Soil Moisture and Crop Prediction : Using Deep Learning

App to monitor soil moisture using a standard digital image and machine learning technology.
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Table of Contents

1. About The Project
   • Built With
   • About The Project
   • Benefit of the Project
2. Getting Started
   • Prerequisites
   • Installation
3. Roadmap
4. Contributing
5. Contact

About The Project

RPReplay_Final1675287630-3.mp4

• Mobile application which replaces teh traditional hardware sensor to predict moisture content in soil
• The applicaiton works on AI Technology to detect moisture content using soil image along wiht many other helpful recommendations

Benefit of the Project

• Categorising the soil into dry, wet, soaked, regular type based on the moisture content
• Predicting moisture content of the soil
• Recommending plants that can grow on the respective soil type considering the moisture content
• Describing the desired crop features from reliable sources

Built With

• Flutter

Getting Started

To get a local copy up and running follow these simple steps.

Prerequisites

Install flutter

• bash

   git clone https://github.com/flutter/flutter.git -b stable

Installation

1. Clone the repo

   git clone https://github.com/raysummee/soil_moisture.git

2. Install pub plugins

   flutter pub get

3. Run the app

   flutter run

Roadmap

See the open issues for a list of proposed features (and known issues).

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Contact

Angshuman Barpujari - @instagram - raysummee@gmail.com

Project Link: https://github.com/raysummee/soil_moisture