AgriHealth AI : Real-time Plant Health Monitoring System
Plant Health Analysis Using Image Processing and Classical Machine Learning
Overview
AgriHealth AI is an academic machine learning project focused on analyzing plant health conditions using image preprocessing techniques and classical classification models. The project explores how data quality, noise reduction, and feature extraction impact model performance in a real-world agricultural context.
Problem
Early detection of plant health issues is challenging for small-scale farmers, and many existing solutions rely on complex or resource-intensive approaches that are difficult to evaluate or deploy effectively.
Solution
I designed a structured experimentation pipeline that preprocesses plant images using multiple denoising techniques and evaluates classical machine learning classifiers to compare accuracy and robustness. The project emphasizes methodological comparison, reproducibility, and practical limitations rather than black-box prediction.