FogHorn’s Lightning Edge AI Platform allows operations tech team to gather actionable insights from streaming data

FogHorn announced on Tuesday availability of new Lightning Edge AI platform features, including tools and enhancements to empower operations technology (OT) professionals. The new drag-and-drop analytic programming capabilities and rich visualization dashboards enable OT staff to derive insights more quickly from real-time data without the need for assistance from data science teams.

Industry analysts recognize FogHorn Lightning Edge AI as a leader in IoT-AI platforms for industrial markets. The Lightning edge computing platform brings intelligence to the edge, at or near the point where data originates, and facilitates analysis with the lowest latencies to improve operational outcomes. 

Artificial intelligence (AI) is enabled through built-in closed-loop edge-to-cloud machine learning, where FogHorn Lightning can detect drifts in model accuracies and automatically trigger cloud-based retraining with Google Cloud Platform (GCP) and now, Microsoft Azure IoT, and republish new models to the edge in an iterative fashion until the expected accuracy is reached.

With this version of Lightning Edge AI, users get access to key improvements for productivity of OT teams. A visual programming tool, VEL Studio, creates simple to sophisticated analytic expressions that derive actionable insights from streaming control & sensor data. A newly introduced drag-and-drop library of over 100 built-in code blocks lets OT professionals perform traditional data science tasks without the need for any programming skills. 

This new functionality allows users to simply drag blocks to the workspace, fill in required parameters and connect the code blocks. These code blocks perform analytic functions, including; data cleansing and filtering, data collection and type conversion, event/pattern detection, signal processing and mathematical and statistical analysis. FogHorn also released OT-centric blocks for manufacturing-specific use cases to make it even easier to create advanced analytics including anomaly and failure condition detection.

VIZ Dashboards allows OT teams to visualize real-time data streams and monitor the efficiency and health of their environments. Dashboards are a user-defined canvas of widgets that visualize results of analytic expressions, display output of machine learning algorithms, validate sensors, and troubleshoot diagnostics of input sources. 

Based on how the user needs to employ each dashboard, widgets can be drawn to any size and include data visualizations, such as line graphs, bar charts, gauges, last state cards, maps, video feeds, images, and containers for nested dashboards.

The Lightning Edge AI platform also includes closed-loop ML to realize closed loop machine learning from edge to cloud in order to maintain the health of deployed models. Now supported on Azure, along with Google Cloud Platform. An exploratory data analysis tool to help teams determine the value of data before investing in analytics and machine learning initiatives, and addition of new, out-of-the-box, ingestion agents such as OPC-DA.

“Lightning Edge AI was designed with OT professionals in mind as a bridge between subject matter experts and deriving actionable insights from real-time data,” said Sastry Malladi, CTO at FogHorn. “The simplicity of the new VEL Studio and code blocks empower OT teams to gain meaningful business insights with easy-to-use data science capabilities without the need to code or be an analytics expert.”

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