Agriculture Portal

• Agriculture Portal is a machine learning-based project designed to provide predictions and recommendations for farmers. The system uses different algorithms to predict crops, recommend fertilizers, and provide rainfall and yield predictions to help farmers make informed decisions about their crops.
• IT also has direct crop sales to customer with real payment interface using Stripe API.
• Other supporting features are Chatbot using OPENAI's gpt-3.5-turbo model, Weather Forecast upto 4 days using Weather API, Agriculture realetd news using News API.

Pre Requisites

Get Below API Keys

• News API
• OpenWeatherMap API
• Stripe API
• OpenAI API

Gmail SMTP Setup

1. Setup app password for gmail
2. Open fsend_otp.php and csend_otp.php files and change username and password.

function smtp_mailer($to,$subject, $msg){
	require_once("../smtp/class.phpmailer.php");
	$mail = new PHPMailer(); 
	$mail->IsSMTP(); 
	$mail->SMTPDebug = 0; 
	$mail->SMTPAuth = TRUE; 
	$mail->SMTPSecure = 'ssl'; 
	$mail->Host = "smtp.gmail.com";
	$mail->Port = 465; 
	$mail->IsHTML(true);
	$mail->CharSet = 'UTF-8';
	$mail->Username = "username@gmail.com";    // Change it to yours email address
        $mail->Password = "password"; 	           // App Password, (16 character Key)
        $mail->SetFrom("username@gmail.com");   
	$mail->Subject = $subject;
	$mail->Body =$msg;
	$mail->AddAddress($to);
	if(!$mail->Send()){
		return 0;
	}else{
		return 1;
	}
}

Installation

1. Clone the repository to your local machine.

git clone https://github.com/Nandha2536/agriculture-portal.git

2. Goto Farmers folder and Install the required packages using pip.

pip install -r requirements.txt

3. Change Success Url and Cancel Url file paths in customer/cbuy_crops.php.

$session = \Stripe\Checkout\Session::create([
'payment_method_types' => ['card'],
	'line_items' => [[
	'price_data' => [
		'product' => 'prod_NdAYaoDLX3DnMY',
		'unit_amount' => $TotalCartPrice,
		'currency' => 'inr',
		],
		'quantity' => 1,
		]],
	'mode' => 'payment',
	'success_url' => 'http://localhost/projects/agri2/customer/cupdatedb.php',   // Change File Path
	'cancel_url' => 'http://localhost/projects/agri2/customer/cbuy_crops.php',   // Change File Path
]);

4. Add API Keys to respective files.

• News API Key to fnewsfeed.php
• OpenWeatherMap API Key to fweather_forecast.php
• Stripe API Key to customer/stripePayment/config.php
• OpenAI API Key to index.php and fchatgpt.php

5. Import database from db folder.
6. Run Apache web server using XAMPP.

Features

• Crop Prediction
• Crop Recommendation
• Fertilizer Recommendation
• Rainfall Prediction
• Yield Prediction
• OTP Verification through mail
• Agriculture realetd news using News API
• Chatbot using OpenAI's gpt-3.5-turbo model
• Dynamically changing quotes using OpenAI's API
• Weather Forecast upto 4 days using OpenWeatherMap API
• Direct crop sales to customer with real time payment interface using Stripe API

Technologies Used

• Python
• PHP
• Pandas
• NumPy
• JavaScript
• HTML/CSS
• Bootstrap4
• Scikit-learn

Dataset

The Crop Management System dataset includes the following features:

Crop Prediction Dataset

• State_Name
• District_Name
• Season
• Crop

Crop Recommendation Dataset

• N
• P
• K
• Temperature
• Humidity
• pH
• Rainfall
• Label

Fertilizer Recommendation Dataset

• Temparature
• Humidity
• Soil Moisture
• Soil Type
• Crop Type
• Nitrogen
• Phosphorous
• Potassium
• Fertilizer Name

Rainfall Prediction Dataset

• SUBDIVISION
• YEAR
• MONTH

Yield Prediction Dataset

• State_Name
• District_Name
• Crop_Year
• Season
• Crop
• Area
• Production

How to Use

• Crop Prediction: Input State_Name, District_Name, and Season to get the predicted crop for that location.
• Crop Recommendation: Input N, P, K, Temperature, Humidity, pH, and Rainfall for that location to get recommended crops for that location.
• Fertilizer Recommendation: Input Temperature, Humidity, Soil Moisture, Soil Type, Crop Type, Nitrogen, Phosphorous, and Potassium to get recommended fertilizer for that crop and location.
• Rainfall Prediction: Input Subdivision and Year to get rainfall prediction for that year.
• Yield Prediction: Input State_Name, District_Name, Crop_Year, Season, Crop, Area, Production to get predicted yields for that crop and location.

License

This project is licensed under the MIT License.