UAV Platform for Pesticide Spraying and Disease Detection for Areca Nut and Pepper Plantations

Drones are a big advancement in precision agriculture and crop management based on GPS and big data as a method to boost crop productivity while addressing water and food shortages. According to studies, there has been an increased demand for systems which deal with accurate spraying of palms and on-board disease detection. This research presents the simultaneous localisation and mapping (SLAM) of palm plantations, and their geolocation using YOLOv4 detector. Autonomous Sequential Decision Process (SDP) is carried out to navigate using the Pixhawk’s inbuilt PX4 system that uses the palms detected through the camera as targets and navigates around them and successively to the next palm. Images captured by the drone are scanned for any signs of yellow leaf disease or rot by learning vector quantization (LVQ) and K-Means Clustering within the RGB channels. The key interest of this research is the trajectorial nozzle system which tracks the arecanut and actively adjusts the spray to match the arecanauts’ position.