Discover the Power of Industrial IoT and Fog-based Machine Learning
Inside you’ll discover how you can…
Understand challenges, benefits, and best practices that will make your project a success.
Learn from real-world examples of applying Fog-based machine learning IoT projects in the Industrial space.
Understand how a Fog-based IoT architecture presents an opportunity for introducing ML to your Industrial IoT system.
Industrial IoT systems have unique requirements and constraints that impact the design of IoT solutions for industrial use. Industrial equipment has a long lifetime, measured in decades, and systems often have legacy edge sensors and limited bandwidth to the cloud. Situated between the legacy Edge and the too-far-away Cloud is a layer that has come to be known in IoT as the Fog. The Fog is the perfect place for doing the heavy lifting of machine learning (ML) in an IoT system. It operates close to the the data sources, but has enough power, bandwidth, and local context to make processing more capable than simple Edge processing.
In his presentation, Ed will discuss IoT projects in the Industrial space where Fog-based ML has been used in image classification, convolutional neural network processing, and data reduction. His extensive experience in embedded engineering and IoT systems offers a very specific and practical viewpoint. Ed developed this lecture to provide actionable takeaways for the Industrial IoT industry. He will discuss best practices in Industrial IoT development and case studies of successful deployments.
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Get a copy of Ed’s presentation and listen to what he has to say.
Learn from a real Industrial IoT expert
Ed founded Software Design Solutions (SDS) in 2003, focusing the company on embedded systems software development, and led the growth of the company from inception to its acquisition by Applied Visions in September 2016.
Prior to founding SDS, Ed was chief software architect for the digital signal processing (DSP) tools group at Texas Instruments. He joined Texas Instruments as part of the acquisition of the Carnegie Mellon spin off Tartan Laboratories, which developed highly optimized compiler technology for embedded systems. His career began at Raytheon Missile Systems, where he led the compiler team for the Patriot Missile system.
Ed holds an MS in Computer Science from the University of Pittsburgh. He is the author of several patents on embedded systems software. Ed developed this presentation to provide actionable takeaways for the Industrial IoT industry.
Ed Kuzemchak
CTO and Director, Embedded and IoT Engineering
Meet Ed Kuzemchak, Chief Technology Officer & Director of Embedded and IoT Engineering at Software Design Solutions. Ed recently delivered an enthusiastically received presentation at IoT DevCon 2018 outlining the unique benefits of Fog-based Machine Learning and Industrial IIoT.