🌿 Agricultural AI Assistant Android App

An Android-based plant disease detection app using AI and Computer Vision. Users can capture or upload plant images to detect diseases, and receive descriptions, causes, treatments, and preventions all available in English, Hindi, and Marathi.

📱 Download

🔗 Download APK from Google Drive

🎓 Academic Information

• 🏫 Final Year Project (2025)
• 🎓 BE Computer Engineering
• 🏢 Gokhale Education Society's R. H. Sapat College of Engineering, Nashik
• 📚 Savitribai Phule Pune University (SPPU)

👨‍💻 Project Contributors

👤 Name	📧 Email	🌐 GitHub Profile
Bhushan Malekar	xectrone@gmail.com
Srushty Borkar	1002borkarsr@gmail.com
Prasen Mhaskar	prasenmhaskar45@gmail.com
Anand Dhomase	dhomaseanand0096@gmail.com

📷 Supported Plants and Diseases

✅ Plants:

Apple, Blueberry, Cherry, Corn, Grape, Orange, Peach, Pepper, Potato, Raspberry, Soybean, Squash, Strawberry, Tomato

🦠 Diseases:

Apple Scab, Black Rot, Cedar Apple Rust, Powdery Mildew, Common Rust, Northern Leaf Blight, Citrus Greening, Bacterial Spot, Early Blight, Late Blight, Leaf Mold, Spider Mites, Target Spot, Tomato Mosaic Virus, and more…

🧠 Features

• 🌱 Plant Disease Detection using HuggingFace ViT (Vision Transformer) via Flask backend
• 📸 Camera and Gallery Support for image upload
• 🧾 Detailed Diagnosis Info: Description, Cause, Treatment, Prevention
• 🗂️ User-specific History Tracking (without storing images)
• 🌐 Multilingual Support (English, Hindi, Marathi)
• 🔐 Login/Signup integration with Flask backend
• ☀️ Always Light Mode UI (disables system dark mode)
• ℹ️ In-App Info Dialog for usage guide

🏗️ Tech Stack

Layer	Technology
UI Framework	Jetpack Compose
Programming Lang.	Kotlin
Local Storage	Room Database
Backend API	Flask (Python)
AI Model	HuggingFace ViT (Vision Transformer)
Language Handling	JSON-based i18n

📂 Project Structure

📦 agricultural_ai_assistant_android/
│
├── MainActivity.kt                  # App entry point
│
├── domain/                          # Reserved for business logic (currently minimal)
│
└── ui/                              # User Interface layer
    ├── home_screen/
    │   ├── DiseaseDetectionApp.kt          # Main screen UI
    │   ├── DiseaseDetectionResponse.kt     # API response model
    │   └── ResponseItems.kt                # Helper data class for JSON items
    │
    └── theme/
        ├── Theme.kt                        # App theme setup
        ├── Color.kt, Fonts.kt, Shape.kt    # Custom theming
        ├── CustomColorPalette.kt           # Custom colors
        ├── CustomShape.kt                  # Rounded UI design
        ├── Dimen.kt, Constants.kt          # App dimensions/constants
        └── Type.kt, Typography.kt          # Fonts and text styles

🎨 Resources (res/)

Folder	Description
drawable/	Icons and camera/upload vector assets
font/	Custom fonts (nunito, rubik, etc.)
values/	Colors, strings, themes, and font configs
values-night/	Overridden night theme (not used in app)
xml/	File path, network config, backups

🚀 How to Build & Run

Prerequisites:

• Android Studio Hedgehog+
• Internet connection (for backend calls)
• Flask backend running (or hosted)

Steps:

1. Clone Repo

   git clone https://github.com/xectrone/agricultural_ai_assistant_android.git

2. Open in Android Studio
   File → Open → Select project folder

3. Edit Flask Backend URL
   Modify the base URL in uploadImageAndDetectDisease() inside DiseaseDetectionApp.kt.

4. Run on Emulator or Physical Device
   Click ▶️ or "Run App"

🌐 Backend Integration

The app communicates with this hosted Flask backend:
🔗 https://agricultural-ai-assistant.onrender.com/

Endpoints used:

• POST /detect → Accepts image, returns prediction
• POST /auth/login & /auth/register → Auth

👉 Backend code available here:
https://github.com/xectrone/agricultural_ai_assistant

📥 Additional Features

• 🧾 Local result display without storing images
• 🌐 Supports UTF-8 language strings (Hindi, Marathi)
• 📖 Info dialog popup to guide first-time users
• ☀️ Locks interface in light theme (ignores system dark mode)

🚀 Deployment

App connects to hosted Flask backend at:

https://agricultural-ai-assistant.onrender.com/

APK available for download from:
🔗 Google Drive APK Link

🚧 Future Improvements

• 🧪 Add offline caching of previous results
• 🗣️ Text-to-speech for diagnosis
• 🌐 Auto language detection from device
• 🖼️ Save result snapshots locally

📄 License

This project is licensed under the MIT License. See the LICENSE file for more details.