Detection of Amateur Drones Using Machine Learning

Skibidi vibes in the air as drones buzz like goons, lowkey invading our space. This paper dives deep into the dank realm of acoustic signals, where the edge of machine learning meets independent component analysis. Imagine a toilet where every sound is classified—birds, planes, storms, and those sneaky UAVs. The sigma of detection is crucial for security, safeguarding human life and infrastructure. With features like MFCC and PSD, we unravel the chaos of sound, ensuring that amateurs do not disrupt the flow. Let us ship this tech to the forefront of safety.