## 1 Introduction  
The continued increase of the world population and its need for food, as well as the decrease in natural resources, has led to the necessity of making great changes in agriculture. Farmers and agricultural workers must implement measures to improve and control the state of crops and to optimize the utilized resources. In many countries, farmers are opting to implement solutions that apply technological means. For example, the European Union (EU) established in its 2020 strategy policies such as the Common Agricultural Policy (CAP) [1], which responds to the new economic, social, environmental, and technological challenges facing our society, and as a result, it contributes to its development. One of those policies has its focus on Precision Agriculture (PA). PA consists of observing, measuring, and acting on crops, regardless of the conditions of the site and utilizing certain technologies [2; 3]. Authors such as [4] present PA as a systematic process that covers data collection, diagnostics, data analysis, and precision field operation and evaluation. As a result, decision making is simplified and better adapted to the ideal solution, leading to obtaining better results. One of the technologies that is being utilized the most in PA implementations is sensor node systems. The advantage of these devices is that they can capture information to observe a large number of environmental parameters 24 h a day, 365 days a year, and their values can be monitored in real time if necessary. The information can be stored and transmitted at any time, based on the developed system and the needs of crop control as long as there is an Internet connection in the deployed area. Gateways in PA systems can be deployed on different manners, i.e., on poles, on trees, on moving machinery such as tractors of pivot-center irrigation structures, and on drones. For the cases where the gateway is located on a static position (poles and trees), the network would require a larger number of gateways to cover the expanse of the fields. Using moving manned vehicles and irrigation structures would be possible for crops that require those vehicles to go through the fields often enough or to be irrigated using pivot-center structures regularly. However, drones can be utilized in more comprehensive types of crops and are not restricted to specific moments of the plant growth where the machinery is necessary. It also allows reducing the cost as only one gateway is required. The use of drones, also known as Unmanned Aerial Vehicles (UAVs) in the military field or Remotely Piloted Aircraft (RPA), has been increasing in the recent years due to the improvement in design and accessibility. Drones are primarily used to perform remote sensing and can capture photographs and videos to send them in real time or to store for later analysis. These images can be utilized to perform mapping, navigation, and georeferencing [5] for applications such as agriculture, forestry, surveillance, location and rescue, environmental monitoring, photogrammetry, vegetation analysis, atmospheric monitoring, wildlife conservation, cultural heritage conservation, and urban environment monitoring [6]. In precision agriculture, remote sensing can be used to monitor growth vigor, drought stress, and nutrients, to detect weeds and pathogens, and to perform yield prediction using multispectral, hyperspectral, RGB (Red, Green, Blue), and thermal sensors [7]. Their use is being extended to the implementation of smart systems such as the system proposed in [8] where a drone took pictures of palm trees and communicated with smart insect traps to spray insecticide. They can also be used as tools for treatments with fertilizers or phytosanitary products or even to scare away birds. The agriculture drones market size is expected to grow from USD 1.2 billion by 2019 to USD 4.8 billion by 2024 at a CAGR (Compound Annual Growth Rate) of 31.4% [9].