Far edge/IOT intelligence design and apparatus for human operators assistance
AssigneeDell Products L.P.
InventorsAurelian Dumitru, Eric L. Caron, Nalinkumar Mistry
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Abstract
One example method is performed at a far edge device and includes collecting data with one or more IoT (Internet of Things) devices, feeding the data to a feedback loop that includes multiple stages, running the feedback loop, providing learning information, comprising output from one or more of the stages of the feedback loop, to a central manager by way of a learn interface, accessing learning information generated by one or more other far edge devices, and updating the feedback loop using the learning information generated by the one or more other far edge devices.
Claims18
A method, comprising:
- performing, by a model running on a far edge knowledge manage instance at a far edge device, operations comprising:
- collecting data with one or more IoT (Internet of Things) devices;
- feeding the data to a feedback loop that includes multiple stages;
- running the feedback loop;
- providing learning information, comprising output from one or more of the multiple stages of the feedback loop, to a central manager by way of a learn interface;
- accessing learning information, which is generated by the central manager based on data fed by one or more other far edge devices;
- and
- updating the model using the learning information generated by the central manager based on the data fed by the one or more other far edge devices,
- wherein the far edge device operates autonomously with respect to the one or more other far edge devices, while also incorporating learnings generated by the one or more other far edge devices.
A non-transitory storage medium having stored therein instructions that are executable by one or more hardware processors of a far edge device to perform operations, by a model running on a far edge knowledge manage instance, comprising:
- collecting data with one or more IoT (Internet of Things) devices;
- feeding the data to a feedback loop that includes multiple stages;
- running the feedback loop;
- providing learning information, comprising output from one or more of the multiple stages of the feedback loop, to a central manager by way of a learn interface;
- accessing learning information, which is generated by the central manager based on data fed by one or more other far edge devices;
- and
- updating the model using the learning information generated by the central manager based on the data fed by the one or more other far edge devices,
- wherein the far edge device operates autonomously with respect to the one or more other far edge devices, while also incorporating learnings generated by the one or more other far edge devices.
Dependencies are inferred from the claim text.