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Project Title:
AI-Based Solution for Addressing Plant Diseases in Egypt's Fruit and Vegetable Crops -
Team Number: { 0091 }
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Faculty:
Faculty of Computers and Information – Fayoum Center - EELU -
Supervised by:
- 👨🏫 Dr. Mahmoud Bassiouni (Supervisor)
- 👩💻 Eng. Toka Ashraf (Assistant Supervisor)
| Name | Role | University ID |
|---|---|---|
| Kholoud Mohsen | Team Leader | 21-00882 |
| Farah Mohamed | Member | 21-00686 |
| Bishoy Ezzat | Member | 21-00584 |
| George Hany | Member | 21-00724 |
| Hager Abdelqader | Member | 21-02131 |
| Mariam Hany | Member | 21-01011 |
| Eslam Ayman | Member | 21-01854 |
🎓 Graduation Project
📍 Project Title: AI-Based Solution for Addressing Plant Diseases in Egypt's Fruit and Vegetable Crops
PlantyCare is a smart mobile application developed in Java, aiming to assist Egyptian farmers by diagnosing plant diseases, recommending suitable crops to grow, and suggesting the best fertilizers based on soil and weather data — all powered by AI models.
- Login and Sign-Up pages.
- Connected to Firebase for user data storage and authentication.
- Keeps a record of the user’s activity and predictions.
The Home Page includes 3 main vertically scrollable options:
- Allows users to upload an image from their device or capture a new photo of the plant.
- After submitting the image, the result page displays:
- Predicted disease name
- The submitted image
- A brief description of the disease
- Prevention steps to follow
- Treatment image and description
- All results are saved to Firebase and displayed in a History section at the top of the Home Page. Clicking any image in history redirects the user to its detailed result page.
- Predicts the most suitable crop based on input values:
- N, P, K
- Temperature
- Humidity
- pH
- Rainfall
- Displays the crop name and an image in a popup result window.
- Suggests the best fertilizer based on the following user inputs:
- Crop type
- Soil color
- Nitrogen, Phosphorus, Potassium values
- pH, Rainfall, Temperature
- The recommended fertilizer and its image are shown in a popup.
The app includes a bottom bar with 4 navigation items:
| Section | Description |
|---|---|
| 🏠 Home | Redirects to the main home page |
| 📅 Calendar | Shows the top 5 crops grown and harvested in each month in Egypt |
| 📘 Dictionary | Contains important agricultural terms used in the app, with simple definitions |
| 👤 Profile | Displays user's name, email, join date, and usage statistics for each main feature (AgriCure, PlantPick, FertiGuide) |
- ⚙️ Settings
- ✏️ Edit Profile
- ℹ️ About Us
- ❓ FAQs
- 🔒 Privacy Policy
- 📞 Contact Us
- ⭐ Rate Us
- 📤 Share the App
- AgriCure: CNN model for plant disease classification using image input.
- PlantPick: Crop recommendation model based on soil and environmental factors.
- FertiGuide: Fertilizer suggestion model for optimizing plant nutrition and growth.
- Java (Android development)
- Firebase (Authentication, Realtime Database, Storage)
- AI Models (Trained using deep learning frameworks)
- Clean & User-Friendly UI/UX (Modern mobile design practices)
PlantyCare was developed as part of a graduation project at the Faculty of Computers and Information. The goal is to support Egypt’s agricultural sector by leveraging AI to reduce crop loss, improve decision-making, and increase productivity.
💬 For further assistance or questions, feel free to reach out to the development team through the app.