US RE50,484 E1
System and method for managing water
Kristin Lavigne, Lincoln, MA (US); David Murr, Minneapolis, MN (US); Lars P. Dyrud, Crownsville, MD (US); Jonathan T. Fentzke, Arlington, VA (US); Indra Epple, Somerville, MA (US); and Shadrian Strong, Catonsville, MD (US)
Assigned to Eagle View Technologies, Inc., Rochester, NY (US)
Filed by Eagle View Technologies, Inc., Rochester, NY (US)
Filed on Aug. 16, 2018, as Appl. No. 15/998,604.
Application 15/998,604 is a reissue of application No. 14/696,867, filed on Apr. 27, 2015, granted, now 9,418,290, issued on Aug. 16, 2016.
Claims priority of provisional application 62/091,040, filed on Dec. 12, 2014.
Int. Cl. G06K 9/00 (2022.01); G06F 18/241 (2023.01); G06F 18/243 (2023.01); G06K 9/46 (2006.01); G06K 9/62 (2022.01); G06V 20/10 (2022.01); G06Q 50/26 (2012.01)
CPC G06V 20/188 (2022.01) [G06F 18/241 (2023.01); G06F 18/24323 (2023.01); G06Q 50/26 (2013.01)] 27 Claims
OG exemplary drawing
 
1. A device comprising [ at least one non-transitory computer-readable media storing a set of instructions for running on a computer system, that when executed cause the computer system to] :
an image data receiving component operable to receive multiband image data [ of an image ] of a geographic region;
a vegetation index generation component operable to generate a normalized difference vegetation index based on the received multiband image data [ of the image] ;
a grey level co-occurrence matrix generation component operable to generate a grey level co-occurrence matrix image band based on the received multiband image data [ of the image] ;
a first classification component operable generate a first land cover classification based on the received multiband image data [ of the image] , the normalized difference vegetation index and the grey level co-occurrence matrix image band;
a second classification component operable generate a second land cover classification based on the received multiband image data [ of the image] , the normalized difference vegetation index and the grey level co-occurrence matrix image band;
a third classification component operable generate a third land cover classification based on the received multiband image data [ of the image] , the normalized difference vegetation index and the grey level co-occurrence matrix image band; and
a voting component operable to generate a final land cover classification based [ on ] a majority vote of the first land cover classification, the second land cover classification and the third land cover classification [ ;
generate a model based on the final land cover classification of the geographic region, by:
extrapolating a first predicted water usage forecast for the geographic region based at least on the final land cover classification of the geographic region, a water budget, and a difference of an amount of water between the water budget and one or more water meter readings of the geographic region;
iteratively extrapolating a second predicted water usage forecast for the geographic region based at least on the final land cover classification, the water budget, and a difference of an amount of water between the water budget and one or more current water readings for the geographic region; and
deriving a relationship between the final land cover classification and water use, without using the water budget; and
predict a third predicted water usage forecast based on the generated model] .