The Flight Path of Aerial Data Processing


Expected to more than triple in size to an estimated USD 63.6 billion by 2025, the drone services market is quickly becoming one of the hottest areas for technology innovation for the built world.

Companies like DJI and other top consumer drone manufacturers have reduced the barrier to entry for enthusiasts and enterprises alike. Not only have drones themselves progressively improved over recent years, but the remote sensing equipment and cameras attached to these UAVs, such as LiDAR, are becoming less expensive and more powerful.

Many civil engineering and land surveying companies have already taken advantage of this increased accessibility by either integrating enterprise drones into their core business models or leveraging them to supplement their data acquisition processes. But, as is often the case with burgeoning technologies, these solutions and their end-users eventually experience growing pains. There is no question that drone technology and aerial intelligence have transformed the landscape for these fields, but solutions like these bring about problems of their own that must be addressed.


Problem: A growing backlog of unprocessed aerial data

The largest bottleneck for companies that utilize drone technology is not in data acquisition but in data processing. Making sense of aerial data often requires specialists who must manually process every acre, which is cost-prohibitive and unacceptably slow. At the current pace of aerial data acquisition, we are on track to far exceed what is realistic for humans to process in a timely manner. Traditional aerial data processing methods simply cannot keep up with growing supply and demand.

As a consequence, companies find themselves with a backlog of hundreds or thousands of acres of data and are unable to process it as quickly as it is collected. This ongoing cycle of accumulated work and unprocessed data issues impacts the bottom line, dulls competitive edge, and prevents them from completing projects on schedule. What these companies need is a scalable solution that provides results that are within project constraints and have a quick turn-around time.


Solution: Implementing AI to speed up manual processes

One of the most promising solutions to this data backlog issue is the use of AI and deep learning to automate the manual drafting process. These technologies allow for scalable solutions to aerial data processing at a fixed cost to users. What previously took specialists days to complete now takes an AI-powered model a few hours. No more unexpected delays in data processing that push back project deadlines and eat away at profits. Moreover, instead of processing projects one after the other, those hundreds or thousands of acres sitting in the backlog can now be processed concurrently.

Implementing deep learning solutions and AI-powered models from scratch is not easy. The growing market need for such tools has resulted in many companies developing software to address the need for fast and cost-effective aerial data processing. AirWorks is one such company that recognized the inherent problem of an overabundance of aerial data with no scalable method of processing it. Instead of relying on slow and expensive manual drafting, we leverage artificial intelligence and computer vision to automate processes within an industry that often relies too heavily on manpower to make sense of aerial data.

By applying new and innovative solutions to old problems, we address the pain points that have been plaguing civil engineering and land surveying firms that struggle to process the exorbitant amounts of aerial data they collect. Our platform produces engineering plans that are as accurate as conventional drafting methods, thanks to our use of AI-powered algorithms, which were designed with scalable aerial data processing in mind.


With AirWorks, processing aerial data is as easy as uploading your imagery and downloading your results in three easy steps. To learn more, visit our website at