Precision agriculture increasingly depends on fast and accurate data collection and analysis. Remote sensing technologies, especially those using unmanned aerial vehicles (UAVs), have become essential tools for monitoring agricultural conditions and crop health. UAVs provide valuable information through sensors such as multispectral, digital, and hyperspectral cameras, allowing detailed insights into crop physiology and environmental factors.
This project introduces AGROBOT, an intelligent agricultural robot designed for plant and pest detection in the field using advanced deep learning and image processing techniques. Equipped with aerial and ground mobility, AGROBOT will use hyperspectral imaging to identify anomalies in crops and support early detection of diseases and pests. It will also play a key role in arthropod monitoring and control.
By integrating cutting-edge technologies such as computer vision, machine learning, robotics, and the Internet of Things (IoT), this project aims to improve the automation, efficiency, and sustainability of farming operations. AGROBOT will also support precision weed management and crop yield prediction, making it a versatile tool for modern agriculture.
