AI Cloud for IIoT

IDC projects that 50% of all data being produced in the world will originate in IoT and be from machines, sensors, and industrial tools. Industrial companies grapple with such colossal volumes of data, necessitating an approach that goes beyond conventional means of data analysis.

While business intelligence (BI) was previously used to extract value from data at scale, visualization and simple statistics are not adequate to drive industrial decisions from real-time and Industrial IoT data. A different approach is needed to work with the volume and nature of IIoT data. Real-time data, also known as IIoT data, takes various forms – telemetry data, SCADA data, PLC data, machine data, and sensor data – all sharing the commonality of being time series data. Traditional BI tools fall short in effectively processing and deriving actionable insights from this complex data type.

Previous Big Data approaches for Industrial IoT applied Machine Learning (ML) to real-time data, which worked well for a small subset of use cases with labeled data and consistent behavior. These were highly dependent on data science teams, required intensive coordination between IT and OT teams, and minimal changes to operations. However, economic and technical constraints have made ML impractical for all but a few IIoT needs. There is a very clear case for AI that is inherently well-suited to extract meaningful conclusions from such massive volumes of real-time data and drive meaningful operational improvement.

While the recent prominence of Large Language Models (LLMs) and ChatGPT are seen to bring AI benefits to businesses, the reality is that it is going to make hardly any difference to IIoT. AI suitable for operational data is clearly the need of the hour. That's exactly what we provide at Falkonry. Just like Google’s PageRank produces an abstract representation of text in a Web page, Falkonry’s Time Series AI automatically builds an abstract representation of operational data. This produces highly usable information from all kinds of operational data.?

As Ali Ghodsi of Databricks says, we need databases with inbuilt intelligence and support for machine learning to make sense of the exponential growth in data. At Falkonry, we call intelligent databases for operational data as Time Series AI Cloud. We are disrupting the real-time data space with out-of-the-box AI and applications in the form of our AI Cloud for IIoT.?

AI Cloud for IIoT seamlessly overcomes integration difficulties, labor-intensive ML projects, and the costs of storing and processing real-time data. It also performs continuous processing of data streams and tells you on a proactive basis when something needs your attention, such as an unknown event or an anomaly, or if a certain operational parameter exceeds a certain range. With an open, secure, and flexible architecture, it lets your operational teams swiftly scale AI in production, unlocking the full potential of your IIoT data, without extensive IT efforts.

If you’d like to know how to get on to this always-active, persistent, intelligent cloud, hit us up.

Original Content

Understanding Data-Driven Operations. Part of our back-to-basics series, this simple explainer delves into the foundational elements of data-driven operations, also known as Smart Operations. Gain insights into its definition, purpose, and comparative analysis with alternative decision-making approaches, including event-driven and intuition-based strategies.

In The News

Falkonry on the Industry 4.0 Club Fireside Broadcast. ?Ashis Khan, Falkonry’s VP of Smart Manufacturing, was invited to a CESMII Smart Manufacturing Broadcast, hosted by the Industry 4.0 club. The live stream (out now) covers insights on a diverse range of topics including the practical aspects of leveraging AI to improve manufacturing results.?Watch now ??

Interesting Reads

Manufacturing Technology Predictions for 2024. As we delve into predictions this time of year, Industry Week points out the profound impact even a basic IIoT system can have on enhancing OEE and productivity. One of their predictions says industrial data management is expected to further evolve and become a top priority for organizations. IIoT software platforms will continue to play a role in connecting, managing, and extracting data from connected devices, it will be crucial for manufacturers to depend on analytics to make sense of the data.

AI Data Warehouses are the new enterprise IT foundation. The annual review of B2B by Ashu Garg features a quote by Ali Ghodsi of DataBricks: “Intelligence will creep in wherever you have data.” AI is not just a feature of data platforms but as Ashu says “intelligence and automation will be bundled into the data architecture that underlies enterprise software.” In other words, “AI will eat software.”