Technology Description
Airports are complex operational environments that generate increasingly vast amounts of data. Airport operators have attempted to make sense of all this data, but as data points become more connected, accounting for every variable can be virtually impossible. One way to help make sense of all this is through digital simulation of real-world assets. A digital representation—or digital twin—of airport assets can help operators prepare, make decisions, and solve issues in real time.
IBM defines the digital twin as “the virtual representation of a physical object or system across its life-cycle. It uses real-time data and other sources to enable learning, reasoning, and dynamically recalibrating for improved decision making.”[1] Digital twin technology is heavily reliant on the Internet of things, artificial intelligence, 5G (fifth generation), and augmented reality to operate at full potential. Digital twin solutions can be enabled by different technologies depending on the use case—from advanced predictive analytics to interactive digital representations of real-world assets. Advancement in computing power provides users with accurate digital representations of increasingly complex assets. Airport operators may one day be able to digitally represent airport infrastructure, passenger flow, and operational processes to see the impact of changes in real-time.
Through the use of digital twin technology, airport operators can monitor airport performance, perform in-depth what-if analysis, and forecast how changes may affect the airport environment. Digital twins could also play an integral part in various aspects of the airport operator’s roles, including designing and decision making. In the future, digital twin technology may also be used in project planning to better understand the types of impacts associated with a new project.
Based on current knowledge, digital twin technology is placed within the Intermediate Transformation Tier. This is due to the airport industry’s understanding of process improvement and forecasting techniques, although in different forms. Conversely, airport organizations only need to be concerned with the internal deployment of digital twin solutions and not how external use may impact the airport organization.
Impacts
Until real-world deployments begin, airport operators will likely not understand the full impact that digital twin deployments will have on their airport environment. This article outlines many of the high-profile impacts that airport operators may expect from digital twin technology as their usage increases. Following the impact list, two notable impacts are detailed further.
Impacts
Management/Operations
- Extensively connected device deployments not in current budgets
- New budgetary considerations for infrastructure upgrades
Technical/Infrastructure Readiness
- Strategic deployment of connected devices to facilitate system operation
- Improved data analytics and visualization software solutions
- Improved network capabilities to increase bandwidth and speed needed to support these solutions
Process/Skill Set Changes
- Staff with advanced data analytics and data visualization skill sets to properly leverage and maintain a digital twin solution
- Inclusion of digital twin data into decision making and project planning processes
Passenger Experience/Passenger Process
- Provides a better understanding of process change and how it may impact the passenger experience
- Identifies operational issues in real time and determines the best option to resolve the issue
- Improves overall airport process and operating performance through data-driven decision making
Security/Safety
- Improved ability to identify security issues
- Proactive responses to emergency events
Airport Design/Construction
- Influences future airport design initiatives, and new design projects must take previous digital twin data into account
Legal/Risk
- Data ownership considerations
Featured Impacts
Improved data analytics and visualization software solutions: Digital twin solutions offer new opportunities for organizations to deploy data analytics and data visualization software tools. These improvements stand to drastically impact how current data analysis is conducted within airports. Airport organizations must have the proper computing infrastructure in place to analyze data streams and properly visualize the results. At this time, further advancements in high-powered computing infrastructure are required to drive down the cost for an airport to pursue implementation.
Data ownership considerations: Airport operators must understand the data ownership policies outlined in the contracts for the equipment they purchase. In some instances, it may be the vendor who has access to the data streams produced and requires airport organizations to pay for access. As data access is vital to the operation of a digital twin solution, access restrictions may impact the chosen connected solution. Organizations must either budget for necessary data access or negotiate access to data within the procurement contract.
Attributes
To better understand digital twin technology, airport operators should gain a better understanding of its specific attributes. This article explores the operating factors of digital twin and some of its usage characteristics. Understanding these attributes will help airport operators determine applicable use cases for digital twin and how their organization can support potential solutions.
Computing Power and Hardware Requirements
High computer and graphics processing power are needed for operating sophisticated digital twin solutions. A digital twin must also possess the machine-learning capabilities necessary to process, analyze, and make predictions on data generated by the environment. Visualization technology must support some of the more advanced data analytics techniques needed to visualize historical, live, and future data streams.
