Combining AI-powered
analytics with mobile and
drone imagery to protect
crops, ensure food security,
and empower farmers with
early disease detection
technology.
The agricultural sector continues
to face significant challenges due
to crop losses caused by diseases.
Early and accurate detection of
these diseases is critical to
minimizing damage and ensuring
food security. In this context, our
research and development team
has undertaken an extensive
project focused on leaf-level
disease detection in a variety of
crops using a combination of cell
phone imagery, video data, and
multispectral drone imaging.
Our mission is to develop scalable, reliable solutions for early-stage crop disease detection that integrate cutting-edge AI with accessible technology.
Develop scalable methods for early-stage detection of crop diseases using advanced leaf image analysis and machine learning algorithms.
Combine low-cost, widely available tools like smartphones with advanced multispectral drone imaging for comprehensive crop monitoring.
Create comprehensive diagnostic platforms that support farmers, agronomists, and researchers with actionable insights and recommendations.
Our comprehensive approach leverages both ground-level and aerial data sources for unprecedented accuracy in crop health monitoring.
High-resolution images and video clips captured by farmers and field workers in real field conditions, documenting visible symptoms including:
Expert agronomists and plant pathologists verify collected data to ensure accuracy and reliability for training our machine learning models, providing the foundation for robust AI-driven diagnostics.
UAV-equipped multispectral cameras capture wide-area crop field imagery, providing critical plant health insights through specialized spectral bands:
Advanced preprocessing pipeline includes: