“AI is going to be everywhere.” This is what Tassio Carvalho, a senior manager at American Airlines, declared recently at the Connected Aviation Intelligence Summit. According to his vision, aviation companies will employ AI to help humans in different domains, from customer support to aircraft maintenance. ‘
In this article, we shall discuss future trends in aviation logistics and how AI and automation will reshape the industry’s operations.
Let’s get started!
Streamlining paperwork and data discovery
Even now, paperwork takes 75% of an average pilot’s duties. Despite numerous efforts with digitalization, a lot of reporting is done on paper, often left undigitized, leaving tons of valuable data to be obscure. Using AI to digitize and systematize flight records is an emerging trend. AI-powered OCR solutions help to convert handwritten, printed, and typed text into data to be used by AI engines to study the aviation industry from the inside.
The rise of unmanned delivery vehicles
According to Boeing’s industry report, the global air cargo market will double in the next two decades, featuring a 4.1% growth yearly starting from 2021. This means the industry will invest heavily in innovation, and unmanned air cargo vehicles will be a point of primary attention.
Although this technology is in the prototyping stage, advances in AI may fuel the development of autonomous aircraft anywhere soon. We already have a couple of initiatives with bright ideas and bright names that promise to populate our skies with autonomous air vehicles in the coming several years. Here are some of them:
- The UK government’s initiative is HEART – Hydrogen Electric and Automated Regional Transportation. HEART must create a pilotless hydrogen-powered aircraft fleet for short flights by 2030. The automated jets will be able to transport from 9 to 19 passengers and cargo.
- ATTOL – Autonomous Taxi, Take-Off, and Landing – is a project from Airbus. Their unmanned plane, equipped with AI-based image recognition technology, took a successful take-off and landed in 2020.
- Chaparral C1 is a cargo drone created for FedEx. FedEx commissioned the drone to the technology development company Elroy Air, and in November 2023, the first delivery UAV was tested successfully. The drone can lift 226 kg and carry a load for 250 nautical miles. Therefore, Chapparal is aimed for middle-mile delivery, and since it is capable of vertical take-off and landing, it can land outside airports, in places like warehouses, etc.
- Rhaegal RG-1 is a development from Sabrewing. The drone can carry a payload of up to 2,455 kg over a distance of 1850 km. It is the highest load capability in the industry so far.
- PrismSky is a delivery drone engineered by Watts Innovation in partnership with Auterion. Walmart used the vehicle for short-haul grocery deliveries. The drone offers real-time flight log uploading, viewing, and multiple flight management possibilities.
- Wing is a solution created by the eponymous on-demand drone delivery provider. Wing has partnered with Walmart for grocery deliveries in Dallas.
- Boeing’s unmanned air cargo vehicle can transport up to 227 kg. The prototype tests started back in 2018.
All unmanned aerial vehicles are capable of vertical take-off and landing. These quadro- or multi-copters come in different sizes and load capacities and are used for short-haul and middle-mile deliveries. Some are capable of long-haul deliveries, too. Anyways, as the experiments prove successful, UAVs are predicted to make up to 80% of deliveries in the future.
AI-planned flight routes
Even now, aviation companies employ artificial intelligence to calculate the best effective routes for passenger and commercial flights. For example, Alaska Airlines uses an AI engine that helps build routes according to favorable winds. If a flight starts with a favorable wind, the flight duration can be cut to seven minutes, leading to fuel and carbon dioxide pollution savings.
The rise of robotics
Aviation companies use falcon-shaped robots to drive bird flocks from plane routes and avoid bird strikes. Robotic dogs are used to prevent wildlife from entering airports; robotic drones are used to check aircraft for signs of structural fatigue visually. Robots also clean aircraft, paint them, or lift heavy luggage.
The future hints there will be more robots in aviation. The spheres of their application will be more comprehensive, too. Several companies are developing robotic pilots. The American state agency DARPA is one of them. They have developed a robotic arm to land a Boeing without human oversight. Their solution is called the Aircrew Labor In-Cockpit Automation System (ALIAS). Although it is in the testing stage now, the solution has a lot of interest on behalf of the government and corporations.
Human resources management
Assigning crews to flights is a burdensome process. Moreover, since specific crews are accustomed to their planes, sometimes switching places requires visibility of the crew’s availability. Lufthansa partners with Google Cloud to create a set of tools collectively called the Operations Decision Support Suite (OPSD). The applications give a lot of possibilities. A visibility into the pilot’s availability is one of them.