Implementation Concerns
For an airport organization to implement digital twin technology, several requirements must be in place within the airport. An extensive network of connected devices and equipment must supply the data; sophisticated machine-learning software must be in place to process incoming data streams; and the computing power must be available to leverage the data taken in. Airport organizations will need to invest heavily in upgrading their current technical infrastructure to support digital twin solutions.
Effect on Other Program Areas/Technologies
Digital twin as a solution not only is heavily reliant on other enabling technologies but also produces results that will directly impact airport operations and technology decisions. This theoretically could place digital twin technology at the center of airport operations. As digital twin technology gains popularity with airport organizations, decision-makers will rely more heavily on the data that is output by the system when designing processes and incorporating new technology solutions within the airport.
Use Cases/Business Effect
With every new or emerging technology, there are two basic questions an airport operator asks: “How can my airport use this?” and “How does this affect my business, even if my airport doesn’t wish to use it for our own benefit?” This article provides answers to both of these questions, addressing the airport uses cases and business effect of digital twin technology.
Use Cases
As digital twin technologies advance to a point of being cost-effective with widespread adoption, potential use cases become available for airport operators to incorporate into their organizations.
Process Monitoring
An airport organization can simulate a digital recreation of airport processes, not only providing predictive metrics about a process but also allowing operators to monitor processes in real time. Performance metric thresholds and key performance criteria can be tracked, with the system alerting users to drastic changes in data. If they choose to monitor key processes and equipment across an airport, airport decision-makers can also monitor the operational health of the organization.
Simulated Performance Forecasting
One of the most notable features of digital twin solutions is the opportunity to simulate processes and equipment within a digital environment. This digital recreation is developed based on machine-learning tools used to analyze past and present data streams from connected items. The machine-learning capabilities of the digital twin technology can then use that data to forecast how the process or piece of equipment will operate into the future and when encountering various factors. This stands to help airport operators better understand what processes changes may mean for the whole airport environment and resolve potential problems before they are encountered in the real world.
Equipment Status
Digital twin solutions can provide airport operators insight into equipment performance and lifespan. Airport operators can update devices with the necessary connectivity to identify performance issues, manage the equipment remotely, and even predict potential issues with maintenance before the equipment experiences failure. A digital twin solution provides an airport organization with a cohesive view of the airport environment, allowing decision-makers to enact cross-functional decisions across multiple operating areas at once.
Business Effect
Unlike some other technologies noted in this Publication, deployments of digital twin technology at an airport are not likely to happen unless they are directly initiated/driven by the airport organization. Therefore, airport operators who chose not to implement digital twin technology should not expect to face any business effects. However, as digital twin technology is developed further and use cases are better understood, this article will be updated with this new information.
Tiered Approach
Airport operators interested in new or emerging technologies, such as digital twin, will differ in their levels of risk tolerance. Some organizations are comfortable at the forefront of technology and have the resources to support innovation. Other organizations are interested in simply exploring how they can use digital twin within their limited resources.
This article takes a tiered approach to digital twin technology, providing use cases that are separated by the following innovation tiers: Reactive, Strategic, and Innovative.
Reactive
Queue Process Performance Simulation
Airport operators can develop smaller-scale digital twin solutions that provide insight into the data from the airport organization. Through strategically placed Internet of things devices, airport organizations can understand the performance of queuing areas within the airport, notable security areas, or the check-in hall. While only a small portion of airport processes, queue monitoring solutions are well tested and have a wealth of project data to gain insight from. Monitoring data from queueing processes can be the first step to organizations leveraging the wealth of processes and equipment data within the airport.
Strategic
Passenger Processing Simulation
Airport organizations looking to move past basic queue performance monitoring can begin to integrate various data sources from across the airport to gain a more comprehensive view of passenger processes. Flight information, check-in time, baggage intake, passenger flow, and queue monitoring metrics can begin to help airport organizations better understand their passenger’s habits, along with the factors that influence those habits. Airport organizations can use this data to predict how changes in the environment can impact aspects of the passenger process.
