Weather Monitoring and Prediction System

This project is a Raspberry Pi-based weather monitoring system that uses a DHT11 temperature and humidity sensor to collect environmental data and predict future temperature values using a machine learning model.

Features

• Real-time temperature and humidity monitoring using DHT11 sensor
• Temperature prediction using LSTM (Long Short-Term Memory) neural network
• Modern, responsive web interface with analog clock display
• RESTful API for sensor data retrieval

Hardware Requirements

• Raspberry Pi (any model with GPIO pins)
• DHT11 temperature and humidity sensor
• Connection wires

Software Requirements

• Python 3.6+
• Flask
• TensorFlow
• NumPy
• Adafruit DHT library
• scikit-learn

Installation

1. Clone this repository to your Raspberry Pi:

   git clone https://github.com/Harshit-Patel01/Weather-Prediction.git
   cd Weather-Prediction
   

2. Install the required Python dependencies:

   pip install -r requirements.txt
   

3. Connect the DHT11 sensor to your Raspberry Pi:

   • Connect the sensor's VCC pin to 3.3V or 5V on the Raspberry Pi
   • Connect the sensor's GND pin to GND on the Raspberry Pi
   • Connect the sensor's DATA pin to GPIO4 (Pin 7) on the Raspberry Pi

Usage

1. Start the application:

   python app.py
   

2. Open a web browser and navigate to:

   http://<raspberry-pi-ip-address>:5000
   

How it Works

• The system reads temperature and humidity data from the DHT11 sensor
• The collected data is processed and served via a Flask web application
• A pre-trained LSTM model (temperature_lstm_model.h5) is used to predict future temperature values
• The web interface displays current readings, predicted temperatures, and includes an analog clock

API Endpoints

• GET /sensor-data: Returns the current temperature, humidity, and predicted temperature in JSON format

Files Description

• app.py: Main Flask application that serves the web interface and API
• temperature_lstm_model.h5: Pre-trained TensorFlow model for temperature prediction
• index.html: Main web interface
• style.css: Styling for the web interface
• script.js: JavaScript for the web interface functionality
• Various SVG files: Graphics for the web interface