learning capabilities and universal compatibility across all major IIoT edge systems. Accenture predicts that IIoT can add $14.2 trillion to the global economy by 2030. However, industrial environments present a challenge to status quo methods for data collection and analysis.
“The money and time required to move massive amounts of machine data to the cloud for analysis, only to send the results back to the edge, often makes little sense,” said Mike Guilfoyle, director of research and senior analyst at ARC Advisory Group. “In many instances cloud computing won’t be practical, necessary, or desirable. The reality is that edge intelligence is critical to a successful overall analytics strategy."
“FogHorn is accelerating the pace of innovation in edge computing by not just democratizing analytics but by making machine learning accessible to industrial operators,” said FogHorn CEO David C. King. “With the introduction of Lightning ML, we now offer customers the game-changing combination of real-time streaming analytics and advanced machine-learning capabilities powered by our high-performance CEP engine.”
According to FogHorn, Edge Lightning ML brings the power of machine learning at the edge in three ways:
1. Leverages existing models and algorithms: Industrial customers can seamlessly plug in and execute proprietary algorithms and machine-learning models on live data streams produced by their physical assets and industrial-control systems.
2. Makes machine learning OT-accessible: Non-technical personnel can use FogHorn’s tools to generate powerful machine learning insights without the need to constantly rely on in-house or third party data scientists.
"FogHorn's breakthrough edge computing technology brings the power of big data analytics and machine learning to the OT (operations technology) world," said Casey Taniguchi, general manager and head of business development center at Yokogawa Electric Corporation, a global leader in process and industrial automation systems.
On-premise-centric and cloud agnostic, the FogHorn Lightning ML software platform can run entirely on premise or connect to any private cloud or public cloud environment. This gives customers flexibility in selecting the best deployment model in terms of IT infrastructure, security policy and cost.
“OT staff are domain experts in their respective industrial environments, but not necessarily experts in edge computing and advanced IT,” said FogHorn CTO Sastry Malladi. “By giving them intuitive tools to automate, monitor and take action on their industrial data in real-time, operators can enhance situational awareness, prevent process failures and identify new efficiencies that lead to huge business benefits.”