It is a global task to protect the climate and prevent temperatures from further rising. Not only do effective concepts exist, but many countries, industries and companies are already working hard to implement them.
The United States is one of the first countries to have developed its "U.S. Aviation Climate Action Plan." The plan outlines strategies for achieving net-zero emissions by 2050 within the U.S. Federal Aviation sector.
Artificial Intelligence (AI) is quickly being sought out as a significant tool to help the aviation industry get to net-zero emissions. With the evolution of AI from research to a viable tool came the need for developing standards and creating Responsible AI guidelines. Smart algorithms have been showing aviation management that properly deploying software powered by AI can achieve substantial cost reductions, improved productivity and better performance. As it continues to advance, there will be faster adoption rates, more innovation in its application and a greater focus on improving efficiency and sustainability in airport operations.
Achieving net-zero emissions in aviation will require a multi-pronged approach that will need international cooperation, technological advancements and potentially stricter regulations. Sustainable aviation targets encompass a range of goals aimed at reducing the environmental impact of air travel.
These targets typically focus on three main areas:
- Reducing greenhouse gas emissions: A primary objective with the ultimate goal of achieving net-zero CO2 emissions by 2050.
- Minimizing air and noise pollution: Regulations to limit emissions like nitrogen oxides and control noise pollution around airports.
- Improving fuel efficiency: Targets aim to encourage the development and use of cleaner-burning fuels like Sustainable Aviation Fuel (SAF) and more efficient aircraft technologies. The value of the global SAF market was estimated at U.S. $1.1 billion in 2023 with a projection to reach U.S. $16.8 billion by 2030, an impressive CAGR of 47.7%.
Airports, no matter the size, are buzzing with activity, particularly with ground operation management teams in charge of airfield maintenance/operations and handling in and outbound airline traffic. To be effective, these activities must be connected, collaborative and operate with the highest levels of efficiency. The advent of advanced technologies, particularly AI embedded in aviation management software, has significantly improved the daily work of these teams and has also made a significant contribution to a reduced environmental footprint.
A key area of focus involves airports, airlines and ground handlers who optimize scheduling and resource management using AI-based software support systems. Such intelligent software platforms, which can analyze historical data on turnaround times, flight schedules and ground crew availability, can help to create dynamic schedules to support on-time departures with no or minimal delays. Less idling aircraft and more efficient resource allocation leads to lower fuel consumption and emissions, a key goal in aviation sustainability initatives.
Airport regulations around sustainability typically first address energy consumption because airports are large consumers of energy, and many are already in the process of transitioning to renewable sources and energy-efficient practices. The goal is to achieve substantial reductions in greenhouse gas emissions.
Advanced software systems that have been architected to use AI at their core, have algorithms that can analyze, for example, data from various sensors on ground service equipment (GSE) to predict potential maintenance issues. The ability to predict and then take proactive measures reduces on-the-fly repairs that often result in flight delays and thus, idling aircraft.
Paving the Way for a Greener Aviation Industry
Analytics is a tool, that, combined with AI, can greatly help analyze the huge amounts of real-time data that is collected on airport management operations. For instance, it can assist with making flight delay predictions, to ensure an efficient on-time operation of ground handlers. Other prediction areas include a precise ETD and ETA, the seat load factor and the baggage volume of specific flights. This helps calculate workforce, GSE and other resource demands, which clearly benefits the optimal usage of existing resources. That, in turn, reduces emissions and improves ecological footprint. Airport aprons have to accommodate all arriving and departing aircraft without delay, which helps not only to increase customer satisfaction but also saves on fuel costs and reduces CO2 emissions. When an aircraft arrives at an airport, it must be able to park at an available gate or stand swiftly. Once parked, all baggage must be, with passengers de-boarding as quickly as possible without delaying other arriving or departing aircraft.
When you add in sustainability initiatives, that’s when AI can assist in predictions, streamlining and optimizing in several key ways:
- Optimizing turnaround processes — aircraft turnaround times and taxiway usage reduce fuel consumption on the apron. This can be achieved through better scheduling, communication, and digitalization of ground-handling processes.
- Lower maintenance costs, irregularities and delays — Predictive maintenance can identify potential spare part failures on the aircraft before they happen.
- Greater efficiency — AI can expedite check-ins, immigration processes and baggage handling operations such as by automating document checks by verifying passports and visas electronically as well as optimizing baggage sorting and routing.
- Enhanced cargo/baggage loading — By optimizing loading plans involving baggage or cargo and potentially reducing the number of GSE needed, AI can contribute to a more efficient and streamlined operation. This can have a positive impact on overall sustainability by reducing transportation-related emissions.
- Implementing more sustainable business practices — This is accomplished through better prediction capabilities regarding resource utilization and process optimization.
- Eco-friendly Ground handling — AI makes it easier for ground handling teams to implement eco-friendly practices like waste reduction, water conservation and using biodegradable materials for operations.
Automation Drives Enhanced Efficiency
Advanced systems, powered by AI, will optimize resource allocation, predict maintenance needs for GSE, and streamline turnaround times for aircraft, resulting in reduced fuel consumption and emissions. Additionally, a lot more autonomous ground vehicles (AGVs) in the form of driverless electric tugs and baggage tractors could become commonplace, further improving efficiency and safety on the apron.
Already we are seeing digital, paperless workflows and real-time data sharing between airlines, ground handlers, and air traffic control but in the future, this will occur a lot more seamlessly, facilitating smoother operations and quicker decision-making.
Modernizing the Flying Experience
Facial recognition and other biometric technologies for international travel are already occurring for safety as well as to streamline passenger check-in, security screening, and boarding processes. Such technologies will be delivering a better passenger experience with reduced wait times and less stress.
AI technologies will not only impact the airside, but also the passenger journey can benefit from these developments. For instance, AI-powered recommendations and services will soon be tailoring the travel experience to individual preferences, from pre-ordering meals to suggesting in-flight entertainment options. Ubiquitous Wi-Fi with faster speeds will soon be available throughout the travel journey, from check-in to in-flight access, allowing passengers to stay connected and productive.
With increased reliance on digital systems comes the need for robust cybersecurity measures to protect sensitive data and prevent operational disruptions, as an AI-centric company, it is an area to follow closely because fast-evolving technologies will require adaptable regulations and airport infrastructure upgrades to accommodate modernizations to airports as well as how airlines service customers.
From the utilization of electric and autonomous GSE to providing upskilling and retraining programs for impacted workers, there are a lot of considerations that come with the adoption of AI as part of an airport’s digital transformation. Overall, the future of aviation in 10 years looks promising as the industry looks to create a more efficient, sustainable and passenger-centric industry.
AI for airport operations is fast evolving. Many software companies are developing solutions and looking to AI as add-on capabilities, but very few are architecting their software from the ground up on AI as its base. This means that many will offer AI functionalities but only to a very limited extent. There will be a struggle to address all that AI can offer on many levels, such as how trustworthy it is in terms of reliability and safety in addition to its impact on society, businesses, and work life. INFORM, as an AI provider, no longer treats algorithms as a purely technical matter but instead take a broader view in more succinctly framing the deployment of AI coupled with questions on its impact, ethics and responsibility.
