**4. Conclusions**

Precision agriculture is a technological reality in orchards. In our study, soil sensors resulted in a better option than UAV imaging. UAV platforms require more research and different bands to detect how micro-sprinkler irrigation is working in real-time. Imaging analysis is much more complicated than simple embedded systems and producers. Producers find UAV technology complicated and environmental conditions make them much more difficult to use than simple embedded systems. Imaging analysis obtained by the camera is challenging for them.

Soil moisture sensors in a walnut orchard were tested; some of them as the DHT 11 and YL-69 failed after 1 week of operation. When drops of saturated water pour over the DHT 11 sensor, it failed after 3 days, meanwhile the YL-69 got rusty after applying a direct current voltage to it. The capacitive 1.2 probe covered with a corrosionresistant material proved to measure properly during several seasons and under clay and loam soil. The V1.2 probe is very cheap and energy-efficient. The sprinklerdecoder sensor was the more efficient sensor based on current consumption, but its price increased by a factor of 2.5. Wetness sensors are being developed with flexible substrates to detect dry and wet conditions but are still very expensive.

WSN groups of nine trees were formed by hectare within the orchard; each group transmitted its information through a LoRa module. The BLE node proved much more economical than the laser system and both operate properly. LoRa modules transmit information toward the farmers' house sending the tree number where the micro-sprinkler failed. LoRa is able to transmit at distances of 500 m even when the temperature ranges between 30 and 35°C. The WSN system can be used to transmit other information from the plantation using a similar version of tree grouping.
