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FlightScanner

Research projects For Safety

FlightScanner has been developed in collaboration with LSTA. Its purpose was to use Flight data as a major source of information on risks. However, with classic analysis tools, no one can browse the millions of pieces of information available. By comparing all flights, machine learning algorithm will provide continuous and accurate measurements of risks  The risks are actually well known, but not systematically monitored. A metric is used for each risk, runway excursion, hard landing, take-off performance, etc. For example, the landing distance for each flight is compared to the actual runway length. Doing so, it is possible to separate flights with long and short landing distances. The innovation is that Machine Learning algorithms are able to determine what the main parameters are between two information sets. As the learning process is updated on a regular basis, it allowq to discover trends and can really perform safety assurance based on data.