US 12,270,728 B2
Fuel leak determination via predictive modeling
Prem Swaroop, Lexington, MA (US); Atish Kamble, Arlington, MA (US); and Bodhayan Dev, Marlborough, MA (US)
Assigned to Wayne Fueling Systems LLC, Austin, TX (US)
Filed by Wayne Fueling Systems LLC, Austin, TX (US)
Filed on Dec. 20, 2023, as Appl. No. 18/390,398.
Application 18/390,398 is a continuation of application No. 17/027,529, filed on Sep. 21, 2020, granted, now 11,852,563.
Claims priority of provisional application 63/046,345, filed on Jun. 30, 2020.
Prior Publication US 2024/0159615 A1, May 16, 2024
Int. Cl. G01M 3/18 (2006.01); B67D 7/08 (2010.01); G01F 25/10 (2022.01); G06F 3/04842 (2022.01); G06Q 10/04 (2023.01); G06Q 50/18 (2012.01)
CPC G01M 3/186 (2013.01) [B67D 7/085 (2013.01); G01F 25/15 (2022.01); G06F 3/04842 (2013.01); G06Q 10/04 (2013.01); G06Q 50/18 (2013.01); G01F 25/13 (2022.01)] 25 Claims
OG exemplary drawing
 
1. A method comprising:
receiving, from one or more of a plurality of sensors disposed in a fuel storage facility, data characterizing the fuel storage facility;
determining, by a server and based on the received data, a predicted fuel leakage rate for the fuel storage facility, the determining further based on at least one predictive model that predicts whether a fuel leak exists in the fuel storage facility, the at least one predictive model being based on one or more user-provided parameters;
providing a visual characterization of the predicted fuel leakage rate for the fuel storage facility to a display communicatively coupled to the server;
wherein the one or more user-provided parameters include at least one of a time period of operation of the fuel storage facility and at least one data quality parameter to improve a quality of the received data.