In October 2016, I wrote about FogHorn Systems' Lightning software platform for real time analytics and its support from industrial companies such as GE, Bosch and Yokogawa. The newest version of Lightning will reportedly extend Lightning's analytics capabilities with the addition of integrated machine learning capabilities and universal compatibility across all major IIoT edge systems, according to FogHorn Systems. Edge computing appears to be the most likely technology through which manufacturers will predominantly connect devices and systems for Industrial Internet of Things (IIoT) initiatives. This is largely due to the fact that edge computing allows for on-premise analysis of manufacturing data, thereby mitigating bandwidth speed and cost issues associated with cloud-based analysis. It also narrows access to the data given the proper installation and use of cybersecurity technologies and practices.

Machine learning capabilities are a significant asset in IIoT platforms, assisting in the collection and organization of data between multiple edge devices within the network. FogHorn Systems announced yesterday the availability of Lightning ML, an edge intelligence software platform for the Industrial Internet of Things (IIoT), which the company states is the industry's first IIoT software platform with integrated machine learning capabilities and universal combability across all major IIoT edge systems, i.e. operational technology (OT) systems and IoT sensors. "To date, machine learning is typically done in the cloud," said David C. King, CEO of FogHorn Systems. "FogHorn Lightning ML is designed to deliver the same powerful machine learning (ML) insights on a very tiny footprint, less than 256MB." Lightning ML users can execute proprietary, domain-specific ML models or choose from ML algorithms which plug into streaming data from assets and machines.