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AirSense: AI-Powered Allergy Forecast & Recommendation App

Django CI

Developed for Hackathon Craiova 2025 by Team Cloud (Alin Radu Andrei Moisă, Andrei Șugubete, Mihail Popescu)

Know Before You Go: Your Personal AI Allergy Assistant

AirSense is an intelligent web application designed to help you proactively manage your allergies. By combining real-time weather forecasts, local pollen data, and AI-powered analysis of your symptoms, AirSense provides personalized recommendations and smart alerts to help you navigate your day with confidence.

Core Features

  • Local Forecasts: Automatically get weather and pollen data for your current location, or search for any city worldwide.
  • AI-Powered Insights: Describe how you're feeling in your own words. Our sentiment analysis model understands your input to tailor its advice.
  • Dynamic Risk Analysis: Select your specific allergens and instantly see a calculated risk level (Low, Medium, High) for today and tomorrow.
  • Personalized Recommendations: Receive actionable advice based on the unique combination of your symptoms, local pollen counts, and weather conditions.
  • Smart Alert System: Get categorized alerts (e.g., Critical, High Risk, Proactive) with clear, immediate tips to help you take action.
  • Interactive Data Visualization: View beautiful charts of weather and pollen forecasts, powered by Chart.js.
  • Interaction History: Keep track of your symptoms and our recommendations over time in a clear, card-based history log.
  • Automated Notifications: Opt-in to receive proactive pollen alerts via Email, Webhook, or Telegram before your day even starts.
  • Secure & Private: Full user authentication, profile management, and GDPR compliance to ensure your data is safe and you are in control.

Demo - Youtube Demo


Weather Forecast
Pollen Forecast
Recommendations

History
Set Notifications
Delete Important Information

Getting Started

Follow these instructions to get a local copy of AirSense up and running for development and testing purposes.

Prerequisites

  • Python 3.9+
  • Pip (Python Package Installer)
  • Git

Installation & Setup

  1. Clone the repository: 
    git clone [https://github.com/your-username/airsense.git](https://github.com/your-username/airsense.git)
cd airsense
  2. Create and activate a virtual environment:
    • Windows: 
      python -m venv venv
.\venv\Scripts\activate
    • macOS / Linux: 
      python3 -m venv venv
source venv/bin/activate
  3. Install the dependencies: 
    pip install -r requirements.txt
  4. Apply database migrations: 
    python manage.py migrate
  5. Run the development server: 
    python manage.py runserver
    The application will be available at http://127.0.0.1:8000/.

Setting Up Automated Notifications

To enable proactive alerts, you need to schedule a command to run periodically. This is done using Cron on Linux/macOS or Task Scheduler on Windows.

The command you need to schedule is:

python manage.py send_notifications

On Linux / macOS (using Cron)

  1. Open your terminal and edit the crontab file by running:

    crontab -e

  2. Add a new line to the file to schedule the task. For example, to run the command every day at 7:00 AM, add the following line. Remember to replace the placeholder paths with the absolute paths to your project's python executable and manage.py file.

    # Example: Run daily at 7:00 AM
0 7 * * * /path/to/your/project/airsense/venv/bin/python /path/to/your/project/airsense/manage.py send_notifications

  3. Save the file and exit the editor. Cron will now automatically run the command at the scheduled time.

On Windows (using Task Scheduler)

  1. Open the Task Scheduler from the Start Menu.
  2. In the right-hand "Actions" pane, click Create Basic Task....
  3. Name and Description: Give the task a name like "AirSense Daily Notifications" and click Next.
  4. Trigger: Choose how often you want the notifications to be sent (e.g., Daily) and click Next. Specify a start time, like 7:00:00 AM.
  5. Action: Select Start a program and click Next.
  6. Configure Program/Script:
    • In the "Program/script" field, browse to and select the python.exe interpreter inside your project's virtual environment. For example: C:\Users\YourUser\projects\airsense\venv\Scripts\python.exe
    • In the "Add arguments (optional)" field, enter the full path to your manage.py file followed by the command name. For example: C:\Users\YourUser\projects\airsense\manage.py send_notifications
  7. Click Next, review the summary, and click Finish. The task is now scheduled.

How It Works

The application follows a simple yet powerful workflow to deliver its recommendations:

  1. User Input: The user describes how they are feeling and selects the pollens they are allergic to.
  2. Data Collection: The backend fetches the user's location, a 7-day weather forecast, and a 7-day pollen forecast from the Open-Meteo and Air-Quality APIs.
  3. AI Analysis:
    • A Hugging Face sentiment analysis model (distilbert-base-uncased-finetuned-sst-2-english) determines if the user's feeling is 'POSITIVE' or 'NEGATIVE'.
    • Our custom logic combines this sentiment with pollen and weather data to calculate risk, generate recommendations, and assign an alert level.
  4. Response & Storage: The analysis is sent to the user's browser. If logged in, the entire interaction is saved to their private history for future reference.

Technologies Used

Category Technology / Service
Backend Python, Django
Frontend HTML5, CSS3, JavaScript, Chart.js
AI / ML Hugging Face Transformers (distilbert-base-uncased-finetuned-sst-2-english)
APIs Open-Meteo (Weather & Air-Quality), ip-api.com (Geolocation)
Database SQLite (default), PostgreSQL (production-ready)

Contributing

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

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".

  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

Don't forget to give the project a star! Thanks again!

License

Distributed under the MIT License. See LICENSE for more information.