CANARD is developing a drone system designed for inspecting an airport’s runway, taxiway and apron to provide pavement condition index (PCI) reports.
The use of drones reduces airside occupation time, while the use of computer vision algorithms makes the detection and classification of defects faster and systematic.
PCI reports are to be elaborated by airports regularly (typically every 12-24 months). Such inspections are included in ICAO regulations as ‘part of an aerodrome preventive and corrective maintenance programme’.
CANARD’s solution uses drones to reduce the time required for the fieldwork from several days to a few hours. This means that the occupation time for runway and other operational areas is dramatically lowered. For example, a 4km runway can be inspected in less than 30 minutes.
After the fieldwork, data is processed in a Cloud-computing platform so the computer vision algorithms developed can detect and classify all the defects of the runway. After the data is verified, a standard report can be generated to comply with regulations such as the ‘Standard Test Method for Airport Pavement Condition Index Surveys’ (ASTM D 5340).
The solution is paired with CANARD’s software platform and tools that provide complete control of the operations and detailed view of the acquired data, allowing for analysis of the results and feedback to the maintenance procedures.
In the same way as the rest of CANARD’s product lines, the company is developing this solution and operational procedures according to ICAO regulations and in collaboration with major airport operators and civil aviation authorities.