Digital Transformation of Ground Handling

The ground turnaround is an essential process for the operations of any airline. Airports, airlines, and ground service providers work hand in hand with the goal of ensuring a smooth handling process between the landing and takeoff of the aircraft. An inefficient and operationally limited ground service provision can cause annual costs in the billions due to delays and interruptions in the turnaround process. Among other things, this might damage the passenger experience or reputation of an airline.

Ground service providers are currently facing major challenges like inefficient processes, increased complexity and staff shortages. By leveraging new technologies such as digital process optimization platforms, real-time data analysis including better data-driven linking of all stakeholders and the future use of AI, current problems can be solved, and the new way of working can be adapted. The digital transformation of ground handling is a key success factor.

If you are interested in digitally transforming and optimizing your tarmac operations with state-of-the-art technology, contact our experts. We will guide you through the key steps and factors to successfully implement innovative solutions and a tailored digitalization strategy for your ground handling operations

Find out how to optimize your operational processes through data driven solutions.

A central element of implementing state of the art technology is the integration of real time data emitted by multiple sources that have a significant influence on daily ground operations at airports worldwide. Examples include the direct transmission of updated passenger numbers via the Passenger Information System (PIS), real-time flight data via the Flight Information System (FIS), real-time weather updates and forecasts via the Weather Monitoring System (WMS) and ground handling management systems (GHMS). In addition to the data from these systems, it is possible to generate further data with new technologies and software that enables the digital visualization of processes on the apron. This includes, among other things, vehicle movements, arrival times of service equipment at the aircraft, and the detection of harmful objects on the apron (FODs).

To manage and work with such a large volume of data, a comprehensive IT architecture is necessary for data storage, transfer, and analysis. It will form a solid base for the digitalization of the complex ground handling system. A cloud-based solution is recommended, potentially incorporating a multi-cloud strategy from major providers to ensure real-time data analysis, scalability, cost efficiency, accessibility, and security.

To enable the digital transformation of ground handling and make the corresponding data usable, the following are required

1. Technological foundation with cloud systems
2. The appropriate technology to detect and digitally visualize processes on the apron
3. The integration of data from all essential systems and a corresponding data architecture to make this data usable and reliable
4. Trained experts among all stakeholders.

A currently trending state-of-the-art technology revolutionizing airport operations and ground handling is AI, more specifically computer vision. Computer vision allows AI to interpret and understand visual data, using digital images and video for deep learning-based object and person classification.

The main components of computer vision can be summarized as follows. The system captures images with cameras and sensors to collect visual data. This is followed by pre-processing of the image quality for noise reduction and contrast adjustment to evaluate images under various lighting and weather conditions. Next, feature detection and actual object recognition occur using deep learning models to identify and classify objects. This process is further supported by 3D vision, which involves the use of stereo and depth sensors to create a 3D model on a meta level. After this, a motion analysis of the objects is conducted to predict their trajectories. The final step is post-processing, where all sensor data is combined to enable decision-making.

All relevant data sources and technologies from a comprehensive, integrative perspective, such as the consolidation of information from various systems (PIS, FIS, WMS, GHMS) and technologies (e.g., computer vision) are used to give a unified overall picture. A meta level can be created to provide a transparent data picture by utilizing cloud environments for centralized storage, processing, and analysis of the collected data. This enables real-time decisions and coordination as well as high potential for centralized decision-making to optimize resources, reduce errors in operational planning, and enhance safety through improved monitoring and quicker identification of potential hazards. Performance management departments should collaborate closely, utilizing modern tools for process mining and analytics.