FogHorn: Lightning Edge Intelligence Product Portfolio

FogHorn’s Lightning™ product portfolio brings a groundbreaking dimension to IIoT and edge computing by embedding edge intelligence as close to the source of streaming sensor data as possible.

The FogHorn platform is a highly compact, advanced and feature-rich edge intelligence solution that delivers unprecedented low latency for onsite data processing, real-time analytics, ML and AI capabilities. It delivers the industry’s lowest total cost for computing requirements, communications services, and cloud processing and storage.

Lightning Product Portfolio

VEL® CEP

A Real Edge Solution
FogHorn’s VEL Complex Event Processor (CEP) was engineered specifically for industrial edges:

• Performs real-time analysis of disparate streams of sensor data
• Optimizes constrained and diverse compute environments that have limited or no connectivity
• Simplifies interoperability with existing OT systems
• Simultaneously performs complex pattern recognition on high frequency and inherently asynchronous streaming data
• Detects events in real-time, enabling immediate closed loop control actions, resulting in significant cost savings
• Handles machine learning pre and post processing (cleansing, filtering, normalizing, and contextualizing streaming sensor data) optimizing it for machine learning performance

EdgeML

Edgified Machine Learning
The Lightning platform edgifies machine learning models to execute efficiently at the industrial edge.

• The VEL CEP engine, in addition to pattern detection and analytics, provides data pre and post processing, preparing streaming sensor data for machine learning
• Reduces machine learning model size and required memory by more than 80%. This enables fast and efficient ML execution in resource-constrained environments
• Import existing models (PMML, Python) seamlessly into the platform, bridging OT-IT divide
• The cloud plays a critical role in ML model creation and training, especially for deep learning models. Once trained, the model can be edgified and pushed to the edge. EdgeML enables an iterative closed-loop edge to cloud machine learning cycle
• Execute neural net models (example: video analytics) in constrained compute environments with the same powerful results as using the cloud

OT-Centric Toolkit

The Industry’s Most Complete IIoT Edge Solution
The Lightning platform offers a robust set of tools to help clients easily create new analytic expressions with a drag and drop UI, simulate sensor traffic, visualize streaming sensor data, and centrally manage FogHorn deployments in a scalable fashion. These include:

• FogHorn Manager – A browser-based tool that lets deploy configuration or custom applications across thousands of Edges, create analytic expressions, and create data publications to send the insights to a preferred cloud storage location
• REX – A multi-purpose tool that simulates sensor traffic to debug production issues in industrial IoT environments
• VIZ – Lets you visualize real-time streams. It can be used to validate sensors, troubleshoot problem input sources, visualize the results of analytic expressions, or view the output of machine learning algorithms
• VEL Studio – Gives users the ability to author and debug analytic expressions using a drag and drop interface. Additionally, it provides templates that are commonly used in industrial settings to accelerate the creation of new analytic expressions. The visual debugger helps validate and troubleshoot expressions using simulated and authentic production data

Product Highlights

Delivers High Performance Edge Analytics + Machine Learning (ML)

Massive amounts of data, combined with the cost and latency of cloud computing demand a robust edge computing solution. Lighting™ platform uniquely combines a highly miniaturized complex event processing (CEP) analytics engine and ML capability in a single software instance. This approach offers rapid data ingestion and enrichment, sensor fusion, and ML to generate actionable insights in real-time.

Operates in the Industry’s Smallest Computing Footprint

Lightning™ performs complex data analytics and executes powerful machine learning models on high volume, high velocity streaming sensor data in a tiny memory footprint of less than 256MB. This allows deployment on highly-constrained compute devices such as PLCs, Raspberry Pi systems, and tiny ruggedized IIoT gateways. The platform also scales up to more powerful Industrial PCs and data center servers.

Designed for Operator Technology Personnel

Operational Technology (OT) personnel can use FogHorn’s tools to generate powerful ML-based insights without data scientists. Sensor auto-discovery, VEL® Studio, device auto-registration and batch configuration deployment deliver unprecedented automation and scale. A drag-and-drop analytics authoring tool offers an intuitive UI for generating actionable and predictive insights without programming.

Edgified Machine Learning

FogHorn Lightning edgifies ML models to execute efficiently at the industrial edge. FogHorn’s CEP provides the data pre/post processing and full conditioning, preparing it for ML models. This approach reduces the size and required memory by ~ 80%, enabling fast and efficient execution in constrained environments. Lightning also supports models such as Spark ML, R Studio etc., through the use of PMML.

Executes Deep Learning – at The Edge

Deep learning is especially relevant in vision / natural language processing use cases. It uses neural networks for training models that are trained in the cloud, then pushed to the FogHorn platform to execute complex Convolutional Neural Networks (CNN) in highly constrained computing environments. No other platform offers edge-based deep learning.

Large Scale Deployment Support

FogHorn’s platform offers automatic edge device registration, one click multi-edge deployment, multi-tenancy and edge-based health metrics and alerts to support use cases with a high volume of intelligent edge devices.

Cloud Integration Out-of-the-Box

FogHorn offers publishing to leading cloud providers including Google Cloud, AWS and Azure IoT Hub. Deeper integration with Google Cloud includes device management, IAM integration and cloud-loop ML.

Enhanced Security

Advanced role-based access control with integrated OAuth based Identity Access Management (IAM) capability with Cloud Foundry, Microsoft Azure, and Google Cloud offers the more robust edge intelligence security solution.

Embraced by Leaders

FogHorn’s technology has been embraced by the world’s leading Industrial Internet innovators as well as major players in cloud computing, systems integration, and high-performance edge gateways. Our partners include GE, Bosch, Yokogawa, PWC, Tech Mahindra, Infosys, NEC, Dell, HP Enterprise, Cisco, Intel, AWS, Microsoft, SAP, and more.