MoniKorn: Autopilot Drone System for Real – Time Monitoring and Detection of Ostrinia Furnacalis Infestations Using Image Processing

Abstract

Pest management remains one of the biggest hurdles in corn farming, especially with infestations caused by the Asian Corn Borer (Ostrinia furnacalis). In many farming communities across the Philippines, pest detection still relies heavily on manual labor and broad pesticide use methods that are not only time-consuming but also harmful to the environment and human health. This study introduces MoniKorn, a smart farming solution in the form of an autopilot drone system designed to monitor and detect Ostrinia furnacalis infestations in real time using image processing and artificial intelligence. Built with Raspberry Pi 5, Pixhawk Pro M10, and powered by YOLOv8 object detection, the drone can fly autopilot or be remotely controlled via a mobile application. It captures aerial footage, detects signs of infestation like leaf discoloration, holes, and wilting, then geo-tags the affected areas while providing actionable recommendations to farmers. Using a mixed-methods research approach, the researchers tested the MoniKorn system in cornfields across Pampanga and Tarlac, engaging with local farmers, agricultural experts, and drone specialists. The system proved effective covering one hectare per flight, operating within safety regulations, and significantly cutting down the time and labor required for pest monitoring. Its most notable feature was its ability to geo-tag infested areas, helping farmers respond more quickly and effectively. In blending technology with agriculture, MoniKorn not only offers a smarter way to protect crops but also empowers communities with tools that promote sustainable and resilient farming.