Autonomous Drone Technology based Random Forest Classifier for Revolutionizing Agriculture

Conventional farming practices in Indonesia face numerous challenges, including low productivity, weather unpredictability, and overuse of natural resources. Autonomous drones offer a promising solution, enhancing efficiency and precision in agricultural operations. The implementation of a monitoring system facilitates real-time assessment of drone performance, including adherence to flight routes, speed, altitude, and detection of abnormalities. Utilizing the Random Forest (RF) method, this system conducts eight classifications of drone data with remarkable accuracy, reaching up to 98%. This innovative approach holds significant potential for revolutionizing the agricultural industry in Indonesia, driving towards sustainable and technologically advanced farming practices.