Amazon Quells Drone Noise with Anti-Noise

Phase cancellation is an interesting acoustic phenomenon. If two identical signals are 180 degrees out of phase, they will completely cancel each other out. With the eventual proliferation of delivery drones, noise will be an issue. As Amazon puts it, “the net effect of the noises generated by the unmanned aerial vehicle may be annoying at best, or deafening at worst.”


Behold: the Silent Drone. Amazon has presented a patent application “directed to actively abating airborne noise, including but not limited to noise generated by aerial vehicles during in-flight operations.” This is not an easy task. It involves sophisticated machine learning, a speaker mounted on a drone, and collecting a brochette of data that can be reused in similar environments. “For example, because environmental conditions in Vancouver, British Columbia, and in London, England, are known to be generally similar to one another, information or data gathered regarding the acoustic energies generated or encountered by aerial vehicles operating in the Vancouver area may be used to predict acoustic energies that may be generated or encountered by aerial vehicles operating in the London area, or to generate anti-noise signals to be emitted by aerial vehicles operating in the London area.”


Amazon’s disclosure is tremendously complex, and we get the impression that they have ran tests with reportable data. A central station gleans information relayed by the drone and predicts anti-noises. “Once such noises are predicted, anti-noises, or sounds having substantially identical intensities or pressure levels and frequencies that are wholly out-of-phase with the predicted noises (e.g., having polarities that are reversed with respect to polarities of the predicted noises), may be determined, and subsequently emitted from the aerial vehicle during operations. When the anti-noises are emitted from one or more sources provided on the aerial vehicle, such anti-noises effectively cancel the effects of some or all of the predicted noises, thereby reducing or eliminating the sounds heard by humans or other animals within a vicinity of the aerial vehicle.”


There is an AI aspect to this method: “After the machine learning system 170 has been trained, and the sound model f has been developed, the machine learning system 170 may be provided with a set of extrinsic or intrinsic information or data (e.g., environmental conditions, operational characteristics, or positions) that may be anticipated in an environment in which an aerial vehicle is expected to operate.”


All drones will be equipped with a speaker. “[W]here noise is anticipated at a given intensity and frequency, anti-noise of the same or a similar intensity may be emitted at the frequency, 180 degrees out-of-phase or of reverse polarity, from not only a traditional audio speaker but also from other devices such as piezoelectric components that are configured to vibrate at given resonant frequencies upon being energized or excited by an electric source.”


No word on battery life or whether the drone can blare Kenny G in flight as it delivers his latest album.


Claim 1 is bold and broad:

  1. An unmanned aerial vehicle (UAV) comprising:
  • a frame;
  • a Global Positioning System (GPS) sensor associated with the frame;
  • a plurality of motors mounted to the frame;
  • a plurality of propellers, wherein each of the plurality of propellers is coupled to one of the plurality of motors;
  • a sound emitting device mounted to at least one of the frame or one of the plurality of motors;
  • and a computing device having a memory and one or more computer processors, wherein the one or more computer processors are configured to at least:
  • determine, by the GPS sensor, a position of the UAV;
  • determine at least one environmental condition associated with the position;
  • determine at least one operating characteristic of at least one of the plurality of motors or at least one of the plurality of propellers associated with the position;
  • determine a sound pressure level of an anti-noise and a frequency of the anti-noise based at least in part on at least one of the position, the at least one environmental condition, or the at least one operating characteristic;
  • and emit the anti-noise from the sound emitting device of the UAV.