US 11,908,186 B2
Systems and methods for optimizing asset maintenance protocols by predicting vegetation-driven outages
Liangliang Zhang, Houston, TX (US); Alfonso Encinas Fernandez, New York, NY (US); Charlie Gascon, New York, NY (US); Derek Chu, Maynard, MA (US); Kelsey Elwood Carter, New York, NY (US); and Nicolas Charles Michel Bellemans, Brussels (BE)
Assigned to MCKINSEY & COMPANY, INC., New York, NY (US)
Filed by MCKINSEY & COMPANY, INC., New York, NY (US)
Filed on Mar. 15, 2023, as Appl. No. 18/184,619.
Claims priority of provisional application 63/320,180, filed on Mar. 15, 2022.
Prior Publication US 2023/0298343 A1, Sep. 21, 2023
Int. Cl. G06V 20/10 (2022.01)
CPC G06V 20/188 (2022.01) [G06V 20/182 (2022.01); G06V 2201/12 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A method for optimizing asset maintenance protocols by predicting vegetation-driven outages, the method comprising:
determining, by one or more processors, a failure probability for each asset in a set of assets within a designated area based on a vegetation coverage value and a vegetation density value determined from a 3D image of the designated area to predict a vegetation-driven outage;
defining, by the one or more processors, an asset risk for each asset in the set of assets based on the failure probability;
clustering, by the one or more processors, vegetation within the designated area based on the asset risk for each asset in the set of assets; and
optimizing, by the one or more processors, a set of asset maintenance protocols corresponding to the set of assets based on the clustered vegetation.