The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 02, 2018

Filed:

Sep. 03, 2016
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Ranveer Chandra, Kirkland, WA (US);

Ashish Kapoor, Kirkland, WA (US);

Sudipta Sinha, Redmond, WA (US);

Deepak Vasisht, Cambridge, MA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06T 3/40 (2006.01); B64C 39/02 (2006.01); G06K 9/62 (2006.01); G06T 3/00 (2006.01); G06T 7/00 (2017.01); A01B 79/00 (2006.01); G01C 11/02 (2006.01);
U.S. Cl.
CPC ...
G06T 3/4038 (2013.01); A01B 79/005 (2013.01); B64C 39/024 (2013.01); G01C 11/025 (2013.01); G06K 9/0063 (2013.01); G06K 9/6215 (2013.01); G06T 3/0068 (2013.01); G06T 3/0093 (2013.01); G06T 7/0028 (2013.01); G06T 7/0034 (2013.01); B64C 2201/127 (2013.01); G06T 2207/10032 (2013.01); G06T 2207/30188 (2013.01); G06T 2207/30192 (2013.01);
Abstract

An apparatus for generating precision maps of an area is disclosed. The apparatus receives sensor data, where the sensor data includes sensor readings each indicating a level of a parameter in one of a plurality of first portions of an area, and video data representing an aerial view of the area. The sensor data may be received from sensors that are each deployed in one of the first portions of the area. The video data may be received from an aerial vehicle. An orthomosaic may be generated from the video data, and the orthomosaic and the sensor data used to generate a predication model. The prediction model may then be used to extrapolate the sensor data to determine a level of the parameter in each of a plurality of second portions of the area. A precision map of the area may be generated using the extrapolated sensor readings.


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