Designed For Use By The Insurance, Roofing And Building Inspection Industries

Loveland Innovations, maker of advanced data analytics solutions and drone-based data gathering tools announced the launch of the beta version of IMGING Detect, a deep learning engine built specifically for drone-based inspections.

Deep learning is an advanced approach to artificial intelligence (A.I.) that allows IMGING to “learn” as it gathers more data, which makes IMGING more sophisticated and accurate each time it’s used. This has vast implications for everything from damage detection to object and materials detection and beyond. The proprietary damage detection algorithms in IMGING are the most advanced currently available to the drone-based roof, building and property inspection space.

“We’re excited about damage detection, but we’re more excited about deep learning. The framework we’ve built completely steamrolls anything else currently available,” says Jim Loveland, CEO and Founder of Loveland Innovations. “A lot of others claim they’re data analytics companies, but their technology really doesn’t live up to the promise. We didn’t take the easy route the way others have. Instead, our team has spent the last two years designing and building the most powerful deep learning system in the property inspection space. This release isn’t just about faster inspections and more accurate estimates, it’s about re-thinking the industry’s entire approach to inspections and estimating. Deep learning is dead center in that vision.”

With the new deep learning framework, IMGING users will be able to inspect a roof or property with an automated drone, automatically find damage and materials, and create detailed estimates using one tool, all without ever stepping foot on a roof. Currently, IMGING Detect makes estimating much easier by automatically highlighting areas of damage on inspection images. The initial build can recognize wind-blown shingles and hail hits, including fringe hail, on composition rooftops.

“It’s a common misconception that all A.I. is the same, but it’s not,” says Leif Larson, CTO of Loveland Innovations. “Deep Learning is built on a neural network capable of learning the same way a human brain learns. For instance, a true deep learning framework doesn’t just look for patterns in pixels that sort of look like hail damage, it’s trained to analyze images closely and determine with measurable confidence where hail damage is. We took our time to develop a deep learning framework because it gets smarter over time as we train it, and because we can build so much more on top of it. It’s just a better way to analyze the data.”

Larson also notes that while this technology is itself a huge milestone, it’s just the first of many uses Loveland Innovations has planned for deep learning in IMGING. “The deep learning framework used in IMGING Detect is foundational technology we’ve built to provide a visionary toolset to anyone who does inspections. We’ll give IMGING the ability to find multiple kinds of damage, to analyze property risks, determine materials, detect objects, and make the process of building and property inspections much more streamlined. There’s really no limit to what this technology can do, and we’ll continue rolling out new features fast,” he says.

IMGING Detect is a part of the IMGING Inspect solution and is included at no additional cost. Users can buy IMGING as a complete software + kit solution or as an app to run on their existing hardware. Those who already have a DJI Phantom 4 Pro drone and cellular-enabled iPad can buy the software or hardware they need to start improving their inspection and estimating process.

(Source: Loveland Innovations news release. Screenshot image from company video)

FMI: www.lovelandinnovations.com/news/ai-machine-learning-deep-learning-insurance