Residents can use the air traffic platform to stay up to date on current operating aircraft runway use and sudden schedule changes

Schiphol Group has recently launched its new ‘Notifly’ app that gives residents in the surrounding areas an insight into air traffic in their region, by supplying them with real time information via the platform.

Those living in the surrounding zones can use the software to gain access to expected traffic and runway use.

Residents can also allow the app to send notifications directly to their devices in the case of sudden changes, such as bad weather conditions.

“I asked the aviation sector to create a ‘weather forecast for flights’ for local residents,” said Cora Van Nieuwenhuizen, Dutch minister of infrastructure and water. “I am pleased that this has been achieved with today’s launch of the Notifly app. Predictability is important to the people living close to Schiphol.”

Dick Benschop, president and CEO of Royal Schiphol Group, added: “Transparent communication and information contributes to improving the quality of the living environment. Notifly meets the neighbours’ need for more predictable air traffic.”

A map is also provided so the public can see live traffic updates, as well as information on the aircraft, which runway is being used and where flights are departing to and arriving from.

When the group began developing the app, it looked into the needs of the local residents. It was found that they wished for more predictability regarding communication.

Notifly has been working under a trial period over the past few months in preparation for its launch. Following this, the company has said that it has been working alongside those within the community to expand the software’s operating range.

Using a self-learning algorithm, it is able to make location-specific air traffic predictions, according to the group. The model incorporates radar and weather data for the Royal Netherlands Meteorological Institute, which then searches for similar conditions in other regions and takes the average.

As the model learns independently, it is able to process new information and learn from this to create a more accurate forecast.