Overview / Usage

This project is intended to detecting birds which are a major cause of airplane disasters. Many airplane accidents have taken place because of birds flying into the engine disabling its function. This model detects any bird near the runways of the airports and sends a warning message. This would help warn the concerned authority about the existence of birds near the runway and the can take necessary actions about it.

Methodology / Approach

Traditionally birds near the airports are recognized manually and thus it involves a lack of accuracy. But if new technologies like bird detection using Machine learning can be used, the accuracy would be more and the process would be more methodical.

Technologies Used

The project is created using haar-cascade classifier. The cascade file is build by training the model over a lot of positive and negative images. The accuracy is a bit low because of the low computation power of my PC but it can be improved to a great extent.

Repository

https://github.com/Souravjyoti/Bird_detection