# Proposed Fuzzy-NN Algorithm with LoRa Communication Protocol for Clustered Irrigation Systems
## 4 Experimentation and Evaluation Results
### Ground Humidity Results  
The average value per day of each ground humidity sensor for the two scenarios are depicted in Figure 8a-h.  
Figure 8: \(Cont.\)  
Figure 7: Irrigation time in hours per day based on the majority and FITRA algorithm.  
Figure 8: _Cont._  
Both MVA and FITRA behave normally according to the previous figures. The only figures where two sensors of the MVA algorithm group of sensors present an erroneous and upper boundary sensor behavior are in Figure 8c,f. In these figures the electrodes of these two sensors have been blocked and left open-circuited. The authors deliberately left this malfunction of those electrodes to carry on, as they wanted to test the error control capabilities of the MVA algorithm. That is, for the MVA algorithm only 6 out of the 8 electrodes carried out the actuator selection process. Moreover, both FITRA and MVA sensor upper lower bounds of accepted values interval has been set to 1020 and 120 respectively. From the algorithm error control experimentation, it has been proven that both algorithms  
Figure 8: **(a)** Mean value per day of ground moisture sensor 1 for the two scenarios; **(b)** Mean value per day of ground moisture sensor 2 for the two scenarios; **(c)** Mean value per day of ground moisture sensor 3 for the two scenarios; **(d)** Mean value per day of ground moisture sensor 4 for the two scenarios; **(e)** Mean value per day of ground moisture sensor 5 for the two scenarios; **(f)** Mean value per day of ground moisture sensor 6 for the two scenarios; **(g)** Mean value per day of ground moisture sensor 7 for the two scenarios; **(h)** Mean value per day of ground moisture sensor 8 for the two scenarios.  
enforced successfully their error control phases, and values outside of that interval have not been taken into account.  
The average ground moisture sensor values of the MVA scenario was 695.8, while the average ground moisture sensor of the FITRA scenario was 608.13. This means that the ground moisture of the FITRA scenario was 12.5% higher than the MVA scenario. This difference is due to the fact that the FITRA algorithm opens and closes the central watering valve fewer times but for longer periods. So the water manages to penetrate deep into the soil or it even evaporates. On the other hand, the majority algorithm opens and closes the valve more often for shorter intervals. The water stays on the surface of the soil and minimizes ground evapotranspiration.  
Comparing the two scenarios, the authors observed that the ground moisture sensors present similar values since they are closely scattered on each field. The weather conditions, the soil ingredients and the sensor placements in relation to the watering system were similar for both test cases (MVA and FITRA fields). However, the irrigation time in the FITRA scenario was smaller by 7% compared to the MVA scenario, while the ground moisture was 12.5% higher in the FITRA irrigated field than the MVA irrigated field. These differences are due to the different algorithms that control the actuator of the two irrigation systems.