PlantHealth App

Intelligent monitoring and control system for plantations, combining IoT sensors, computer vision and mobile application.

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Overview

PlantHealth is a full-stack solution for smart plantation monitoring. The system collects real-time environmental data through physical sensors, uses computer vision to identify plant health status, and delivers actionable insights through a Flutter mobile application — all integrated with a local weather API for context-aware recommendations.

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Features

• Real-time monitoring of temperature, humidity and luminosity
• Computer vision with Raspberry Pi 4 for automated detection of healthy and diseased plants
• Automated irrigation via water pump triggered by sensor thresholds
• Local weather API integration for climate-aware recommendations
• Clean and responsive Flutter mobile interface
• Modular architecture separating core logic, features, services and UI

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System Architecture

┌─────────────────────────────────────────┐
│            Flutter Mobile App           │
│         (Dart · Feature-First)          │
└───────────────────┬─────────────────────┘
                    │
          REST / Serial Communication
                    │
     ┌──────────────┴──────────────┐
     │                             │
┌────▼─────┐               ┌──────▼──────┐
│Raspberry │               │ Arduino     │
│  Pi 4    │               │   MEGA      │
│          │               │             │
│ Computer │               │ Sensors:    │
│ Vision   │               │ · Temp      │
│ (C++)    │               │ · Humidity  │
└──────────┘               │ · Light     │
                           │ · Water pump│
                           └─────────────┘
                                  │
                         ┌────────▼────────┐
                         │  Weather API    │
                         │ (Local Climate) │
                         └─────────────────┘

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Project Structure

lib/
├── core/           # Dependency injection, shared configs
├── features/       # Feature-first modules (monitoring, alerts, recommendations)
├── models/         # Data models and entities
├── screens/        # Application screens
├── services/       # External integrations (API, serial communication)
├── widgets/        # Reusable UI components
├── injection_container.dart
└── main.dart

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Tech Stack

Layer	Technology
Mobile App	Flutter / Dart
Computer Vision	C++ (Raspberry Pi 4)
Microcontroller	Arduino MEGA (C++)
Sensors	Temperature · Humidity · Luminosity
Actuators	Mini water pump
External API	Local weather service

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Hardware Requirements

• Raspberry Pi 4 — computer vision processing
• Arduino MEGA — sensor data acquisition and pump control
• DHT sensor — temperature and humidity
• LDR sensor — luminosity
• Mini water pump — automated irrigation
• Camera module — plant health imaging

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Getting Started

Mobile App

# Clone the repository
git clone https://github.com/KodexBase/PlantHealth_App.git

# Install dependencies
flutter pub get

# Run the application
flutter run

Arduino

Upload the firmware located in the /arduino directory to your Arduino MEGA using the Arduino IDE.

Raspberry Pi

# Install dependencies
pip install -r requirements.txt

# Run the vision module
python3 vision/main.py

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Status

Module	Status
Mobile App (Flutter)	✅ Ready for physical testing
Computer Vision (Raspberry Pi)	🔄 In development
Arduino firmware	✅ Complete
Weather API integration	✅ Complete

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Developed by

Kodex Base — Full Stack Development
kodexbase.com · Instagram · kodexbase@gmail.com