Weather Forecasting Project

Made by Masa Aladwan and Mohammad Moataz

Overview

This project aims to provide accurate weather forecasting for various cities in Jordan. The project comprises data collection, model building, data visualization using Power BI, and a web interface for user interaction. Additionally, it integrates real-time data streaming from sensors for live updates.

Project Components

1. Data Collection

• Source: Meteostat API
• Parameters Collected: Temperature (temp), Pressure (pres), Wind Direction (wdir), Wind Speed (wspd), Date and Time (datetime)
• Technology Used: Python

2. Data Processing and Model Building

• Cities Covered: Various cities in Jordan
• Models Developed:
  • Temperature Prediction Model
  • Pressure Prediction Model
  • Wind Direction Prediction Model
  • Wind Speed Prediction Model
• Input: City and Date
• Output: Predicted values for Temperature, Pressure, Wind Direction, and Wind Speed
• Libraries Used:
  • scikit-learn for building machine learning models
  • pandas for data manipulation

3. Web Interface

• Framework: FastAPI
• Features:
  • User form to input City and Date
  • Display forecasted weather values
  • Two main buttons:
    1. Dashboard: Redirects to the Power BI dashboard displaying historical and forecasted data
    2. Real-Time Data Streaming: Displays real-time data from sensors

4. Data Visualization

• Tool Used: Power BI
• Features:
  • Interactive dashboard
  • Date range selection from 1999 to 2023
  • City-specific weather data visualization

5. Real-Time Data Integration

• Sensors Used:
  • Ultrasonic Sensor HC-SR04
  • DHT11 Humidity & Temperature Sensor
• Technology Stack:
  • Node-RED: For data collection and processing from sensors
  • Power BI: For real-time data visualization
• Functionality:
  • Node-RED collects data from sensors
  • Processes data and feeds it into the pipeline
  • Sends processed data to Power BI for real-time dashboard updates

Installation

1. Clone the repository:

   git clone https://github.com/MohammadMoataz2/WeatherForecasting.git

2. Install dependencies:

   pip install -r requirements.txt

Usage

1. Run the application:

   • main.html
   • main.py --> python -m uvicorn main:app --reload

2. Input your information to predict the Weather.