# UAV Path Optimization for Precision Agriculture Wireless Sensor Networks
###### Abstract
Drones are also able to take high-precision pictures in certain points of the plantation, analyzing points of failure in the harvest and giving more information to farmers. In addition, the data collection time is key in the decision-making process, since IoT agricultural networks sometime provides varying measurements; therefore. it is necessary to ensure that every message is fresh [16]. The correct measurement of the water level present in the soil is fundamental for agriculture [17]. The management of water resources is essential to control soil humidity. The excess of water generates a loss of nutrients, causes root rot, as well as water stress for plants. Many of these processes are still manual, requiring that a worker goes to certain points of the plantation to gather the information required to decide whether or not to irrigate the soil at those points. Developing countries, which have agriculture as their main source of wealth, still have many of their sensory data gathering processes carried out manually [18]. The use of UAVs to collect sensory data has been widely researched due to the need to increase productivity in the sector. [PERSON] et al. [19] carried out studies to optimize UAV paths using the bisector angle to direct the UAV through sensor nodes (SNs), reaching UAVs flight path optimization rates of approximately 25% compared to a non-optimized route, where the UAV must fly over all SN coordinates. [PERSON] et al. [20] studied the use of UAVs to collect sensory data scheduling the active time of grounded SNs with UAV flight enhancing SN lifetime. [PERSON] et al. [21] studied a model that synchronizes the UAV path according to the transmission and hibernation period of sensors on the ground, seeking energy efficiency improvements for stations. [PERSON] et al. [22] researched the application of UAVs for the collection of sensory data, also synchronizing the hibernation and transmission period with SNs. However, they focused their studies on the communication channel model with the UAV and an in-depth detailed analysis on transmission rates and signal strength at the interfaces of the elements involved. [PERSON] et al. [23] investigated the advantages of working with collaborative UAVs gathering sensory data using DTNs-Delayed and Disconnection Tolerant Networks, besides the advantages that this communication model adds to the system. The authors also reported several benefits in using UAVs when compared to land vehicles in agriculture, and proposed route optimization models for problems such as the traveling salesman problem (TSP) and the vehicle routing problem (VRP). Although there are many studies on the application of UAVs in agriculture for collection of sensory data, many authors point out the difficulty in designing systems where SNs have their transmission and hibernation intervals scheduled according to the predefined UAV route [20,24], still being a challenging issue. The main objective of this work is to propose a new strategy where we displace SNs over a large area with no direct communication between them. Then, we consider a UAV as a mobile sink to gather data, where the SN has it own timeslots to become active. The SN's active timeslot can be shared or dedicated. As the UAV must fly over them to find out which are their active timeslots, along with the Prohibition List, we propose a new strategy ensuring UAV path length reduction, associated with a reduction in the SN active time after SNs are properly scheduled. Our focus was not to evaluate the quality of data transferred between UAV and SNs, or study energy constraints of the communication because these aspects were already explored by related authors [20, 21, 22]. Our goal in this work is to investigate the dynamics of UAV flight to understand which scenario presents better results based on each functionality of the system. The rest of this paper is structured as follows. Section 2 presents the characteristics of the UAV path optimization models and main system elements.