Daniel Barrett

Title: Daniel Barrett: Inventor in Distributed Fault Detection

Introduction

Daniel Barrett is an inventor based in Moore, Oklahoma, whose patent work addresses distributed fault detection. His disclosed invention uses machine learning to help computing systems identify potential faults in physical environments.

Latest Patents

Barrett is associated with 1 patent, titled “Distributed Fault Detection.” The invention describes a computing node that receives sensor data and analyzes it with a restricted Boltzmann machine (RBM) neural network to detect a fault condition. The RBM is trained without fault-condition identifications, and the node can update the network using incoming sensor data. It then sends a patch representing the updated network to a central server. The server can aggregate that patch with a patch from another computing node and return information about a further updated network.

Career Highlights

Barrett is associated with Dell Products Inc. His patent reflects an approach to distributed machine learning in which local computing nodes contribute updates that can be combined centrally.

Collaborations

Pulkit Rathi is identified as Barrett’s coworker. The patent description also outlines a collaborative system in which multiple computing nodes send model updates to a central server for aggregation.

Conclusion

Daniel Barrett’s distributed fault detection patent presents a method for using sensor data and collaboratively updated neural networks to identify potential faults in physical environments.