With the precision and effectiveness this tool gives, it can be more widely used in the near future.
Digital twins
Aircraft engineers use sophisticated virtual models of aircraft, known as virtual twins, to build and test prototypes, experiment with ideas, or look for new solutions. Yet, today, building a digital twin is a time and labor-consuming process requiring a lot of manual effort.
The further development of generative AI will make digital twins simpler to build. Once applied in aviation, this technology will revolutionize how digital modeling is seen now. It is predicted that, in the future, digital twins will be accessible to broader engineering audiences.
According to Rishi Ranjan, founder and CEO of GridRaster, the generative AI is expected to cut every dollar spent on creating AI models into 10 cents. Also, GenAI is expected to speed up the development of digital twins, meaning that aircraft engineering will speed up, promising more innovation.
Use of AI for predictive maintenance of aircraft
The use of AI for predictive aircraft maintenance is a trend that has been around for a while. Yet, it will be a rising one shortly. This technology promises success. For example, the aircraft maintenance, repair, and overhaul market will slow down the pace of development from 2.8% in 2024 to 0,7% a year after 2028.
So, how will it work?
AI unlocks access to smart robotic cameras, intelligent sensors, predictive analysis, and more. In total, the new approaches reduce the number of failure incidents and enhance the effectiveness of predictive maintenance.
New jobs
According to MIT’s Sloan Review, the growth of AI will lead to the development of new jobs to handle it. In a joint article by Accenture’s upper-level managers Wilson, Daugherty, and Morini-Bianzino, the new roles are introduced, labeled as trainers, explainers, and sustainers. These new jobs will be novel and demanding skills and training that have no precedents. These people will train, deploy, oversee, and test new AI models, ensuring their productivity.
In the future of air cargo, there will be more AI, so there will be more AI-induced jobs. For example, companies will need people to train custom AI solutions on their data.
Robotics is another source of new jobs. According to Jo Alex Tanem, CEO of Nordic Dino Robotics AB, the future of aviation will need people who oversee robots “to ensure the accuracy and safety of these automated processes.”
Pilot health monitoring
U.K.-based software company Blueskeye AI, specializing in facial analysis using artificial intelligence, has recently developed a tool that can read fatigue in pilots’ faces and give alerts on the mental state of pilots and their health.
Although this technology raises some critical privacy concerns, it may prove efficient. Blueskeye hopes their solution will help identify pilots who are unfit to fly due to declining health conditions and enhance flight safety.
AI-designed planes
AI uncovers previously unseen engineering possibilities. Like in any industry, AI streamlines data collection and processing.
So, how do aviation experts see the development of aircraft engineering in the next few decades?
According to Todd Citron, Boeing’s chief technology officer, in 2040, there will likely be some changes to the shape of the airframes and the engines.
Other experts support his statement. Kirsten Rose, executive director of future industries at CSIRO, thinks AI will significantly change the design parameters. The most interesting thing about all of this is that we cannot predict those changes now. According to Rose, “only now understanding the capability for optimization, which will drive efficiency, for design parameters and things like that.”
We can be sure that AI will help generate innovative and more efficient aircraft concepts that will be more cost-effective and fuel-efficient.
AI-powered additive manufacturing
The merge of AI and 3D printing technology opens opportunities to create engineering details that are technically difficult to produce.
3D printing reduces the cost and weight of aircraft details, giving companies that use this technology a competitive edge.
For example, Boeing has just opened a new additive manufacturing factory in Auburn, Washington. This facility will create parts for parts commercial airplanes, satellites, helicopters, and spacecraft.
AI-based virtual modeling and rapid 3D prototyping considerably cut the way from idea to industry tests.
Vertical take-off and landing for small urban aircraft
The possibility of small vertical aircraft for urban use has been studied long ago. Yet, until now, engineering efforts haven’t been successful. As AI powers research and modeling, new technical solutions are coming. Peng Wei, a professor of the Department of Mechanical and Aerospace Engineering, whose specialty is control, optimization, machine learning, and artificial intelligence (AI) in air transportation and aviation, has started an interdisciplinary project with NASA, the University of Texas, and MIT to explore new engineering possibilities for the electric aircraft of vertical take-off and landing.
Conclusion
Have a question?
Speak to Data Scientist
Jagdeep ChawlaMS in Data Science
NorthWestern Univeristy, Illinois
MS in Data Science
NorthWestern Univeristy, Illinois
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