Data in the Sky

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Drones may look like toys (like the small, remote-controlled one your kid flies into the trees the third day after Christmas, never to be seen again — true story). But drones have been buzzing through the skies for enough time now that some real commercial applications are starting to come to light.

Forget about Jeff Bezos’ dream of small-package delivery for a second. That is not going to happen at scale anytime soon. Drones are not interesting because they are flying robots. Drones are interesting because they are data-capture devices.

Drones are eyes in the sky, giving businesses data on their real-world operations from on high. They are like mini-satellites flying at tree level, producing sub-5-centimeter resolution imagery of the planet. That sky-based data is being processed and analyzed in increasingly sophisticated ways — with machine learning playing an increasingly crucial role.

Real-World Applications for Drones

Industries where drones are starting to make an impact tend to have large, outdoor sites such as mining, construction, forestry, oil & gas, and shipping. Some commercial applications that rely on drone data include:

• Creating 3-D models of land masses at mining sites
• Estimating and verifying outdoor stockpile volumes at manufacturing plants
• Terrain mapping and tree-counting
• Identifying and tracking heavy machinery and equipment
• Detecting gas leaks at chemical and energy facilities
• Comparing the construction progress of a building against the CAD models of the design

Two commercial drone startups that exemplify this sky-data approach are Airobotics and SkyCatch. (Both have presented to our IoT Global Council). Airobotics is an Israeli-based startup that recently got clearance in that country to fly their autonomous drones. In industrial application, they use computer vision to estimate how much sulfur, sand or other manufacturing materials are left in a company’s stockpiles. In another, they can keep track of equipment on a site.

SkyCatch creates self-piloting software for a variety of standard drones, with a focus on data capture and analysis for the enterprise. SkyCatch is also using computer vision and machine learning to identify things like earth-moving equipment on a work site or to identify vegetation in an image and remove it to create 3D models of the underlying land. One customer, Komatsu, uses drone data from SkyCatch to instruct its self-driving bulldozers on how and where to move earth. Another construction customer uses drone data to compare concrete pours and the exact location of building additions to the architectural CAD models to detect variations to the plan as they occur.

These are just a few examples of how drones, computer vision, and machine learning are combining in powerful ways to give companies new vantage points from which to see their operations — and, in fact, give them the ability to see things they never could before.

Deep Links:

Watch Amazon’s Prime Air drone make its first demo delivery in the US — While the technology is already here, drone delivery is still strictly for demos in the U.S.

Airobotics scores authorization to fly autonomous drones in Israel — Drone regulations are evolving more quickly in other countries like Israel. Success in smaller countries could pave the way for similar regulatory changes here.

This Airobotics ‘homing’ drone flies and lands without any need for a human — Some background on Airobotics and its autonomous drones. Check out the video in the article.

Microsoft invests in real-time maps for drones, and someday, flying cars — AirMap raised $26 million for real-time mapping of drone flight paths, allowing drones to broadcast their positions to each other while in flight.

John Deere Floats Drones as the Next Big Tool for Construction Workers — In another indication of where this market is headed, John Deere recently partnered with startup Kespry to offer aerial data to the forestry and construction industries.

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