Discover the Power of Industrial IoT and
Fog-based Machine Learning

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.

Inside you’ll discover how you can…

Integrate Machine Learning with a wide array of IoT systems and projects
Overcome common roadblocks & challenges of Industrial IoT and Machine Learning
Use cutting-edge tools to facilitate the implementation of IoT and ML technology

Imagine a future where machines in the transport, energy, and industrial sectors achieve maximum efficiency.

Existing technology such as embedded sensors and other Industrial IoT (IIoT) technologies are already capable of gathering valuable data in the Cloud. This data can be analyzed and used to significantly improve the production process. In recent years, these industrial machines are becoming self-regulating and more intelligent through Machine Learning (ML).

But today, there simply is not enough time or network power to transmit all of the necessary ML data to the Cloud for processing. Situated between the legacy Edge and the Cloud is The Fog. This is a layer where the on-premise processing of data takes place. The Fog is the perfect solution for ML to provide real-time insights that can be used immediately; effectively known as Fog-based Machine Learning.

Now, imagine a future where your project uses Fog-based Machine Learning and Industrial IoT technology. With Fog-based ML and IIoT reaching maximum efficiency is becoming a real possibility.

Inside Ed’s presentation you’ll find real-world examples of IoT projects in the industrial space where Fog-based ML has been used for several applications such as image classification, convolutional neural network processing, data reduction, and much more…

Download the comprehensive presentation on Fog-based ML and IIoT
Learn from a real IIoT 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.