PROJECT TOPICComputer Vision & Embedded AI
Real-time Crop Phenotyping Rig
An agricultural vision research concept exploring calibrated multi-spectral imaging, 3D point cloud plant reconstruction, and automated vegetation indexing across experimental greenhouse seedling trays.
Digital Agricultural Phenomics & Health Tracking
- ✓Combines near-infrared (NIR) and RGB bands to compute normalized difference vegetation indices (NDVI).
- ✓Generates 3D surface point clouds to estimate total vegetative canopy volume over time.
- ✓Automates longitudinal growth tracking for seed breeding and fertilizer research.
The Engineering Challenge
Problem / Objective
Manual plant phenotyping requires destructive leaf clipping and slow physical calipers that damage experimental specimens.
Conceptual Signal Flow
System Concept
Multispectral Sensors → 3-Axis Greenhouse Gantry → Point Cloud Canopy Analysis → Plant Health Metrics.
Architecture Modules
1Greenhouse Overhead Gantry Stage
2Multispectral Camera Payload
3Automated Calibration Panel
4Phenomics Analysis Database
Hardware Categories
Multispectral CameraWhite Reference PanelCartesian Motion RailsEdge PC
Technologies & Software
Multispectral ImagingNDVI Analysis3D ReconstructionAgri-TechPlantCV / OpenCV PipelinesNDVI Calculation Algorithm
Engineering Considerations & Edge Cases
- Varying solar lighting intensity across greenhouse glass throughout the day
- Color calibration drift over multi-month growth studies
Applications
Greenhouse seed research
Drought resistance benchmarking
Vertical farm growth optimization
Engineering Inquiry & Collaboration
Interested in Developing this Architecture?
Connect directly with Tamizh Tech engineers in Coimbatore to discuss mechanical fabrication, sensor selection, firmware implementation, or turnkey system commissioning.