiming towards monitoring GPS-traceable animals by means of a glider-like UAV, whereas we make use of a quadcopter and expand the usage of the UAV beyond animal monitoring,  
[PERSON] et al. [17] put forward their own developments for sheep livestock monitoring. The authors describe how they have chosen a quadcopter as the most suitable option for cattle monitoring, since it does not require a runaway for takeoff and landing. It is mentioned how the ArduPilot Mega (APM) is used as the flight controller, which reflects some of the choices that have been done for our own solution. A Raspberry Pi processor and a camera are used as part of the UAV as well. Once the UAV is deployed, it is used to collect data processed afterwards for animal detection and counting. When all is said and done, this paper shows that a UAV built from scratch with off-the-shelf components is viable for livestock monitoring, but it makes no reference on how to secure the data or how to create a framework or system beyond the UAV itself, focusing rather on the data processing procedures. Another piece of research can be found in the study of video cameras to assess feeding behavior of Raramuri Criollo cows [18]. In this piece of work, researchers were most interested in whether the UAV sounds and presence would altern in any way the feeding patterns of the cows (something that is also considered in our own research activities). To assess this, an experiment with two groups of non-lactating cows, where they were fed with and without the presence of UAV noise, was conducted. According to the authors, pilot tests showed no difference in feeding behavior between UAV-naive and UAV-adapted cows, proving that UAV can be good tools for cattle monitoring. However, the presented piece of research does not provide information about UAV features or security frameworks. In addition to this, resources like aerial images from Google Earth can be used for effective monitoring, in the way that has been depicted in [19].