# Spectral and Energy Efficiency Trade-Off in UAV-Based Olive Irrigation Systems
### Precision Irrigation  
In the literature, various methods and systems have been developed for precise irrigation. [PERSON] et al. developed in [18] an automated irrigation protocol for olive farms, where RDI (regulated deficit irrigation) strategies were implemented. The authors used a decision support system (DSS) to evaluate the productive response of a heterogeneous plot in a super high-density plantation olive grove. The irrigation process was carried out automatically based on the information obtained through wired sensors. However, using cables to communicate data in smart farming presents several drawbacks, such as scalability, deployment costs, absence of mobility, and cable corruption. Therefore, adopting wireless communication technologies like LoRaWAN (Long-Range Wide-Area Network), ZigBee, Bluetooth, and the IEEE 802.15.4 protocol presents an attractive alternative to wired networks [5; 19]. In [19], [PERSON] et al. developed an IoT-based system to monitor the water scarcity of a vineyard, where different types of ground-based sensors were implemented. The LoRaWAN standard was adopted to ensure data transmission. The results showed that the proposed system outperforms other IoT systems based on Bluetooth or WiFi communications. However, as aforementioned, these wireless communication technologies do not guarantee precise irrigation, mainly in terms of delay, speed, scalability, and bandwidth. Therefore, other recent studies proposed using 5G/6G technologies to deploy smart irrigation systems. For example, in [20], [PERSON] et al. proposed a framework for a drip irrigation remote control system (DIRCS) based on mobile application and IoT-enabled 5G technology. Precisely, the DIRCS framework is managed remotely through a mobile application. Data storage and sharing are ensured by IoT-enabled 5G technology.  
One of the most crucial variables in a precise irrigation system is soil moisture, which provides information about the water content in agricultural fields and the vegetation indices used in precision agriculture [21]. The traditional way to measure soil moisture is with the use of moisture sensors that are installed directly in the soil. There are four methods for measuring soil moisture: (i) resistance blocks, (ii) travel time sensors, (iii) capacitance sensors, and (iv) neutron thermalization [22]. Unfortunately, directed measurements havedifferent issues depending on the sensor type [23]. All these shortcomings encourage the development of remote sensing (RS) approaches. They will allow for data acquisition of soil moisture measures without physical contact with a sensor [24]. Therefore, remote sensing applied in smart irrigation offers the advantage of collecting vital information on a large temporal and spatial scale which cannot be achieved with traditional technologies. In recent years, using unmanned aerial vehicles has enhanced remote sensing approaches for measuring soil moisture [25]. In fact, remote sensing systems based on UAVs are efficient, cost-effective, and have great geometric accuracy. UAVs can potentially reduce the data acquisition gap between conventional ground-based methods and satellites [26]. The combination of the IoT and UAVs in precise irrigation has been widely considered by researchers in many existing works (see, for example, [27] and the references therein). In [27], [PERSON] et al. considered the problem of water scarcity in arboriculture and proposed a smart irrigation solution based on UAVs and ML. The deployment of UAVs in irrigation systems was studied to save both waste and time. The UAVs were equipped with different remote sensors and collected the necessary data (such as soil moisture) for the irrigation process. The collected data were processed using ML techniques, allowing the smart IoT system to make better decisions.