• • • INTERVIEW • • •
HOW IOT IS CHANGING THE WAY ENGINEERS MANAGE ELECTRICAL SYSTEMS
BY VALTERS SKRASTINS, HEAD OF IOT HARDWARE, LMT IOT A
s electrical infrastructure becomes increasingly connected, IoT, edge computing and AI are reshaping how
engineers monitor, maintain and manage equipment. In this Q&A, we speak to Valters Skrastins,
Head of IoT Hardware at LMT IoT, to explore the challenges of connected systems, the role of edge intelligence and how technology will influence the future of electrical engineering.
1. As electrical infrastructure becomes increasingly connected, how is the convergence of IoT, edge computing and industrial communications changing the way engineers design, monitor and manage electrical systems?
A long time ago, before predictive maintenance was a known term, engineers had very limited ways to understand their product. They were limited to their test lab, with a finite number of test
cases, a finite number of test hours and very aggressive test conditions, yet they had to forecast long-term behaviour based on these limited tests. The next touchpoint with the equipment was often a malfunction, where engineers faced the end result and tried to guess what went wrong and how to fix it in the next product revision. Today, the entire equipment lifetime has become
a test period with more realistic conditions, far more hours and more relevant test cases. Engineers can now draw data-backed conclusions about what led to equipment malfunction and fix them in the next revision without dozens of product respins.
2. What are the key challenges involved in integrating IoT connectivity with existing electrical infrastructure and legacy equipment, particularly where systems were not originally designed for digital monitoring or remote access?
There are a number of technical challenges, such as: – Reading diagnostics data from the equipment using legacy protocols. Custom protocol stack development is often needed.
– Physical space and dimension restrictions. – Limited number of connectivity technologies available at the location.
36 ELECTRICAL ENGINEERING • SEPTEMBER 2026
Business challenges can also cause more problems than the technical ones. For instance: – OEM or equipment owner does not allow certain technical manipulations needed to add monitoring or remote access.
– Monitoring reliability of almost five nines is expected, but not always possible within the budget and available infrastructure.
3. How can engineers move beyond simply collecting data from connected electrical assets and use IoT-generated data to support predictive maintenance, identify developing faults and improve the overall reliability of electrical systems?
Someone has to analyse the data. Collecting
data is a critical prerequisite for predictive maintenance. However, data alone is just a bunch of bits in your database if it isn’t analysed properly. I believe edge AI has huge potential to analyse data and decide what constitutes a good or bad operation of the equipment. You can train it well enough to detect early-stage malfunctions while prevention is still possible. Moreover, it reduces the load on connectivity, since most processing happens at the edge and only a limited amount of data needs to be sent to the cloud.
electricalengineeringmagazine.co.uk
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