This research project by i369 Innovation Limited introduces a cutting-edge approach to early-stage disease detection in crops by integrating drone, satellite, and mobile imagery with advanced computer vision technologies. The multi-tiered system combines high-resolution drone imagery for localized crop monitoring, satellite imagery for broad-area analysis, and mobile imagery for on-the-ground verification. By leveraging machine learning and artificial intelligence, the project aims to detect biotic and abiotic stress factors in crops at the earliest stages, enabling timely interventions and reducing potential crop loss. This innovative approach marks a significant leap forward in precision agriculture, offering a scalable solution for real-time disease monitoring and management.
This research provides a comprehensive and scalable solution for early disease detection in agriculture, enhancing crop monitoring with a multi-tiered approach. The integration of advanced computer vision and AI techniques allows for precise identification of stress factors, enabling timely interventions that can significantly reduce crop loss and boost productivity. This advancement in precision agriculture ensures real-time, accurate disease management across diverse agricultural environments, ultimately supporting sustainable farming practices and improved yields.
Accurate early disease detection.
Adaptable to various agricultural environments.
Timely interventions reduce crop loss.
Combines drone, satellite, and mobile imagery.