Virtual Equipment Performance Simulation
An airport organization can also begin to track and forecast the use of airport equipment through the correlation of data from passenger processing equipment, baggage handling systems, and location monitoring solutions. Machine-learning techniques can allow an airport operator to view the status and performance of equipment across the airport property. Along with the current status, airport operators can be alerted to equipment outages and future issues before they become a significant problem.
Innovative
Campus-Wide Equipment and Process Simulation
As digital twin solutions become more sophisticated and airport organizations begin implementing new computing infrastructure, more advanced digital twin operations become available. Airport operators can combine and correlate data sources—such as building infrastructure and monitoring sensors—from across the airport property to develop a digital recreation of those assets within a digital twin solution. Operators can then begin to forecast performance and process adjustments and take a comprehensive approach to viewing the airport environment.
Industry Status
Exploring digital twin technology deployments in both aviation and non-aviation industries can provide airport operators with a better understanding of the technology as a whole. This article outlines the current state of digital twin technology from both perspectives.
Aviation Industry
Airplane Equipment Testing
Airlines are using this technology to test aspects of airplanes before entering production. This provides insights early in the process to save time and resources. Airline engineers can also use digital twin technology to forecast equipment performance under various operational scenarios.[2]
Simulated Airport Environment
Real-time data visualization of a digital simulated airport environment assists with monitoring performance around airport systems and processes to identify issues and areas for improvement.[3]
Non-aviation Industry
Product Prototyping
Companies are using digital twins to better understand product performance and attributes across a range of scenarios, helping to reduce product development time and identify potential product issues.[4]
Automotive Industry
The automotive industry is combing vast amounts of historical data with advancements in a computing infrastructure to develop digital twins of their product offerings. The hope is to improve the speed and efficacy of prototyping efforts when developing vehicles.[5]
Technology Interaction
Technology solutions may enable or be supported by other types of technologies. In some cases, the advancement of one technology may be vital to the effective use of another. This article highlights some of the high-level ways that digital twin technologies may leverage the functionality of other technologies or be used to enhance the functionality of another technology. As solution development continues, integrations with other technologies may become more evident.
Mixed Reality
Through integration with digital twin solutions, mixed reality technology could allow users to interact with a virtual recreation of real-world objects. Mixed reality allows users to visualize how pieces of equipment may behave under different operating scenarios, or it can provide training to staff using digitally simulated equipment.
Internet of Things
A digital twin is heavily reliant on the data produced by the Internet of things (IoT) embedded in equipment and airport processes; however, the necessary IoT devices must be installed to provide that data. Extensive networks of IoT devices provide enhanced digital twin functionality and provide airport operators with a comprehensive view of the data generated across the airport.
Artificial Intelligence
Artificial intelligence (AI) supports many of the data analytics and simulation functionalities of a digital twin solution. As AI improves in performance, more sophisticated simulations can be achieved by the solution.
Technology Barriers
As with some other technologies noted in this Publication, there are market forces or development factors that present barriers to the deployment and widespread adoption of digital twin technology. Keeping abreast of these barriers can help airport operators know when to expect to see wider use of this technology in the public and when they should look to reassess it for their own use. This article outlines the current state of digital twin technology barriers.
Computing Power and Software Solution Development
Since substantial computing power is necessary to process, visualize, and forecast scenarios from incoming data sources, improvements to computing power and the development of effective software tools are needed to make the most of a digital twin in both aviation and non-aviation use cases.
Increase in Data Interfaces and Connected Device Networks
To develop a digital twin of an airport, extensive airport property mapping and inclusion of the necessary connected devices are required. Data must be effectively extracted from all necessary devices and processes to make the digital twin solution as comprehensive as possible.
Process Design to Incorporate Generated Insights
Through the use of data provided from digital twin solutions, airport operators can use the insights gained to improve the accuracy and efficiency of various processes across the airport. This means that rigidly designed processes must now include the flexibility to adapt process steps based on real-time data. Consequently, an organization’s culture must be comfortable with this flexibility and trust the insights provided from a digital twin solution.