The PlantPatrol project is an innovative initiative by a group of dedicated students from the Catholic University of Eastern Africa.
# AI-Driven Plant Disease Detection System
## Group Information
- **Group Name:** Leaf PlantPatrol
- **Supervisor:** Dr. Stanley Mwangi Chege, PhD (Email: stanley.mwangichege@gmail.com)
- **Group Members:**
- Isaac Ngugi (Group Lead: itsngugiisaackinyanjui@gmail.com)
- Naftali Koome
- Serena Waithera
- Wangeci Njiru
- Mark Wema
- **Group Slogan:** Your Plants, Our Priority
- **Topic:** AI for Climate Change, Agriculture, and Food Security
- **Project Title:** AI-Driven Plant Disease Detection System
## Table of Contents
1. Project Overview
2. Project Understanding
- 2.1 Problem Statement
- 2.2 Stakeholders
3. Installation Instructions
4. Project Structure
5. Dataset Description
- 5.1 Key Features of the Dataset
- 5.2 Target Variable
6. Objectives
- 6.1 Main Objective
- 6.2 Specific Objectives
7. Exploratory Data Analysis (EDA)
8. Modeling Overview
9. Validation Results
10. Model Explainability
11. Validation Strategy
12. Conclusion
- 12.1 Insights
- 12.2 Limitations
- 12.3 Recommendations
- 12.4 Future Work
## 1. Project Overview
The PlantPatrol project is an innovative initiative that leverages artificial intelligence (AI) to address critical issues in agriculture and food security. By creating an AI-driven plant disease detection system, PlantPatrol aims to provide farmers with an accessible, real-time tool for diagnosing plant diseases, thereby enhancing crop health and yield.
## 2. Project Understanding
### 2.1 Problem Statement
Plant diseases pose a significant threat to global food security, resulting in substantial crop losses and adversely affecting farmers, particularly those in developing regions. Traditional detection methods often require expert knowledge, are time-consuming, and are inaccessible to small-scale farmers. This delay exacerbates the spread of diseases and reduces crop yields. The PlantPatrol project proposes an AI-driven plant disease detection system that leverages image recognition technology to offer real-time, accurate disease dia …