TXT Group AVIO Project | Innovation & Research

The impact of technologies such as Digital Twin (DT) , Artificial Intelligence (AI) and eXtended Reality (XR) is progressively increasing; in particular, they are and will be fundamental to support the improvement of operations efficiency in complex environments and systems, and airports are a perfect example of this.
Through the study and prototyping of a real-time DT of the Milan Bergamo Airport that collects and integrates data from various sources, including algorithms and models of vision and artificial intelligence that will be developed, the AVIO (Airport Virtual Infrastructure Operation) project aims to use these innovative technologies to improve the resilience of the airport, in particular ground handling, also with respect to rare and extreme weather events through improved Situational Awareness and better decision-making.

Co-funded by the Ministry of Enterprise and Made in Italy through the funds for Innovation Agreements (PNRR), the AVIO project aims to develop a digital twin of an airport (Milan Bergamo - BGY) that collects real-time data on the position of aircraft, vehicles and operators using machine vision modules. The digital twin will be used to display relevant information to airport operators in various ways to support efficient ground operations.
The project is the result of a collaboration between four important players in the field of software engineering applied to the aviation sector: SACBO (project coordinator and manager of Milan Bergamo Airport - BGY) together with a large digital enabler company such as TXT e-tech, the Sorint Group Business Unit focused on the development of Advanced Analytics and IoT solutions such as Sorint.tek, and an important research institution such as the University of Pavia.

The ultimate goal is to improve airport safety and efficiency by providing airport operators with accurate, real-time information on the positions of aircraft, vehicles and operators.
This information will help operators make more informed decisions on how best to manage the flow of traffic on the ground and respond to disruptive events. This is achieved through four different modules:

Objective #1: Computer Vision
The machine vision module for transforming video streams from cameras that frame the airside into structured information about the position and activities of the various actors present such as aircraft, vehicles and ground operators.

Objective #2: Data IoT Hub
The data collection and integration module (Data IoT Hub), dedicated to collecting and integrating data from various sources, including the machine vision module, GPS systems and other sensors. This data will be used to create a real-time model of the airport environment.

Objective #3: Digital Twin
The digital twin for visualising the data collected and integrated by the IoT Data Hub to present relevant information to airport operators in various ways. This could include 2D and 3D maps, augmented reality overlays and other visualisations.

Objective #4: Virtual Reality (VR)
The simulator to train ground operators. The digital twin will also be used to train ground operators through a virtual reality (VR) experience and a simulator. This will allow operators to practise responding to disruptive events in a controlled environment before they occur in the real world.

Although airport digital twins have been developed for other airports, the aims of this project are unique in that it will collect and merge information from multiple sensors, including video sources, into a single coherent multimodal representation and use this data stream to feed a realistic simulator of airport operations. The aim is highly relevant as it will raise the efficiency and safety standards of the airport and provide a national and international benchmark of what can be achieved with the latest and most innovative digital techniques.

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