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Dynamic execution of predictive models

  • US 10,579,750 B2
  • Filed: 06/17/2016
  • Issued: 03/03/2020
  • Est. Priority Date: 06/05/2015
  • Status: Active Grant
First Claim
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1. A local analytics device configured to monitor operating conditions of an asset, the local analytics device comprising:

  • an asset interface configured to couple the local analytics device to the asset;

    a network interface configured to facilitate communication between the local analytics device and a computing system (i) configured to monitor operating conditions of the asset and (ii) located remote from the local analytics device;

    at least one processor;

    a non-transitory computer-readable medium; and

    program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor to cause the local analytics device to;

    identify a predictive model that is configured to output predictions related to operation of the asset;

    based on one or more execution functions corresponding to the identified predictive model, determine whether the local analytics device should execute the predictive model, wherein the one or more execution functions are configured to quantify (i) an expected cost associated with executing the predictive model at the local analytics device that is based at least in part on an expected accuracy of predictions related to the operation of the asset to be output by the predictive model as executed at the local analytics device and (ii) an expected cost associated with executing the predictive model at the computing system that is based at least in part on an expected accuracy of predictions related to the operation of the asset to be output by the predictive model as executed at the computing system;

    if it is determined that the local analytics device should execute the predictive model, execute the predictive model based on operating data for the asset received via the asset interface; and

    otherwise, transmit to the computing system, via the network interface, (i) an instruction for the computing system to execute the predictive model, and (ii) operating data for the asset received via the asset interface.

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