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Every morning at the construction site down the street from my office, the day starts with a familiar hum. It’s the sound of the regular drone scan, when a small black quadcopter flies itself over the site in perfect lines, as if on rails. The buzz overhead is now so familiar that workers no longer look up as the aircraft does its work. It’s just part of the job, as unremarkable as the crane that shares the air above the site. In the sheer normalness of this — a flying robot turned into just another piece of construction equipment — lies the real revolution.

“Reality capture” — the process of digitizing the physical world by scanning it inside and out, from the ground and the air — has finally matured into a technology that’s transforming business. You can see it in small ways in Google Maps, where data is captured by satellites, airplanes, and cars, and presented in both 2-D and 3-D. Now that kind of mapping, initially designed for humans, is done at much higher resolution in preparation for the self-driving car, which needs highly detailed 3-D maps of cities in order to efficiently navigate. The methods of creating such models of the real world are related to the technology of “motion capture,” which drives movies and video games today. Normally that requires bringing the production to the scanners — putting people in a large room outfitted for scanning and then creating the scene. But drones flip that, allowing us to bring the scanner to the scene. They’re just regular cameras (and some smart software) precisely revolving around objects to create photo-realistic digital models.

In some ways it’s astonishing that we’re using drones on construction sites and in movies. Ten years ago the technology was still in labs. Five years ago it was merely very expensive. Today you can buy a drone at Walmart that can do real enterprise work, using software in the cloud. Now that it’s so cheap and easy to put cameras in the sky, it’s becoming commercially useful. Beyond construction, drone data is used in agriculture (crop mapping), energy (solar and wind turbine monitoring), insurance (roof scanning), infrastructure (inspection), communications, and countless other industries that touch the physical world. We know that “you can manage only what you can measure,” but usually measuring the real world is hard. Drones make it much easier.

Industries have long sought data from above, generally through satellites or planes, but drones are better “sensors in the sky” than both. They gather higher-resolution and more-frequent data than satellites (whose view is obscured by clouds over two-thirds of the planet at any time), and they’re cheaper, easier, and safer than planes. Drones can provide “anytime, anywhere” access to overhead views with an accuracy that rivals laser scanning — and they’re just getting started. In this century’s project to extend the internet to the physical world, drones are the path to the third dimension — up. They are, in short, the “internet of flying things.”

You might think of drones as toys or flying cameras for the GoPro set, and that is still the lion’s share of the business. But like the smartphone and other examples of the “commercialization of enterprise” before them, drones are now being outfitted with business-grade software and becoming serious data-collection platforms — hardware as open and extensible as a smartphone, with virtually limitless app potential. As in any app economy, surprising and ingenious uses will emerge that we haven’t even thought of yet; and predictable and powerful apps will improve over time.

Or you might think of drones as delivery vehicles, since that’s the application — consumer delivery — that the media grabs on to most ferociously when seeking click-generating amazing/scary visions of the future. Frankly, delivery is one of the least compelling, most complicated applications for drones (anything that involves autonomously flying in crowded environments is the black-diamond slope of technology and regulation). Most of the industry is focused on the other side of the continuum: on data, not delivery — commercial use over privately owned land, where the usual concerns about privacy, annoyance, and scary robots overhead are minimized.

Drone economics are classically disruptive. Already drones can accomplish in hours tasks that take people days. They can provide deeply detailed visual data for a tiny fraction of the cost of acquiring the same data by other means. They’re becoming crucial in workplace safety, removing people from precarious processes such as cell-tower inspection. And they offer, literally, a new view into business: Their low-overhead perspective is bringing new insights and capabilities to fields and factories alike.

Like any robot, a drone can be autonomous, which means breaking the link between pilot and aircraft. Regulations today require that drones have an “operator” on the ground (even if the operation is just pushing a button on a smartphone and idly watching as the drone does its work). But as drones are getting smarter, regulators are starting to consider flights beyond “visual line of sight” — ones in which onboard sensors and machine vision will more than compensate for the eyes of a human on the ground far away. Once such fully autonomous use is allowed, the historic “one pilot/one aircraft” calculus can become “one operator/many vehicles” or even “nooperator/many vehicles.” That’s where the real economic potential of autonomy will kick in: When the marginal cost of scanning the world approaches zero (because robots, not people, are doing the work), we’ll do a lot more of it. Call this the “democratization of earth observation”: a low-cost, high-resolution alternative to satellites. Anytime, anywhere access to the skies.

The drone economy is real, and you need a strategy for exploiting it. Here’s how to think about what’s happening — and what’s going to happen. We’ll start back at the construction site, a work environment in desperate need of what drones can provide.


The construction industry is the world’s second largest (after agriculture), worth $8 trillion a year. But it’s remarkably inefficient. The typical commercial construction project runs 80% over budget and 20 months behind schedule, according to McKinsey.

On-screen, in the architect’s CAD file, everything looks perfect. But on-site, in the mud and dust, things are different. And the difference between concept and reality is where about $3 trillion of that $8 trillion gets lost, in a cascade of change orders, rework, and schedule slips.

Drones are meant to close that gap. The one buzzing outside my window, taking passes at the site, is capturing images with a high-performance camera mounted on a precision gimbal. It’s taking regular photos (albeit at very high resolution), which are sent to the cloud and, using photogrammetry techniques to derive geometries from visual data, are turned into photo-realistic 2-D and 3-D models. (Google does the same thing in Google Maps, at lower resolution and with data that might be two or three years old. To see this, switch to Google Earth view and click on the “3-D” button.) In the construction site trailer, the drone’s data shows up by mid-morning as an overhead view of the site, which can be zoomed in for detail the size of a U.S. quarter or rotated at any angle, like a video game or virtual reality scene. Superimposed on the scans are the CAD files used to guide the construction — an “as designed” view overlaid on an “as built” view. It’s like an augmented reality lens into what should be versus what is, and the difference between the two can be worth thousands of dollars a day in cost savings on each site — billions across the industry. So the site superintendent monitors progress daily.

Mistakes, changes, and surprises are unavoidable whenever idealized designs meet the real world. But they can be minimized by spotting clashes early enough to fix them, work around them, or at least update the CAD model to reflect changes for future work. There are lots of ways to measure a construction site, ranging from tape measures and clipboards to lasers, high-precision GPS, and even X-rays. But they all cost money and take time, so they’re not used often, at least not over the entire site. With drones, a whole site can be mapped daily, in high detail, for as little as $25 a day.

Info Source:https://hbr.org/cover-story/2017/05/drones-go-to-work

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