Siren Detector - Smart Traffic Management System

Welcome to the Siren Detector project, a part of the Smart Traffic Management System! This project utilizes TensorFlow and Keras to detect siren sounds of emergency vehicles.

Getting Started

Follow the steps below to set up and use the Siren Detector:

Prerequisites

• Python 3.x
• TensorFlow
• Keras

Installing Dependencies

Install TensorFlow and Keras using the following commands:

pip install tensorflow
pip install keras

Training Your AI Model To train your own AI model for siren detection, run:

python trainer.py

This will initiate the training process using the Adam optimizer and binary cross entropy for loss calculation.

Testing the Model

To test the trained model on sample siren sounds, run:

python livetester.py

This will evaluate the performance of the model on test data.

Using the Siren Detector

Once the model is trained and tested, you can use it to detect siren sounds in real-time. Implement the detector in your Smart Traffic Management System for efficient handling of emergency vehicles.

Contributing

Contributions are welcome! If you have improvements or new features to suggest, please open an issue or create a pull request.

Happy coding and safe traffic management!