Clickable GIF Map – Pavaman

Revolutionizing

Crop Disease Detection

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.

SND

R&D Objectives

Our mission is to develop scalable, reliable solutions for early-stage crop disease detection that integrate cutting-edge AI with accessible technology.

Smart Crop Monitoring Slides

Reliable Detection

Develop scalable methods for early-stage detection of crop diseases using advanced leaf image analysis and machine learning algorithms.

Reliable Detection

Technology Integration

Combine low-cost, widely available tools like smartphones with advanced multispectral drone imaging for comprehensive crop monitoring.

Technology Integration

Data-Driven Platform

Create comprehensive diagnostic platforms that support farmers, agronomists, and researchers with actionable insights and recommendations.

Data-Driven Platform

Multi-Modal Data Collection

Our comprehensive approach leverages both ground-level and aerial data sources for unprecedented accuracy in crop health monitoring.

RADD

Smartphone Imagery

High-resolution images and video clips captured by farmers and field workers in real field conditions, documenting visible symptoms including:

  • Discoloration patterns
  • Lesion identification
  • Wilting symptoms
  • Fungal growth detection
SBR

Ground Truthing

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.

DN
GSD

Multispectral Drones

UAV-equipped multispectral cameras capture wide-area crop field imagery, providing critical plant health insights through specialized spectral bands:

  • Near-infrared analysis
  • Red edge detection
  • Invisible spectrum monitoring
  • Large-scale field mapping

Advanced preprocessing
 pipeline includes:

  • Noise reduction algorithms
  • Contrast enhancement
  • Leaf area segmentation
  • Feature extraction optimization