Aerial surveying uses drones to capture high-resolution, geo-tagged imagery of mine elevations and depressions. The data is uploaded into photogrammetry software to generate a 2D map, point cloud and 3D model to assist mining managers in determining mine performance and monitoring material volumes.
From the data captured, multiple data outputs are possible including: 2D maps, point clouds, 3D models, Contour Maps, Digital Terrain Models and Digital Surface Models. Data can be utilised for stockpile management, asset management, mine monitoring, operational planning, mining exploration and to assess mine performance.
Drones can also conduct BVLOS (Beyond Visual Line of Sight) flights for large scale surveys.
We supply a number of telecommunication providers with low-risk, detailed drone inspections as a regular part of their asset lifecycle programmes. This ensures asset longevity for optimum and uninterrupted service to customers.
Where telco or tower inspection used to require abseiling, harnessing and scaffolding, aerial drone analysis improves employee safety, lowers operational costs and provides a richer data set. Coupled with our cloud analytics software, SmartData, we provide a powerful digital solution for tower owners.
Utilising aerial data can also bring incremental revenue generation to each telecommunication tower by maximising the current capacity.
Aerial intelligence has multiple applications in the power and renewables sectors, enabling the safe inspection of assets such as towers, power lines, solar panels, wind turbines and dams.
National Drones provides a number of power operators and suppliers with low-risk, detailed drone inspections to assist with their asset lifecycle and asset risk management programs.
As part of the inspection process, drones can be equipped with LiDAR (Light Detection and Ranging) technology. This is standard in the regular inspection of power transmission lines to assess line sag and the proximity of vegetation. This gives energy providers the ability to manage assets more proactively and predict potential outages.