Empirical Study of Drone-LoRa Enable Performance to Doppler Robustness for Livestock Industry

Abstract

This study develops an airborne LoRa gateway system for livestock industry that can help to improve food demand. The objective of this study is to learn the doppler effect on LoRa regarding drone speed, which drone speed can achieve the optimum LoRa performance and the effect of Drone-Lora on LoRa coverage expansion. The method is carried out by developed a LoRa-based water quality monitoring system that detects water level, temperature, pH, turbidity, dissolved oxygen, and electro conductivity for livestock drinking water, as well as the LoRa gateway. Following that, for the coverage extension experiment, LoRa RSSI data is collected every 200 meters, and for the doppler effect experiment, drone-LoRa enable fly at 5 km/h with increments of 5 until maximum speed reaches 95 km/h to 100 km/h. The result is drone-LoRa enabling immune to doppler effect with LoRa spreading factor 12 and drone-LoRa capable of extending LoRa coverage by more than 10 km radius. This research aims to show that drones with LoRa capabilities can be a boon to smart farming in livestock industry by demonstrating that drone speed has no effect on LoRa performance.