Zain Drone’s software was created to organize, process, and visualize data from UAVs. As an evolution to the way we visualize drone data today, we created the software to be data agnostic, giving it the ability to ingest any type of data and overlay it on top of other applications such as maps, vectors, and 3D models.
Having data-agnostic software is important when managing large projects with a vast variety of data types. A single asset can have a multitude of inspection datasets attached to it, for example, overhead lines inspection requires visual data, infrared data, UV, or corona datasets, in addition to LIDAR data.
Having all data in digital form has immense benefits, provides single-point access to all historical data and previous conditions of the assets in a single click or touch of a screen. This is especially important for well-informed maintenance decisions and increased asset reliability. Another important factor is that once shifted to digital data, enterprises can benefit from artificial intelligence (AI) and simulation technologies.
A custom AI application can be trained to accurately detect various faults on all new inspections in a matter of minutes. Simulation profiles utilize historic data and rate of degradation to predict the state of the asset in the future. By assessing the rate of degradation and fault intervals, simulation profiles can create predictions on how the asset will perform in the future, giving decision makers better predictive maintenance tools than earlier technology.
Using our visualizer and custom algorithms such as “data fusion”, we give our customers the ability to overlay visual, thermal, and UV data on top of a digital twin of the asset created with LIDAR data. This generates a virtual inspection environment that creates inspection points on top of digital twins, essentially replacing PDF reports with a digital report that can be viewed from any mobile device or computer.