Remotely piloted aircraft (drones) are an excellent tool for creating new usable data. Airborne gas and particle sensors inevitably record millions of readings in a matter of minutes. A single 30-minute survey flight can easily capture gigabytes worth of pictures. An aerial surveillance mission will go even further and break the terabyte barrier in terms of recorded footage. RPAs are new players in the big data boom. In fact, very effective ones.

Scout Aerial understands the challenges of managing complex data sets, not only in terms of the actual collection, but especially the analytical and intelligence based aspects that can be extracted from them. This capability has allowed us to add significant value to our services, helping our clients to make better decisions, based on actual data, and ultimately improve their performance.

We currently partner with a number of organisations to develop new RPA capabilities and remote sensing technologies. A considerable amount of time and resources have been invested in integrating artificial intelligence, computer vision and machine learning algorithms into our airborne sensors. The results are exciting and motivate us to find out what is just over the horizon.

A few examples of what we have been developing recently.

Shark Detection

Spotting dangerous sharks along the coast through computer vision, machine learning and fit-for-purpose, airborne GPU computers.

Shark Detection System

Gas and Particulate Matter Sensors

Early detection of bush fire through the analysis of CO, CO2, PM2.5, PM10, humidity and temperature data collected by networked ground and airborne sensors.

Gas and Particulate Matter Monitoring Dashboard

Animal Detection and Counting

Using computer vision and machine learning to identify different types of animals, numbers, sick animals and extract georeferenced statistics that become actionable tasks.

Animal Detection and Counting
  • Data collection and analytics
  • Algorithm development
  • Machine learning and computer vision
  • Custom sensor integration