The next generation of Smart & Sustainable Aviation: Digital innovation powered by neuro-network and cybernetic computing

Suhail Kamil Kadri, Senior Vice President of Technology and Innovation, Hamad International Airport

What if airlines, airports command centres and air-traffic control authorities can optimise the ‘sequence’ of landing and take-off to save fuel and reduce carbon emission based on current ground coordination conditions? Taking into consideration weather and airport ground conditions and airline connectivity, this method of airport operations spread across the aviation sector globally can allow for coordinating in real-time, updating flight plans in unison.

In the face of climate change and increasing environmental concerns, the aviation industry is constantly searching for impactful solutions to reduce its carbon footprint. Adopting new technology and innovative solutions can assist these goals, such as, harnessing the power of neural-network, cybernetics computing built over and above Airport Collaborative Decision Making (ACDM) as a foundation, can truly transform aviation sustainability, by saving fuel and reducing carbon emission, on a global scale.

In 2022, Hamad International Airport (DOH) adopted Airport Collaborative Decision Making (ACDM) by working closely with its airline partners and stakeholders in order to optimize airport operations with a focus on aircraft turn-around management. Implementing ACDM is the first step towards a goal of building and connecting a global network of air spaces, allowing airlines and airports to coordinate in real-time whilst updating flight plans in order to conserve fuel and reduce carbon emissions. 

Environmental impact of adopting Airport Collaborative Decision Making in the industry

Enabling ACDM has multiple positive functions such as, improving air traffic management and allowing for smooth flight departure and arrival; sharing real-time data within the airport network including airlines, air traffic control, ground-handlers and airport authorities; minimises delays and congestion and supports efficiency in aircraft operations. In terms of ground operations, it enables the airport and ground handlers to efficiently assign gates based on aircraft type and passenger connections, plan baggage handling, refuelling and catering effectively. 

By synchronizing these activities where aircraft schedules and turnaround management is enhanced, will result in minimal engine idle time, reduce taxiing times, improve sequencing of aircraft movements, allocate resources accordingly, reduce fuel consumption during ground movements, resulting in a reduction of fuel burn and associated carbon emissions. 

With ACDM, airports can identify opportunities to implement eco-friendly technologies and process as it encourages the adoption of sustainable infrastructure and operational practices through data sharing and collaboration with stakeholders. One such feature is the implementation of autonomous, electric or hybrid ground support equipment, which reduces the use of conventional fossil fuel-powered vehicles on the airfield. 

Embracing ACDM can help the industry achieve its carbon reduction targets and with sustainable practices significantly contribute to carbon emission reduction and align with global sustainability goals.

How neural-network and cybernetics computing can be leveraged to power the ‘last mile’ of this innovation

Weather conditions along the flight paths directly influences the decisions pilots make to reach their final destinations, and ground conditions of final approach impacts the air-traffic control authorities’ instructions to pilots on their take off time slot or final approach for landing at the airport.

Historically, commercial aircraft would have flown on average about 8 percent faster than their optimal cruising speed leading to an earlier than planned arrival to a landing airspace, to which ground conditions at the airport may not be able to comply with due to multiple factors. Therefore, the air-traffic controllers instruct the pilots to circulate the airspace around the airport until a landing slot is allocated, resulting in counter-productive fuel consumption and adds to carbon emission.

Once the foundations of ACDM are in place, it is conceivable that by dynamically allocating optimal sequences of aircrafts landing and take-off, a new digital innovation can be realised for airlines, airports and air-traffic controllers to reduce fuel burn and carbon emission at the last mile of each aircraft’s journey.

All this can be made possible by adopting neural-networks to compute the optimal sequences with the input parameters associated with aircrafts’ travel speeds, weather conditions, estimated arrival times, currently forecasted available landing slots timings based on airport ground conditions.

Coupling this innovation with cybernetics on-board the aircrafts which can recommend to the pilot continual amendments to the flight plan based on the end-to-end situation can potentially increase fuel efficiency even further.

With this, it potentially makes the open dialogue between air-traffic controller and pilot minimal; as by the time the aircraft nears the airport’s airspace, the allocated landing slot will almost certainly be the most optimal to be utilised taking into accounts of the total aircraft journey from origin to destination, and all this while saving fuel and reduce carbon emission.

When such futurist capability is adopted throughout the global network of airlines, airports and air-traffic controllers in a network centric operation manner, the magnitude of fuel saving and carbon emission reduction this breakthrough innovation can bring about on a global scale will be phenomenal.