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:
Apr. 05, 2022

Filed:

Oct. 04, 2018
Applicant:

Jiddu, Inc., Sunnyvale, CA (US);

Inventors:

Miku Jha, Sunnyvale, CA (US);

Amitava Bhaduri, Sunnyvale, CA (US);

Assignee:

Other;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2022.01); G06T 7/00 (2017.01); H04N 5/232 (2006.01); G01N 21/88 (2006.01); G01N 33/02 (2006.01); G06T 5/50 (2006.01); H04N 5/225 (2006.01); H04N 5/247 (2006.01); G06V 20/20 (2022.01); G16Y 10/05 (2020.01); G16Y 10/45 (2020.01); G01N 21/84 (2006.01); G06V 20/68 (2022.01);
U.S. Cl.
CPC ...
G06T 7/0004 (2013.01); G01N 21/8851 (2013.01); G01N 33/025 (2013.01); G06T 5/50 (2013.01); G06V 20/20 (2022.01); H04N 5/2253 (2013.01); H04N 5/2256 (2013.01); H04N 5/23299 (2018.08); H04N 5/247 (2013.01); G01N 2021/8466 (2013.01); G01N 2021/8887 (2013.01); G01N 2201/062 (2013.01); G01N 2201/0634 (2013.01); G06T 2207/20221 (2013.01); G06T 2207/30128 (2013.01); G06V 20/68 (2022.01); G16Y 10/05 (2020.01); G16Y 10/45 (2020.01);
Abstract

An IoT based apparatus to assess the quality of food or agricultural produce is disclosed. The apparatus comprises a frame having an enclosure, a movable tray disposed at a middle portion of the enclosure, one or more camera installed within the enclosure, one or more light source strategically mounted within the enclosure to avoid reflection and hot spots, at least one storage unit, a touch screen display and a single board computer coupled to the camera, light source, storage unit and touch screen display. The enclosure is illuminated by the light source and the camera is configured to capture the image of the produce from both the top and bottom side of the produce. A pre-trained deep learning model is used on both the top and bottom view images to identify defects in the agricultural produce. The identified defects are displayed to the user via the touch screen display.


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