AgriHub
An earlier agricultural platform prototype.
Problem and contribution
AgriHub explored a common interface for connecting farmers and buyers, finding farming information, and using image and language tools for crop-related questions. I contributed to the team’s agricultural platform work. The historical portfolio documents the project and its interface screenshots.
Approach and implementation
The recorded approach combines a marketplace and dashboard with QuickFarm chatbot interactions, crop-image analysis, and agricultural information. The historical stack names Python, PyTorch, SQL, YOLOv8, and language-model components including TinyLlama, Llama-2-7B, and Phi-3-mini.
The project describes image-based leaf disease detection, fruit counting, and crop classification alongside language-based information access. These components have different data and evaluation requirements. Their appearance in the platform account does not establish agronomic accuracy or effectiveness in the field.
Evidence and boundaries
The archived study contains four interface screenshots and a source-code link. It lists future work including database optimization, agricultural model training, frontend development, and expanded language support.
Planned features are not treated as completed deployments. No adoption, yield improvement, or marketplace impact is claimed. Detailed individual ownership beyond the documented team contribution is not asserted.