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RELIABLE

YOU MUST YEILD RELIABLE DATA TO DRIVE TRASTWORTHY AI FOR IIoT

DATA

There’s a well-known industry facet that producing dependable outcome like predictive maintenance requires involvement of enormous amount of data and AI/ML modeling. But that doesn’t shine light on the fact that it’s not just happening by itself and, to date, entails substantial amount of manual effort to develop and train the AI models.

Thus, unless human biased involvement is minimized or eliminated, at least in the process of AI labeling or aligning data with a perceived problem, predictive analysis will always be assumptive, inaccurate and impractical.

IIoT reliable data

There’s a well-known industry facet that producing dependable outcome like predictive maintenance requires involvement of enormous amount of data and AI/ML modeling. But that doesn’t shine light on the fact that it’s not just happening by itself and, to date, entails substantial amount of manual effort to develop and train the AI models.

Thus, unless human biased involvement is minimized or eliminated, at least in the process of AI labeling or aligning data with a perceived problem, predictive analysis will always be assumptive, inaccurate and impractical.

Predictive Analysis

Flow Diagram

Predictive Analysis Flow Diagram
Open scheme

To resolve these challenges, Vixtera developed and patented Root Cause Analysis algorithm, performing it closer to devices and explicitly identifying and using cause of failure as reliable source (label) for auto-generation of training data sets for Neural Network (NN). Although it has been mainly developed for real-time failure detection at the edge, this method provides significant uplifting helping to eliminate error-prone human involvement in AI/ML modeling providing accurate and dependable source for predictive analysis whereas generating trustworthy data for variety of applications and services.

...TRASTWORTHY OUTCOME

Summary

Vixtera developed and patented Root Cause Analysis algorithm using cause of failure as a reliable source (label) for auto-generation of training data sets for Neural Network (NN).

Summary