Leveraging the Industrial Metaverse to transform and future proof operations
Likened to small cities, airports are incredibly complicated environments with many moving parts that all need to be well coordinated to ensure smooth operations. Much is required for a flight to complete boarding and take off in time. From proper passenger traffic management in security terminals to efficient aeroplane pre-flight technical assessments on the ground. In the meantime, the availability of facilities in and outside the airport play a critical role in a passenger’s experience and route towards the gate.
With the shutdown caused by the pandemic forcing many airports to reduce personnel,
understaffing remains an issue as both airlines and airports struggle to fill vacancies.
The issue of understaffing is further exacerbated by the fact that there is an unexpected boom in the number of passengers wishing to make up for lost time during the pandemic resulting in delays, queues and frustrated travellers.
Worldwide inflation is impacting the costs of running an airport. Airports and airlines will be seeking ways to reduce expenditure and improve maintenance measures to increase the lifecycle of products and facilities.
Sustainability is a pressing concern across all industries and commercial aviation is not immune. Inefficient operations such as delays in which passengers are held in the plane on the tarmac or flights having to circle before they can land all contribute to the sector’s carbon footprint.
By treating an airport as a smart-city, equipped with smart digital twin solutions, airport managers can foresee traffic congestion or weak points in their processes and act to avert risk. Similarly, efficient airport management translates to happy travellers who are less stressed. Let’s look at advances being made in the sector.
Aviation giant CAE's SSE produces a comprehensive 3D digital twin of an airport’s entire infrastructure and systems and can be scaled to incorporate millions of entities. The platform integrates key data to support situational awareness and decision-making.
The CAE SSE models elements of the behaviour, environment, architecture and can incorporate external factors such as weather, intel from connecting airports and public transport networks in order to consider various scenarios to support data-driven decisions.
It provides teams with data and insights synthesised from multiple departments or functions for optimal decision-making. It offers a single platform to be able to unify datasets from the organisation to facilitate common understanding and optimal decision-making.
