Air Quality Data Processing

Welcome to the Air Quality Data Processing project by Team MobDevOne! In this project, we gather and process air quality data, including temperature, humidity, and particle size data. Our goal is to provide valuable insights into the air quality trends in our environment.

Project Overview

The Air Quality Data Processing project involves collecting air quality data from sensors, processing it, and providing users with valuable information about temperature, humidity, and particle sizes in the air. The project has the following main components:

• Data Collection: We fetch air quality data from various sensors using URLs provided by the Sensor.Community archive. This data includes temperature, humidity, and particle size measurements.

• Data Processing: The collected data is processed and stored in a SQLite database. We calculate various statistics such as maximum, minimum, and average values for temperature, humidity, and particle sizes.

• Data Retrieval: Users can input a specific date and choose whether they want to see temperature, humidity, or particle size data. The program retrieves and displays the relevant statistics for that date.

• Automated Data Loading: We've implemented an automated data loading process that checks for new data updates daily and adds them to the database.

Getting Started

1. Clone the repository to your local machine:

   git clone https://github.com/MobDevOne/air-quality-data-processing.git
   

2. Navigate to the project directory:

   cd AirQuality
   

3. Install the required Python packages:

   pip install pandas
   

4. Run the main program:

   python3 air_quality_processing.py
   

5. Follow the on-screen instructions to retrieve air quality data for a specific date.

Technologies Used

• Python: The project is developed using the Python programming language.
• SQLite: We use an SQLite database to store and manage the processed air quality data.
• Pandas: The Pandas library is used for data manipulation and analysis.

Contributing

We welcome contributions from the community to enhance this project. If you'd like to contribute, please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix: git checkout -b feature-name
3. Implement your changes and test thoroughly.
4. Commit your changes: git commit -m "Add feature"
5. Push to your forked repository: git push origin feature-name
6. Create a Pull Request in this repository.

Contact Us

Feel free to reach out if you have any questions or feedback about the project:

• Twitter: @MobDevOne

We're excited to collaborate and improve air quality awareness together!

License

This project is licensed under the MIT License.

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Thank you for your interest in our Air Quality Data Processing project. Let's make the air we breathe healthier!