MOUNTAIN VIEW, Calif., July 18, 2018 (GLOBE NEWSWIRE) — FogHorn, a leading developer of edge intelligence software for industrial and commercial Internet of Things (IoT) solutions, today announced its participation plans in coordination with Google at Google Cloud Next 2018. FogHorn will give a sneak peak of the industry’s first iterative edge-to-cloud demo, showcasing how industrial IoT (IIoT) artificial intelligence (AI) and closed loop machine learning (ML) between edge and cloud helps maximize the value of industrial data from connected, IoT devices.
- EVENT: Google Cloud Next is a global exhibition of inspiration, innovation, and education. It’s where developers and anyone passionate about an accessible, scalable, socially responsible cloud come together to share challenges, solutions, 10x ideas, and game-changing technologies.
- WHEN: July 24-26, 2018
- WHERE: Booth: S1615, Level 1, Moscone South, San Francisco, CA
- DEMONSTRATIONS: At the event, FogHorn will showcase how edge-to-cloud closed loop ML is being used to enhance industrial operations. Attendees will also be able to witness first-hand demonstrations of edge intelligence applications for the manufacturing and oil & gas sectors.
Global management consulting firm Accenture estimates the IIoT could add $14.2 trillion to the global economy by 2030. Within this fast-growing market, the innovative approach to data processing with edge computing is experiencing rapid adaptation. In four years, 75 percent of enterprise generated data will be processed at the edge, up from less than 10 percent today, according to Gartner1.
Among the varied benefits edge computing can provide to companies, edge-to-cloud processing can help industrial organizations significantly optimize distributed assets and processes. FogHorn recently announced a partnership with Google Cloud IoT Core to help organizations enrich and elevate data processing at or near the source of sensor data for further analysis.
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.
“By combining FogHorn’s industry-leading edge intelligence with the power of Google Cloud’s world-class data infrastructure we have created a fully-integrated edge-to-cloud solution that maximizes the insights gained from every IIoT device,” said Keith Higgins, VP of Marketing at FogHorn. “Our collaborative demonstration at Google Cloud Next 2018 will showcase the opportunities available for industrial organizations to use our combined solution to achieve reduced costs, improved efficiencies and better business outcomes overall.”
For more information about FogHorn at Google Cloud Next, please visit: https://www.foghorn.io/google-cloud-next-conference-2018/
1Gartner, “Top 10 Strategic Technology Trends for 2018: Cloud to the Edge,” March 18, 2018
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-premises 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 is a trademark of FogHorn Systems. The names of actual companies and products mentioned herein may be the trademarks of their respective owners.