The collection of geodata is undergoing a fundamental transformation through the use of drones and artificial intelligence. As manual processes are increasingly automated, digital twins and predictive models enable precise condition monitoring. For decision-makers in industry, the “Drone as a Service” model offers new economic opportunities to plan complex infrastructure projects more efficiently and make informed decisions based on real-time data.

The way we capture and understand our environment has changed dramatically. Where terrain was once painstakingly surveyed and rigid, two-dimensional maps were created, interactive databases and digital twins now dominate the landscape. Information from a wide variety of sources is fused into GPS-referenced real-time situational awareness maps. Drones and AI algorithms have become virtually indispensable for collecting and processing the necessary data.

Data is a tricky thing. If it’s missing, subsequent processes are like flying blind. However, if there’s too much of it, processing it adequately becomes a real challenge, and the risk of not seeing the forest for the trees increases significantly. Where once a large number of personnel and just as much time had to be allocated, the collection, processing, and interpretation of even the greatest flood of information are now

largely automated. This profound transformation is largely based on optimized methods for data acquisition as well as rapid advances in the fields of artificial intelligence (AI) and machine learning (ML).

Day by day, the global collection of geodata grows, which can then be used to train AI algorithms (Photo: Jimmy Tran – Adobe Stock)