Dynamic execution of predictive models
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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Abstract
Disclosed herein are systems, devices, and methods related to assets and predictive models and corresponding workflows that are related to the operation of assets. In particular, examples involve assets configured to receive and locally execute predictive models, locally individualize predictive models, and/or locally execute workflows or portions thereof.
160 Citations
19 Claims
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1. A local analytics device configured to monitor operating conditions of an asset, the local analytics device comprising:
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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. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A non-transitory computer-readable medium having instructions stored thereon that are executable to cause a local analytics device to:
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identify a predictive model that is configured to output predictions related to operation of an asset to which the local analytics device is coupled via an asset interface of the local analytics device; 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 a computing system located remote from 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 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 a network interface of the local analytics device, (i) an instruction for the computing system to execute the predictive model, and (ii) operating data for the asset received via the asset interface. - View Dependent Claims (12, 13, 14, 15, 16)
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17. A method comprising:
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identifying, by a local analytics device, a predictive model configured to output predictions related to operation of an asset to which the local analytics device is coupled via an asset interface of the local analytics device; based on one or more execution functions corresponding to the identified predictive model, determining 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 a computing system located remote from 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 computing system; if it is determined that the local analytics device should execute the predictive model, executing, by the local analytics device, the predictive model based on operating data for the asset received via an asset interface of the local analytics device; and otherwise, transmitting, by the local analytics device to the computing system via a network interface of the local analytics device, (i) an instruction for the computing system to execute the predictive model, and (ii) operating data for the asset received via the asset interface. - View Dependent Claims (18, 19)
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Specification