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    Home»IoT»Utility Infrastructure Advances with AI
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    Utility Infrastructure Advances with AI

    big tee tech hubBy big tee tech hubFebruary 26, 2026003 Mins Read
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    Our energy infrastructure is close to failing—in fact, the ASCE (American Society of Civil Engineers) puts our energy grade at a D+. Narrowing in, the U.S. power grid includes an estimated 180–200 million distribution poles, which often have a lifespan anywhere between 50 and 70 years. Here’s the challenge. As with most infrastructure here in the United States, many of them are aging, and many are located in regions increasingly exposed to extreme weather.

    “Utilities need to make a difficult decision,” says Dominique Meyer, CEO of Looq AI. He says they ultimately need to decide whether these poles need to be replaced or not—and making that decision can cost a lot of time and money. Meyer tells me directly that North America’s distribution poles are even more substantial than earlier estimates, placing the total near 400 million.

    No doubt, utilities are under mounting pressure to meet state requirements for wildfire mitigation and storm hardening. As a result, accurate pole data has become a cornerstone of grid reliability. Yet much of this data is still gathered and processed through slow, manual, and inconsistent workflows—often requiring two people to collect the data. With the rise of AI (artificial intelligence) much of this is set to change.

    Looq aims to solve the challenge of spotty, inaccurate, and unreliable data, according to Meyer, by creating a full geometric engineering grade model of every single asset. qPole enables distribution designers and engineers to transform simple field captures into accurate engineering-ready asset models.

    Traditional field capture alone takes roughly 15 minutes per pole. Backoffice processing previously added another 15 minutes per pole, as engineers manually validate data. Now, that is all beginning to change. As one example of new technology, the qPole AI-assisted processing is completed in about 5-7 minutes per pole and automatically detects and models each structure and its equipment.

    Meyer equates the average saving of 23 minutes per pole to represent unlocking an estimated 19 million work hours saved annually in the United States alone.

    “We are enabling designers, backoffice work, to be way more effective,” says Meyer. “We’re essentially increasing their efficiency by over 60% in the backoffice, and that means that because there are not enough people that do this kind of work, those people that do it get more efficient. The industry feels a huge pain and relief around that.”

    The time savings is only one component of benefit for engineers. Field measurements are also accurate to under a centimeter, which helps derive correct construction requirements, avoiding overbuilt or unnecessary projects, ultimately saving money in the long run.

    Utility Infrastructure Advances with AI

    “That’s the real magic behind qPole is that automation piece in matching components to geometric and image perimeters,” says Meyer.

    Candidly, this is the type of innovation we need to build stronger, more resilient infrastructure here in the United States. If we want to raise our nearly failing grade, we must take swift action. Or we’ll see the report card virtually unchanged in three years.

    Want to tweet about this article? Use hashtags #construction #IoT #sustainability #AI #5G #cloud #edge #futureofwork #infrastructure #utilities #energy #utility 



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