# US 10,370,093 B1 · On-demand drone noise measurements

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 10,370,093 B1
- Document ID: US10370093B1
- Status: Granted
- Kind: B1
- Application number: 15/353,637
- Filed: 2016-11-16
- Granted: 2019-08-06
- Earliest claimed: 2016-11-16
- Assignees: Amazon Technologies, Inc.
- Applicants: Amazon Technologies, Inc.
- Inventors: Brian C. Beckman; Eric Berlinberg; John Raymond Brodie; Emilia Sorana Buneci
- Web page: https://patentgrep.com/patent/US10370093B1

## CPC

- B64C 27/001: {Vibration damping devices}
- G01S 1/751: {Mounting or deployment thereof}
- G01S 1/753: {Signal details}
- G08G 5/21: located onboard the aircraft
- G08G 5/32: for flight plan preparation
- G08G 5/54: for approach or landing
- G08G 5/55: for a single aircraft
- G08G 5/57: for unmanned aircraft
- G08G 5/80: Anti-collision systems
- B64C 2027/004: {using actuators, e.g. active systems}
- B64U 10/13: Flying platforms
- B64U 50/19: using electrically powered motors
- B64U 2101/30: for imaging, photography or videography
- B64U 2101/60: for transporting passengers; for transporting goods other than weapons
- B64C: AEROPLANES; HELICOPTERS
- G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G08G: TRAFFIC CONTROL SYSTEMS (guiding railway traffic, ensuring the safety of railway traffic B61L; arrangement of road signs or traffic signals E01F9/00; radar or analogous systems, sonar systems, lidar systems specially adapted for traffic control G01S13/91, G01S15/88, G01S17/88; {radar or analogous systems, sonar systems, lidar systems specially adapted for anti-collision purposes G01S13/93, G01S15/93, G01S17/93})
- B64U: UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR

## Abstract

Techniques for calculating a sound received at a plurality of distances from an unmanned aerial vehicle (UAV) may be provided. For example, during delivery, the UAV may be associated with a sensor to obtain first sound information that corresponds to the sound generated by the UAV. A sensor associated with a landing marker may obtain second sound information about the sound generated by the UAV during flight and delivery of a payload to a location associated with the landing marker. In embodiments, the first sound information and the second sound information may be utilized to calculate sound metrics for the sound generated by the UAV and determine the sound received at a plurality of distances from the UAV during flight.

## Claims

### Claim 1

A computer-implemented method, comprising:
receiving, by a computer system, an order to deliver a payload;
generating, by the computer system, a flight plan that instructs an unmanned aerial vehicle (UAV) to deliver the payload to a location based at least in part on information associated with the order;
receiving, by the computer system, first sound information from a first sensor associated with the UAV, the first sensor configured to obtain sound generated by the UAV during flight;
receiving, by the computer system, second sound information from a second sensor associated with a landing marker of the location, the second sensor configured to obtain the sound generated by the UAV during flight, the landing marker utilized to guide the UAV to deliver the payload;
extracting, by the computer system, sound metrics for the sound generated by the UAV based at least in part on the first sound information and the second sound information;
determining, by the computer system, one or more sound pressure levels for a plurality of distances from the UAV based at least in part on the extracted sound metrics, a sound pressure level of the one or more sound pressure levels identifying the sound received at a particular distance from the UAV during flight; and
instructing, by the computer system, the UAV to alter a modulation of an associated set of propellers based at least in part on the one or more sound pressure levels for the plurality of distances thereby altering the sound generated by the UAV.

### Claim 2 (depends on 1)

The computer-implemented method of claim 1, wherein receiving the second sound information is based at least in part on a signal received by the second sensor associated with the landing marker, the signal being provided by the UAV.

### Claim 3 (depends on 1)

The computer-implemented method of claim 1, wherein receiving the first sound information from the first sensor associated with the UAV is based at least in part on a first geographic location for the UAV and a second geographic location for the location.

### Claim 4 (depends on 1)

The computer-implemented method of claim 1, further comprising identifying a component failure of the UAV based at least in part on the first sound information and the second sound information.

### Claim 5 (depends on 1)

The computer-implemented method of claim 1, further comprising:
requesting, by the computer system and from a user device associated with the location, for third sound information obtained by the user device about the sound generated by the UAV; and
updating, by the computer system, the sound metrics for the sound generated by the UAV based at least in part on the third sound information.

