Cross-organization continuous update of edge-side event detection models in warehouse environments via federated learning
One example method includes deploying, from a central node, respective instances of an event detection model to each edge node in a group of edge nodes, providing training data to the edge nodes, wherein the training data is usable by each of the edge nodes to train its respective instance of the mo...
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Main Authors | , , |
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Format | Patent |
Language | English |
Published |
03.09.2024
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Subjects | |
Online Access | Get full text |
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Summary: | One example method includes deploying, from a central node, respective instances of an event detection model to each edge node in a group of edge nodes, providing training data to the edge nodes, wherein the training data is usable by each of the edge nodes to train its respective instance of the model, and wherein the training data comprises data obtained from an environment other than an environment in which the edge nodes operate, receiving, by the central node from the edge nodes, gradients that capture differences between the instance of the model, and updated instances of the model that were updated by the edge nodes as part of a training process performed at the edge nodes, updating, by the central node, the model with the gradients to create an updated model, and deploying, by the central node, respective instances of the updated model to the edge nodes. |
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Bibliography: | Application Number: US202217694173 |