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DTECH 2024: Looq AI’s Digital Transformation Empowers Engineering and Grid Resilience

AI-powered insights are enabling utilities to predict vulnerabilities and optimize grid performance at scale

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By Dominique Meyer, Ph.D. · Distributech 2024Dominique MeyerDtech 2024Engineering and Grid Resilience
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Key takeaways

01

AI-powered insights are enabling utilities to predict vulnerabilities and optimize grid performance at scale

Engineering and grid resilience were top of mind at DISTRIBUTECH 2024, and AI solutions paved the way for exciting advancements that will transform the industry.

Artificial Intelligence (AI) is revolutionizing the utilities and energy sectors by enhancing efficiency, reliability, and customer service. AI accelerates processes, improves decision-making, streamlines testing procedures in utilities, predicts system vulnerabilities, and optimizes resource allocation for better efficiency and cost reduction. AI's role in grid optimization, energy management in buildings, and enhancing grid security has demonstrated the tremendous capabilities of AI and how it can optimize operations and contribute to a more sustainable energy ecosystem.

The evolution of AI in the utilities and energy sectors is more than enhancing existing processes; it's about pioneering new ways to manage and utilize data for groundbreaking efficiency and sustainability. This shift towards a more data-driven approach highlights the importance of collecting vast amounts of data and the ability to analyze, understand, and act upon it in previously unimaginable ways. How can AI interpret this data and transform it into actionable insights that can lead to more informed decision-making and strategic planning?

MarketScale spoke with Dominique Meyer, Ph.D., the CEO & Founder at Looq AI, at DISTRIBUTECH 2024. Meyer detailed Looq's newly launched AI platform at DTECH2024, which strives to bring digitalization to the built world and empower engineering and grid resilience.

Dominique's Thoughts

"Yesterday, we launched our Looq AI platform, which is a way to digitize our built world.

It's composed of the "Q," the camera system that allows engineering companies, utilities, and surveyors to go around and capture high-accuracy survey-grade 3D data. Paired with our AI web platform, which allows them to navigate and interact with the data for all kinds of engineering integration and CAT analysis.

You know, we're just at the forefront of what AI will deliver in terms of bottom-line value for projects. And I think at Looq, we embody that at full scale. We believe in helping engineering company surveyors get the actionable data they need, reducing the amount of refilling they do, and making sure that they can drive the accuracy needs for the different requirements.

Does it serve a great stamping? Is it actual, cat design, civil 3D, right? Pull analysis for different software tools there. And the only way to do that is to be able to leverage that AI to automate these processes that were today, you know, and yesterday, still very manual. And that's where what we've done is build a technology that allows us to really automate the parts, drive bottom-line value in terms of time savings in the field back in the office, and enable key decision makers.

I think that's the important part at the end is really making sure we don't overrun in project timelines don't overrun in terms of mistakes, right, being able to have the actionable data so that high level decision makers can take the right decisions for critical human structure.

It's All About the Data

And I think in this industry, it's become common to collect a lot of data. At Looq, we believe in value way over the volume of data. Right? So, we focused on building the AI that extracts high-level information and semantics so that these decision-makers, these engineers, can get their work done to the pawn, and quickly.

I want to use an example very specifically. Like, a lot of our work in the distribution space looks at extracting information that is needed for asset management, information that is needed for polar analysis. All of these tasks today are still very manual. And as we bring that AI to the markets, we can automate the extraction of high-level asset information without having to manually go through terabytes and terabytes of home cloud data, being able to have a single list of, hey, these are the poles, these are the items on the poles.

Engineering and Grid Resilience

These are the geometric dimensions that mean that mortgages are done faster, which is today something that is very difficult with the scale of data that is being collected through other tools and technologies. I'm excited about bringing the technology to the electric utility markets. There is so much that can be done and will be done across the industry.

I think we're only starting to see, repeatable asset management taking place, right, before we're talking decades between data captured, between inspection of distribution, between transmission assets. Now, we're building the technology for the first time that allows us to do this at a yearly scale. That allows us to be able to capture the data you need to be able to really improve the grid resilience. And we're beyond excited to be working with industry partners to be able to provide and enable us to build a better and safer world."

Video TranscriptExpand ↓

Yeah. So, yesterday, we launched our look AI platform, which is a way to digitize our built world. It's composed of the queue, the camera system that allows engineering companies, utilities, surveyors to go around and capture high accuracy survey grade three d data. Paired with our AI web platform, which allows them to navigate and interact the data for all kinds of engineering integration and cat analysis. You know, we're just at the forefront of what AI will deliver in terms of bottom line value for projects. Right? And I think at look, we embody that at full scale. So we really believe in helping engineering company surveyors get the actionable data they need. Right? Reducing the amount of refilling they do, making sure that they can drive the accuracy needs for the different requirements Is it serve a great stamping? Right? Is it actual, cat design, civil three d, right, poloed analysis for different software tools there. And the only way to do that is to be able to leverage that AI to automate these processes that were today, you know, and yesterday, still very manual. Right? And that's where what we've done is build a technology that allows us, right, to really automate the parts, drive bottom line value in terms time savings in the field back in the office and enable key decision makers. Right? And I think that's the important part at the end is really making sure we don't overrun in project timelines don't overrun in terms of mistakes, right, being able to have the actionable data so that high level decision makers can take the right decisions for critical human structure. Yeah. And I I think in this industry, right, it's it's become common to collect a lot of data. And at look, we believe in value way over volume of data. Right? And so we focused on building the AI that extracts high level information and semantics so that these decision makers, these engineers can get their work done to the pawn and quickly. Right? I wanna use an example very specifically, right? Like, a lot of our work in the distribution space looks at extracting information that is needed for asset management, information that is needed for polar analysis. Right? All of these tasks today are still very manual. Right? And as we bring that AI to the to to to the markets, we are able to automate the extraction of high level asset information without having to manually go through terabytes and terabytes of home cloud data, being able to have a single list of, hey, these are the polls, these are the items on the polls. These are the geometric dimensions means that mortgage done faster, which is today something that is very difficult with scale of data that is being collected through other tools and technologies. You know, I'd look very excited about bringing the technology to the electric utility, markets. There is so much that can be done and will be done across the industry. I think we're only starting to see, repeatable asset management taking place, right, before we're talking decades between data captured, between inspection of distribution, between transmission assets. Right? Now we're building the technology for the first time that allows us to this at a yearly scale. That allows us to be able to capture the data you need to be able to really improve the grid resilience. And we're beyond excited to be working with industry park to be able to provide and enable, you know, us to build a better and safer world.

About the author

DM
Dominique Meyer, Ph.D.

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