US 12,443,999 B2
System and method for model-based prediction using a distributed computational graph workflow
Jason Crabtree, Vienna, VA (US); and Andrew Sellers, Monument, CO (US)
Assigned to QOMPLX LLC, Reston, VA (US)
Filed by QOMPLX LLC, Reston, VA (US)
Filed on Jun. 28, 2021, as Appl. No. 17/360,007.
Application 17/360,007 is a continuation in part of application No. 16/575,929, filed on Sep. 19, 2019, granted, now 11,074,652.
Application 16/575,929 is a continuation in part of application No. 16/191,054, filed on Nov. 14, 2018, granted, now 10,681,074, issued on Jun. 9, 2020.
Application 16/191,054 is a continuation in part of application No. 15/655,113, filed on Jul. 20, 2017, granted, now 10,735,456, issued on Aug. 4, 2020.
Application 15/655,113 is a continuation in part of application No. 15/616,427, filed on Jun. 7, 2017, abandoned.
Application 15/616,427 is a continuation in part of application No. 14/925,974, filed on Oct. 28, 2015, abandoned.
Application 15/655,113 is a continuation in part of application No. 15/237,625, filed on Aug. 15, 2016, granted, now 10,248,910, issued on Apr. 2, 2019.
Application 15/237,625 is a continuation in part of application No. 15/206,195, filed on Jul. 8, 2016, abandoned.
Application 15/206,195 is a continuation in part of application No. 15/186,453, filed on Jun. 18, 2016, abandoned.
Application 15/186,453 is a continuation in part of application No. 15/166,158, filed on May 26, 2016, abandoned.
Application 15/166,158 is a continuation in part of application No. 15/141,752, filed on Apr. 28, 2016, granted, now 10,860,962.
Application 15/141,752 is a continuation in part of application No. 15/091,563, filed on Apr. 5, 2016, granted, now 10,204,147, issued on Feb. 12, 2019.
Application 15/141,752 is a continuation in part of application No. 14/986,536, filed on Dec. 31, 2015, granted, now 10,210,255, issued on Feb. 19, 2019.
Application 15/141,752 is a continuation in part of application No. 14/925,974, filed on Oct. 28, 2015, abandoned.
Prior Publication US 2022/0058745 A1, Feb. 24, 2022
Int. Cl. G06Q 40/08 (2012.01); G06N 7/01 (2023.01); G06Q 30/0201 (2023.01); G06Q 50/00 (2012.01)
CPC G06Q 40/08 (2013.01) [G06N 7/01 (2023.01); G06Q 30/0201 (2013.01); G06Q 50/01 (2013.01)] 10 Claims
OG exemplary drawing
 
1. A system for model-based prediction using a distributed computational graph workflow, comprising:
a computing system comprising at least one memory, at least one processor, and at least one non-volatile data storage device; and
a plurality of network-connected physical sensors;
wherein the at least one memory comprises a first plurality of programming instructions stored in the at least one memory and operating on the at least one processor, wherein the first plurality of programming instructions, when operating on the at least one processor, causes the computing system to:
automatically gather telematics data from the plurality of network-connected physical sensors;
record the telematics data and time of receipt in a multidimensional time-series database stored on the at least one non-volatile data storage device;
retrieve a prediction model from the non-volatile data storage device for prediction of a probability of a future event from the received data;
send the telematics data and the prediction model to a distributed computational graph for processing;
receive processed data from the distributed computational graph;
predict the probability of a future event from the processed data;
determine a premium for an insurance product based on at least the predicted probability of the future event;
generate a specific remedial action based on the predicted probability of the future event, wherein the specific remedial action comprises a recommended operational adjustment for communication to an insured party to reduce the probability of the future event;
transmit the specific remedial action to a notification device associated with the insured party;
after transmission of the specific remedial action to the notification device:
automatically gather updated telematics data from the plurality of network-connected physical sensors;
analyze the updated telematics data to determine whether the recommended operational adjustment was implemented by the insured party; and
determine a new premium for an insurance product based on whether the recommended operational adjustment was implemented, as indicated by the updated telematics data; and
wherein the at least one memory further comprises a second plurality of programming instructions stored in the at least one memory and operating on the at least one processor, wherein the second plurality of programming instructions, when operating on the at least one processor, causes the computing system to:
receive the prediction model for processing;
construct the distributed computational graph from the prediction model using the at least one processor, the distributed computational graph representing a data processing workflow and comprising a directed graph with nodes representing data transformations and edges representing messaging between the nodes;
receive the telematics data; and
process the telematics data according to the data processing workflow represented by the distributed computational graph.