The European research project START, coordinated by the Universidad Carlos III de Madrid (UC3M) and with the participation of important actors in the aeronautical scene, combines Big Data and Artificial Intelligence to develop algorithms that allow air traffic networks to be optimised during storms. This would improve the safety and timeliness of flights and reduce economic losses associated with delays and cancellations. Sometimes, during flights, aircrafts have to change their route (their flight plan) because of unforeseen events, such as storms. These meteorological phenomena, which may be accompanied by hail and lightning, are difficult to predict; they are known to appear in a wide area, but it is difficult to accurately predict when and where the storm focus will happen. START's objective is the development of research algorithms for optimising air transport networks in terms of their resilience (the system's recovery capacity) when facing this kind of disruptive phenomena.

Sometimes, during flights, aircrafts have to change their route (their flight plan) because of unforeseen events, such as storms. These meteorological phenomena, which may be accompanied by hail and lightning, are difficult to predict; they are known to appear in a wide area, but it is difficult to accurately predict when and where the storm focus will happen. START's objective is the development of research algorithms for optimising air transport networks in terms of their resilience (the system's recovery capacity) when facing this kind of disruptive phenomena. "The storms we are analysing in this project are convective, typically cumulonimbus (a type of cloud), which are very energetic and dangerous for an aircraft in flight, so pilots tend to systematically avoid them", explains the project's coordinator, Manuel Soler, from the UC3M's Department of Bioengineering and Aerospace Engineering. In addition to heavy rain, these storms often present hail, lightning, and thunder, and may eventually block airports or large airspace corridors.

Sometimes, during flights, aircrafts have to change their route (their flight plan) because of unforeseen events, such as storms. These meteorological phenomena, which may be accompanied by hail and lightning, are difficult to predict; they are known to appear in a wide area, but it is difficult to accurately predict when and where the storm focus will happen. START's objective is the development of research algorithms for optimising air transport networks in terms of their resilience (the system's recovery capacity) when facing this kind of disruptive phenomena. "The storms we are analysing in this project are convective, typically cumulonimbus (a type of cloud), which are very energetic and dangerous for an aircraft in flight, so pilots tend to systematically avoid them", explains the project's coordinator, Manuel Soler, from the UC3M's Department of Bioengineering and Aerospace Engineering. In addition to heavy rain, these storms often present hail, lightning, and thunder, and may eventually block airports or large airspace corridors.