Mesh network routing based on availability of assets
First Claim
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1. A computer-implemented method comprising:
- receiving, by an analytics system from a mesh network comprising a plurality of assets at a remote location, respective operating data for each asset in the mesh network that is indicative of the operating conditions of the asset, wherein each asset is equipped with a respective set of sensors for monitoring the operating conditions of the asset;
for each asset in the mesh network, executing a respective predictive model that takes the respective operating data for the asset as inputs and outputs a respective likelihood value for the asset indicating a likelihood that the asset will become unavailable within a given period of time in the future;
while executing the respective predictive model for each asset in the mesh network, determining that the respective likelihood value for a given asset of the plurality of assets in the mesh network has met threshold criteria indicating that the given asset is likely to be unavailable within the given period of time in the future;
in response to the determining, communicating with the mesh network to cause a routing configuration for at least one other asset in the mesh network to be updated such that the given asset is removed from the routing configuration.
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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 updating a routing table. In particular, examples involve based on a predictive model, determining that a given asset of a plurality of assets in a mesh network is likely to be unavailable within a given period of time in the future and in response to the determining, causing a routing configuration for at least one other asset in the mesh network to be updated.
131 Citations
20 Claims
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1. A computer-implemented method comprising:
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receiving, by an analytics system from a mesh network comprising a plurality of assets at a remote location, respective operating data for each asset in the mesh network that is indicative of the operating conditions of the asset, wherein each asset is equipped with a respective set of sensors for monitoring the operating conditions of the asset; for each asset in the mesh network, executing a respective predictive model that takes the respective operating data for the asset as inputs and outputs a respective likelihood value for the asset indicating a likelihood that the asset will become unavailable within a given period of time in the future; while executing the respective predictive model for each asset in the mesh network, determining that the respective likelihood value for a given asset of the plurality of assets in the mesh network has met threshold criteria indicating that the given asset is likely to be unavailable within the given period of time in the future; in response to the determining, communicating with the mesh network to cause a routing configuration for at least one other asset in the mesh network to be updated such that the given asset is removed from the routing configuration. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A non-transitory computer-readable medium having instructions stored thereon that are executable to cause a computing system to:
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receive, from a mesh network comprising a plurality of assets at a remote location, respective operating data for each asset in the mesh network that is indicative of the operating conditions of the asset, wherein each asset is equipped with a respective set of sensors for monitoring the operating conditions of the asset; for each asset in the mesh network, execute a respective predictive model that takes the respective operating data for the asset as inputs and outputs a respective likelihood value for the asset indicating a likelihood that the asset will become unavailable within a given period of time in the future; while executing the respective predictive model for each asset in the mesh network, determine that the respective likelihood value for a given asset of the plurality of assets in the mesh network has met threshold criteria indicating that the given asset is likely to be unavailable within the given period of time in the future; and in response to the determining, communicate with the mesh network to cause a routing configuration for at least one other asset in the mesh network to be updated such that the given asset is removed from the routing configuration. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A computing system comprising:
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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 computing system to; receive, from a mesh network comprising a plurality of assets at a remote location, respective operating data for each asset in the mesh network that is indicative of the operating conditions of the asset, wherein each asset is equipped with a respective set of sensors for monitoring the operating conditions of the asset; for each asset in the mesh network, execute a respective predictive model that takes the respective operating data for the asset as inputs and outputs a respective likelihood value for the asset indicating a likelihood that the asset will become unavailable within a given period of time in the future; while executing the respective predictive model for each asset in the mesh network, determine that the respective likelihood value for a given asset of the plurality of assets in the mesh network has met threshold criteria indicating that the given asset is likely to be unavailable within the given period of time in the future; and in response to the determining, communicate with the mesh network to cause a routing configuration for at least one other asset in the mesh network to be updated such that the given asset is removed from the routing configuration. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification