## 1 Introduction
#### TeenOlivo Project  
TeenOlivo pursues modernizing a traditional agricultural sector such as olive cultivation, by creating a pioneering technological device that opens up new business opportunities, and places the olive production industry of Huelva and that of the southeast of Portugal at the forefront of international innovation and, by extension, the rest of Andalusia, Spain, and Portugal. With 2.5 million euros of budget, co-financed with FEDER Funds and submitted to the first call of the INTERREG V-A Spain-Portugal Programme (POCTEP 2014-2020), the project targeted the development of a marketable technological solution (TecnOlivo) to be easily-used by farmers, and which allows the integral, ecological, and optimized management of the olive grove by monitoring non-invasive agronomic parameters of interest to partner olive growers. With TecnOlivo, partners sought to improve the sustainability of olive cultivation, by favoring an optimal use of resources. Figure 2: Specific energy/power comparison among different energy sources. TecnOlivo represented a holistic solution to traditional olive farming in which an unmanned aerial vehicle captured georeferenced crop information through cameras or other sensors, and integrated the data collection, transmission, analysis, processing, visualization, action guidelines, and \"learning processes,\" in an easy and ergonomic way for the farmer. It was supported by a network of low-cost ground sensors, which will constitute a relevant intelligent tool for olive farmers, such as those ancient farming tools and farm tractors were in their days. Thus, TecnOlivo will allowed olive growers to know, in real-time and on-the-spot, information on key parameters such as the hydric status and nutrients of the groves, what extent treatments were needed, and in what areas of the orchards. During the development of the project Tecnolivo [67; 68; 69; 70], different types of rotary-wing RPASs were used, but when the extensions of the study area were very large, an RPA with greater autonomy was missing. The TecnOlivo project proposed a methodology for plant detection, geolocation, and counting in olive orchards, based on aerial imagery and image processing and analysis. To that end, an RPAS equipped with a multispectral camera was used to carry out image acquisition. The captured multispectral images were processed in order to yield a DSM (digital surface model). This data structure was subsequently transformed by means of mathematical morphology, aiming to individually segment the olive trees appearing in the images from the ground. Aerial imaging was conducted using a DJITM Matrice 100 RPAS (SZ DJITM Technology Co., Ltd., Shenzhen, Guangdong, China). This aircraft is propelled by four rotors (quadcopter), enabling its vertical take-off and landing. Images were taken with the multispectral camera MicaSense RedEdge-MTM (MicaSense, Inc., distributed by ACE surveying solutions, Spain), installed on the RPAS. This sensing device was capable of capturing information in five different spectral bands within the visible and the infrared spectrum. The main problem was that the quadcopter batteries had to be changed every 15 or 20 min, making the data collection missions very short. For this reason, the goal of this paper is to propose a methodology to transform an ICE RPA into an electric RPA with the aim that the developed aerial platform takes advantages from both ICE and electric technology. Preliminary results indicate that the endurance achieved with the new energy and propulsion systems and the payload weight available in the RPA meet the expectations of the use of this type of aerial platform in the study of large areas of crops. The autonomy achieved by the electric RPA is almost 50% more than the same model with internal combustion engine. If it is compared with the commercial UAV (multicopters) models currently used in the TecnOlivo project, the advantage in terms of flight autonomy and surface to be treated is enormous.