Hey everyone! I’m a computer engineering undergrad working on an open source initiative to support a laboratory at my university that analyzes soil samples — kinda like a blood test for the earth ![]()
Their current workflow relies heavily on Excel spreadsheets and manual processing, so I’m building a Python-based system to:
- Automate the generation of readable soil reports for farmers (using equations and thresholds)
- Apply AI for smart recommendations like fertilizer needs or soil correction (future goal)
Right now, I’m still a beginner in the AI world — I’ve learned Perceptrons, Adaline, MLPs, and I’m hungry to go deeper. Any thoughts on:
- ML models that could fit this use case?
- How to approach feature engineering with soil data?
- Cool tools or examples of similar AI-for-agriculture projects?
This is 100% open-source and intended to help a real-world lab team. I’d love to hear your ideas, questions, or anything you think could help me shape this better ![]()
I’m starting fresh and here is my github repository for this initiative.
Thanks in advance!