MOUNTAIN VIEW, CA--(Marketwired - Sep 13, 2016) - FogHorn Systems, a leading developer of "edge intelligence" software for industrial and commercial IoT use cases, announced today the general availability of its new Lightning software platform for real-time analytics applications running on ultra-small footprint edge devices. Lightning allows application developers, systems integrators and production engineers to quickly and easily build high-performance edge analytics solutions for their industrial operations and Industrial IoT (IIoT) use cases, and rapidly deploy those applications throughout highly-dispersed distributed edge environments. By reducing bandwidth usage and costs, minimizing latency, and increasing reliability, FogHorn enables real-time responsiveness that is critical to a growing number of IIoT applications.
FogHorn recently announced a $12 million Series A round of funding, with several global IIoT leaders participating in the financing, including GE, Bosch and Yokogawa.
"FogHorn is revolutionizing the development of high-value IoT application solutions in a huge variety of industrial and commercial settings by bringing the power of 'big data' intelligence to the source of high-volume and high-velocity machine data at the edge, rather than transporting that data to the cloud or data center for upstream processing," said FogHorn CEO David C. King. "Lightning enables our end customers and their technology partners to build a powerful new class of real-time edge analytics IIoT solutions by minimizing application latency, as well as saving those customers an enormous amount of money associated with bandwidth and cloud hosting costs. Our initial successes have been with major players in the manufacturing, energy, transportation and smart cities sectors."
FogHorn helps to close the divide between the massive amounts of data generated -- often by thousands of sensors -- in an IIoT environment and the amount of the data that is used in operations. For example, McKinsey & Company has reported that less than one percent of the data being generated by 30,000 sensors on an offshore oil rig is currently being used to make decisions.
FogHorn's Lightning software platform allows businesses with distributed operations to derive actionable insights as close as possible to geographically dispersed IoT-connected machines and the operations technology (OT) control systems and sensors attached to those machines. Using Lightning, businesses can accelerate their digital transformation projects by spending less time and money on bandwidth costs and end-to-end integration tasks, and focusing more on the delivery of next-generation applications to optimize machine performance, increase total output, improve process yield, and reduce both production and energy consumption costs.
According to John L. Myers, managing Research Director at Enterprise Management Associates (EMA), the growth of connected IoT devices and sensors is driving an increase in new and disruptive business models across industries. "Data processing at the edge is disruptive because it enables industrial companies to tap into operational data for making decisions in real-time and at significant scale," Myers said. "Using data from IoT sensors to drive immediate action was not possible when data was processed in the cloud and not at the network edge. The benefits of edge computing solutions such as FogHorn's could extend well beyond cost savings and factory yield optimization, to intelligent management and forecasting."
In modern manufacturing plants, data ingestion from sensors on the assembly line, data processing, event detection/alerting, and detailed analysis can be achieved using the FogHorn Lightning Edge solution. For example, one of GE's "Brilliant Factories" that produces industrial-grade electrical products used in power grids is working with FogHorn to apply real-time analytics for maximizing manufacturing yields from data emitted by hundreds of sensors attached to each assembly line.
"FogHorn's real-time edge analytics align with our strategy to optimize lean manufacturing and digital capabilities in our brilliant factories," said Anup Sharma, GM - Digital Productivity, GE Digital. "Our engineers and analysts can work together on applications to analyze data from hundreds of sensors in real-time using an extremely agile approach, helping to improve productivity."
"At FogHorn, we solved the biggest challenges associated with gaining data insights at the edge, such as processing and correlating massive amounts of sensor data in real-time," said FogHorn CTO Sastry Malladi. "The high bandwidth costs of sending data from thousands of devices in remote deployment locations to the cloud for later processing is eliminated or significantly reduced. Bringing powerful analytics closer to the data source is made possible through our patent-pending, high-performance, small-footprint edge analytics engine and other key technology innovations we have introduced at the data ingestion, data processing and data publication layers of the Lightning edge software stack."
FogHorn Lightning is now available directly from FogHorn as well as a growing ecosystem of Lightning-certified IIoT application developer partners. Lightning is also accessible on the Microsoft Azure Marketplace and FogHorn is a certified SAP HANA application solution partner. In terms of IoT gateway hardware support, FogHorn is a certified Dell IoT solution partner and Lightning has also been validated on HPE Edgeline IoT Gateways as well as other Intel x86 IoT server platforms.
Available immediately, FogHorn's Lightning edge intelligence software platform is currently available in two different versions.
Lightning™ Micro Edition
Lightning Micro is embeddable software with a very small memory footprint (less than 256 MB) required for data processing and real-time analytics at the edge. Features include:
- High-speed data ingestion via OPC-UA, MQTT, Modbus and other protocols
- Data transformation and enrichment
- VEL, a real-time streaming analytic engine with an easy-to-use expression language and hundreds of built-in functions
- Low footprint Edge Application development using our C++ SDK
Lightning™ Standard Edition
The Lightning Standard Edition includes all of the features of Lightning Micro edition with additional support for advanced analytics, and edge applications in different languages. These additional features include:
- Built-in time series database for historical analysis
- Dashboard visualizer for real-time insights and a machine learning sandbox with commonly used algorithms
- Edge Application Development SDK in multiple languages (Java, Python, C++)
- Data publication to external/cloud based data stores such as Apache Hadoop, Kafka, Microsoft Azure, Cloud Foundry RIAK, etc.
The software installation can be managed remotely from a central management console for both these versions of the software with the following capabilities.
- Management console scaling to thousands of edge deployments
- Ability for users to add, manage, and monitor all connected devices and sensors from a single pane of glass
- Application deployment and monitoring
- VEL Analytic expression authoring and deployment
- Simplified edge configurations for easily repeatable deployments.
For additional information or a product demonstration
Please contact email@example.com.
About FogHorn Systems
FogHorn is a leading developer of "edge intelligence" software for industrial and commercial IoT application solutions. FogHorn's software platform brings the power of advanced analytics and machine learning to the on-premise edge environment enabling a new class of applications for advanced monitoring and diagnostics, machine performance optimization, proactive maintenance and operational intelligence use cases. FogHorn's technology is ideally suited for OEMs, systems integrators and end customers in manufacturing, power and water, oil and gas, renewable energy, mining, transportation, healthcare, retail, as well as Smart Grid, Smart City, Smart Building and connected vehicle applications.
FogHorn and Lightning are trademarks of FogHorn Systems. The names of actual companies and products mentioned herein may be the trademarks of their respective owners.