### Claim 6 (depends on 1)

The computer-implemented method of claim 1, further comprising:
receiving, by the computer system, environmental input within a certain distance of the UAV, the environmental input obtained by a third sensor associated with the UAV; and
updating, by the computer system, the sound metrics for the sound generated by the UAV based at least in part on the environmental input.

### Claim 7 (depends on 1)

The computer-implemented method of claim 1, wherein the UAV is configured to store the first sound information in a local data store and transmit the first sound information to the computer system upon arriving at an origination location.

### Claim 8

A computer-implemented method, comprising:
generating, by a computer system, a flight plan that instructs a first unmanned aerial vehicle (UAV) to land at a location;
receiving, by the computer system, first sound information from a first sensor associated with the first UAV, the first sensor configured to obtain sound generated by the UAV during flight;
receiving, by the computer system, second sound information from a second sensor associated with a second UAV, the second sound information transmitted by the second UAV to the computer system based at least in part on a certain distance between the first UAV and the second UAV during simultaneous flight of the first UAV and the second UAV;
extracting, by the computer system, sound metrics for the sound generated by the first UAV based at least in part on the first sound information and the second sound information; and
generating, by the computer system, a sound map for the location based at least in part on the extracted sound metrics, the sound map identifying sound parameters comprising transformations of the sound calculated for different distances from the first UAV.

### Claim 9 (depends on 8)

The computer-implemented method of claim 8, wherein the sound metrics for the sound generated by the first UAV comprise one or more of a sound pressure level for the sound, a sound power level for the sound, a decibel level for the sound, a loudness level for the sound, a sharpness level for the sound, a roughness level for the sound, a tonal prominence for the sound, or a fluctuation strength of the sound.

### Claim 10 (depends on 8)

The computer-implemented method of claim 8, wherein the sound map is generated further based at least in part on a machine learning algorithm utilizing the extracted sound metrics.

### Claim 11 (depends on 8)

The computer-implemented method of claim 8, further comprising:
configuring the first UAV to utilize a third sensor for obtaining object detection information; and
updating, by the computer system, the object detection information utilizing the first sound information and the second sound information.

### Claim 12 (depends on 11)

The computer-implemented method of claim 11, wherein the third sensor includes a time of flight sensor.

### Claim 13 (depends on 11)

The computer-implemented method of claim 11, further comprising:
generating, by the computer system, a new flight plan that instructs the first UAV to avoid an object, the object identified using the updated object detection information.

### Claim 14 (depends on 8)

The computer-implemented method of claim 8, further comprising updating, by the computer system, the flight plan for the UAV for subsequent flights to the location, the flight plan updated based at least in part on the generated sound map.

### Claim 15

An unmanned aerial vehicle (UAV), comprising:
a frame;
a set of propellers associated with a propulsion system associated with the frame, the set of propellers configured to provide propulsion for the UAV;
a first sound sensor configured to obtain sound generated by the UAV during flight; and
a computing system configured to manage the propulsion system during a flight associated with a transfer of a payload and further configured to:
obtain, by the first sound sensor, first sound information about the sound generated by the UAV;
receive, from a second sound sensor associated with a landing marker in a first position of a location for the UAV, second sound information;
extract sound metrics for the sound generated by the UAV based at least in part on the first information and the second information; and
transmit, to a user device, instructions for moving the landing marker to a second position of the location based at least in part on the extracted sound metrics.

### Claim 16 (depends on 15)

The UAV of claim 15, wherein the computing system is further configured to maintain information that identifies a particular sound level for the location.

### Claim 17 (depends on 16)

The UAV of claim 16, wherein the computing system is further configured to alter modulation of the set of propellers based at least in part on the extracted sound metrics and the information thereby altering the sound made by the UAV.

### Claim 18 (depends on 15)

The UAV of claim 15, wherein the computing system is further configured to generate a sound map for the location based at least in part on the extracted sound metrics for the sound, the sound map identifying sound parameters comprising transformations of the sound calculated for different distances from the UAV.

### Claim 19 (depends on 18)

The UAV of claim 18, wherein the instructions for moving the landing marker to a second position of the location is based at least in part on the generated sound map.

### Claim 20 (depends on 19)

The UAV of claim 19, wherein the computing system is further configured to generate a flight plan for subsequent flights to the location based at least in part on the generated sound map.