Category: Uncategorized

OPUS Product Update

Post author By Megan Finkelde
Post date July 2, 2024

Learn more the latest OPUS product updates. OPUS is VROC's AIoT Platform for process industries

Comparison of DataHUB+ and OSIsoft PI

Post author By Megan Finkelde
Post date April 16, 2024

A comparison of two process historians, OSIsoft PI and DataHUB+

Introducing OASIS product release 4

Post author By Megan Finkelde
Post date March 20, 2024

OASIS. IoT Platform for facilities, new release product information.

DataHUB+ : A Modern Alternative to PI ProcessBook

Post author By Megan Finkelde
Post date February 27, 2024

High level dashboard, of operating limits being monitored by a client using DataHUB+

5 Data & AI Essentials for Australian Councils and Cities

Post author By Megan Finkelde
Post date December 20, 2023

Discover the 5 Data and AI Essentials for Australian Councils and Cities in 2024.

Choosing The Right Predictive Maintenance Solution

Post author By Megan Finkelde
Post date December 1, 2023

4 factors to consider when choosing a predictive maintenance solution for your plant

8 Myths about AIoT

Post author By Megan Finkelde
Post date October 18, 2023

What is AIoT and what myths about it need to be dispelled

Anomaly Detection 101

Post author By Megan Finkelde
Post date August 23, 2023

Anomaly Detection 101. Learn how anomaly detection can help early fault detection and optimization strategies

Podcast: Leveraging AI to control Assets

Post author By Megan Finkelde
Post date June 6, 2023

Everyone Podcast by Smart Cities Council

Unlocking the Power of Time Series Data

Post author By Megan Finkelde
Post date May 10, 2023

Unlocking the power of time series data with no-code AI

Protecting Customer Data

Post author By Megan Finkelde
Post date April 18, 2023

VROC SOC 2 and ISO 27001 compliant — VROC AI is SOC 2 and ISO 27001 compliant

How AI Determines Correlations in Data

Post author By Megan Finkelde
Post date April 12, 2023

How does AI determine correlations in data? — How does AI determine correlations in data? How does it know good data from bad data?

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