Date of Award


Degree Type


Degree Name

Master of Science (MS)


Computer Science

First Advisor

Ashwin Ashok

Second Advisor

Anu Bourgeois

Third Advisor

Awad Mussa


The use of drones introduces the problem of noise pollution due to the audio noise generated from its propeller rotations. To mitigate the noise pollution from drone propellers, this thesis explores a method of using active noise cancellation ANC. This thesis hypothesizes that by analyzing the waveform of the drone propeller noise, an approximated wave function can be produced and used as an anti-noise signal that can effectively nullify the drone noise. In order to align the phase of the anti-noise signal to maximize drone noise reduction, this thesis presents a signal pitch-shifting approach, to guide areas of destructive interference to a desired target such as a microphone, at a desired location. Through experimental evaluation using a prototype of the proposed Pitch-Aligned Active Noise Cancellation system PA-ANC, this thesis reveals that the proposed technique can achieve a 43.82% reduction of drone noise.


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