Researchers from the Department of Electrical Engineering, Universitas Padjadjaran (Unpad) have published an exciting study titled “Design of Intelligent Sprayer Control for an Autonomous Farming Drone using a Multiclass Support Vector Machine.” This work introduces an innovative approach to precision agriculture by equipping autonomous farming drones with an intelligent sprayer control system. Instead of applying water at a constant rate, the system uses Multiclass Support Vector Machine (MSVM) to determine the optimal watering strength based on key environmental factors such as drone altitude, wind speed, and movement.
The research team conducted experiments with a dataset of 3,750 entries across six classes, testing their MSVM-based design through multiple flight trials. The results were highly promising, with the system achieving accuracy levels up to 99.83%. Beyond accuracy, the analysis of precision, recall, and F1 scores demonstrated robust performance across all classes, ensuring that the drone sprayer delivered the right amount of water in diverse conditions. This marks a significant step forward in creating smarter, more resource-efficient farming drones that can adapt to real-world challenges in agriculture.
This innovation directly supports Sustainable Development Goal (SDG) 2: Zero Hunger, by promoting sustainable farming practices that increase productivity while conserving water resources. With global demand for food continuing to rise, Unpad’s contribution highlights the vital role of advanced technology, artificial intelligence, and smart systems in ensuring food security. By integrating AI-driven solutions into agriculture, Unpad researchers are paving the way toward a future where farming is not only more efficient but also environmentally responsible.
Link: https://www.degruyterbrill.com/document/doi/10.1515/opag-2022-0375/html
#UnpadResearch #SmartFarming #SDG2
06/TE/2025
