Users upload satellite or drone-style field images for analysis.
project/03Final Year Project / 2025
Crop Yield AI
An AI platform for land suitability and crop yield assessment.
RoleEnd-to-End Development
StackPython, Flask, Supabase, JavaScript
readme / overview
Flask, Supabase, image processing, machine learning, and dashboard workflows.
Built in 2025, Crop Yield AI analyzes satellite or drone imagery to support land suitability review and crop yield estimation through a Supabase-supported dashboard.
- Year
- 2025
- Technology
- Python, Flask, Supabase, HTML, CSS, JavaScript, OpenCV, scikit-learn
01
02
contribution / build notes
What I worked on
Built the upload, analysis, prediction, result display, and dashboard flow.
Structured the project around image processing, model integration, and backend storage.
Prepared a portfolio-safe preview that avoids exposing private keys or heavy model files.
system / workflow
How it works
The system extracts vegetation and colour features from the image.
Supabase supports the project data flow without exposing private keys.
artifacts / links
Project resources
Crop Yield Brochure
Open the brochure from an external link and download a copy if needed.
Crop Yield Poster
Open the poster from an external link and download a copy if needed.
more work in the index
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