# Algorithms for Delivery of Data by Drones in an Isolated Area Divided into Squares
## 2 Materials and Methods
### Drone Network Architecture and Communication
The endurance of drones can be improved using various methods, such as changing the battery [44; 45], charging the battery via wires [46; 47], wireless recharging [48], solar cells [49; 50], laser-beam in-flight recharging [49; 51], and tethered drones [49]. An average time of 90 min is needed to fully charge an empty battery. An automated means of charging a battery via a wire can be performed using a charging platform installed on the ground and a drone retrofit-kit mounted on the drone [46; 47]. Thus, the landing gear of the drone is connected by touch with the charging platform after the drone lands, and charging starts automatically. The main disadvantage of this system is that the drone is locked on the ground during the charging of the battery. An automatic battery changing and recharging system was investigated in [44]. The battery is automatically recharged after it is changed at the station. The electricity needed at each station is able to be provided by a solar panel that charges a battery located at the station. The changing time depends on the efficiency of the changing mechanism, and varies between 15 s [44] and 60 s [45]. In the current study, a maximum changing time before the drone is ready to take off of 60 s was considered. Four flight tests were performed based on the square-shaped flight mission in the Brasov area of Romania. The flight tests were performed at a temperature of 2 \({}^{\circ}\)C, humidity of 69%, and wind speed of 3.5 km/h. A Samsung S9 smartphone device, on which DJI Go 4 app software (DJI, Shenzhen, China) was installed, connected to a DJI remote controller, was used to program the flight mission segments and to remotely control the drone (Figure 4). A flight altitude of 30 m was chosen [52] and the cruise flight distance of each drone was 12,000 m. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Max ascent/descent speed & 4 m/s; 3 m/s \\ Max flight time (no wind) & 31 min (at a consistent 25 km/h) \\ Max flight distance (no wind) & 18 km (at a consistent 50 km/h) \\ Drone battery & 3850 mAh, 1800 mA, 3.83 V \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Drone performance [43]. Figure 3: Square shape flight mission profile of the drone. The theoretical flight times calculated based on the drone specifications (max. ascent, descent speeds, and cruise speed) are not realistic for simulations. The main factors that influence the experimental flight times are acceleration and deceleration of the drone, and wind speed. The mean flight time for each flight segment was calculated based on the flight tests (Table 2). Moreover, the average calculated cruise speed of the drone obtained from the flight tests was 12.93 m/s. The percentage of the remaining drone battery obtained at the end of the flight mission was 16% for the rectangular cell. The charging time for the drone battery was 79 min. A safety multiplier of 1.1 was applied to obtain the considered charging time, and the resulting time was used in the simulations. Thus, 87 charging minutes were considered for the rectangular cell flight. The average values of the flight times for each segment were used as input parameters for the simulation of the drone networks in the DTN algorithms. Eight high-resolution and two infrared sensors were used on the DJI Mavic 2 Pro. These sensors enabled omnidirectional obstacle sensing, to determine the relative speed and distance between the drone and the object, and to ensure good stability in forward and hovering flight. Left, right, up, down, forward, and backward obstacle sensing were used. A NodeMCU Lua Wi-Fi, V3, ESP-12E, CP2102 Wi-Fi Arduino development board (Espressif Systems, Shanghai, China) was used for the data transfer between the drones and the stations. The main characteristics of the NodeMCU are shown in Table 3. The data were stored on a micro-SD card. The Wi-Fi board and micro-SD card module are very lightweight and have very low power consumption.