US 11,942,207 B2
Artificial intelligence methods and systems for generating zoological instruction sets from biological extractions
Kenneth Neumann, Lakewood, CO (US)
Assigned to KPN Innovations, LLC, Lakewood, CO (US)
Filed by KPN Innovations, LLC, Lakewood, CO (US)
Filed on Mar. 20, 2020, as Appl. No. 16/825,248.
Prior Publication US 2021/0295951 A1, Sep. 23, 2021
Int. Cl. G16H 20/60 (2018.01); B01D 11/02 (2006.01); G06F 18/24 (2023.01); G06N 20/00 (2019.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 20/69 (2022.01); G16B 40/00 (2019.01)
CPC G16H 20/60 (2018.01) [G06F 18/24 (2023.01); G06N 20/00 (2019.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 20/698 (2022.01); G16B 40/00 (2019.02); B01D 11/0207 (2013.01)] 16 Claims
OG exemplary drawing
 
9. An artificial intelligence method of generating zoological instruction sets from biological extractions, the method comprising:
retrieving, by a computing device, a biological extraction pertaining to an animal;
generating, by the computing device, a zoological classifier wherein the zoological classifier utilizes the biological extraction as an input and outputs a zoological profile;
receiving, by the computing device, a zoological input from a remote device wherein the zoological input identifies a zoological habit;
selecting, by the computing device, a zoological machine-learning model of a plurality of zoological machine-learning models utilizing the zoological input and the zoological profile, wherein:
the zoological machine-learning model comprises a supervised machine learning model;
the zoological machine-learning model utilizes the zoological input and the zoological profile as inputs and outputs a correlated zoological instruction set; and
selecting the zoological machine-learning model comprises:
generating an input classifier;
training the input classifier using input classifier training data comprising a plurality of zoological input data and a plurality of zoological profile data correlated to a plurality of corresponding zoological machine-learning model data;
classifying the zoological input to the zoological machine-learning model of the plurality of zoological machine-learning model using the trained input classifier; and
selecting the zoological machine-learning model from the plurality of zoological machine-learning models using the trained input classifier and the classification;
training, by the computing device, the selected zoological machine-learning model using zoological machine-learning model training data comprising a plurality of zoological input data set and a plurality of zoological profile data set correlated to a plurality of zoological instruction sets;
outputting, by the computing device, a zoological instruction set utilizing the trained selected zoological machine-learning model;
receiving, by the computing device, an instruction set input from a remote device;
comparing, by the computing device, the instruction set input and the zoological instruction set; and
updating, by the computing device, the zoological instruction set as a function of the comparison utilizing the trained selected zoological machine learning model.