All the latest quantum computer articles

See the latest stories on quantum computing from eeNews Europe

Wednesday, September 14, 2016

Moving IoT analytics to the network edge

By Nick Flaherty

FogHornSystems has launched a software platform that it says can provide real-time analytics applications on what it calls ultra-small footprint edge devices.

This is ground breaking, as it allows 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 the highly-dispersed distributed edge environments. This reduces bandwidth usage and cost, minimizes latency and increases reliability as well as providing real-time responsiveness that is critical to a growing number of IIoT applications.

It looks like this is mostly aimed at edge gateway devices as the development kit supports C++ code up to 256M, rather than smaller embedded implementations for IoT nodes.

“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,” said John Myers, managing Research Director at Enterprise Management Associates (EMA). “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.”
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, to develop the technology.

“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 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 huse amount of data being generated by 30,000 sensors on an offshore oil rig is currently being used to make decisions, and it is something that has been highlighted by the Embedded Blog.
The Lightning software platform allows businesses with distributed operations to get insights as close as possible to geographically dispersed IoT-connected machines and the operations technology (OT) control systems and sensors attached to those machines. 

“FogHorn’s real-time edge analytics align with our strategy to optimize lean manufacturing and digital capabilities in our brilliant factories,” said Anup Sharma, General Manager of Digital Productivity at 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.”

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.

The platform is currently available in two different versions: 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 using a C++ SDK. Features include high-speed data ingestion via OPC-UA, MQTT, Modbus and other protocols, sata transformation and VEL, a real-time streaming analytic engine with an easy-to-use expression language and hundreds of built-in functions

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 and an Edge Application Development SDK in multiple languages such as Java, Python and C++. Data publication is to external/cloud based data stores such as Apache Hadoop, Kafka, Microsoft Azure, Cloud Foundry RIAK, etc.

No comments: