Artificial Intelligence in Airport Cargo Transit. Airports 4.0 II

We are experiencing—and suffering—a global supply crisis driven by logistics issues, with the focus on both maritime and land transport. Goods are stuck in ports, either because they cannot be moved due to the mismatch between high product demand and the limited supply of cargo vessels, or due to a shortage of carriers for overland distribution.

These bottlenecks—each highly impactful on its own—together have caused a global supply shortage. It is common to hear in the media that cars are not being manufactured at the required pace due to the shortage of microchips, for example, or that when purchasing an appliance, delivery times are delayed by weeks and even months.

Air logistics: a solution to supply shortages?

Faced with this reality, companies are beginning to look for alternatives in air cargo traffic, which is seeing increased activity as an alternative to more traditional means—primarily ship and truck, but also rail. The airport sector is gaining increasing weight in the global logistics landscape; in fact, there are shipping companies buying aircraft for cargo distribution, and aircraft manufacturers are dedicating more and more units to freight transport.

In addition to the sector’s existing logistics challenges (a shortage of carriers, reduced maritime operations, and rising prices), the crisis caused by COVID-19 has further complicated the situation due to increased online consumption and the decline in passenger air traffic, which has hindered cargo transit on mixed flights.

In 2020, the drop in passenger air transport reached 60%—a downward trend in operations that, although to a lesser extent, also continued in 2021. Lockdown periods, mobility restrictions, the consolidation of online work, and countries’ recommendations not to travel to areas with high virus incidence have greatly reduced passenger flights, which are forecast to recover more slowly than flights for cargo transactions. Cargo flights are proving to be the lifeline for those goods that can absorb the cost of air transport.

What goods can be transported by plane?

And we say “absorb” because this is not a suitable means of transport for all types of products, since its high cost makes it unviable for low-priced items that cannot sustain the logistics investment. In air freight, two variables must be balanced: product cost and delivery urgency (products subject to expiry dates or requiring immediate stock replenishment). The combination of both must result in a profitable operation—and in many cases, it does not.

Faced with this reality, as we have already noted regarding land transport and logistics operations in general in other articles, efficiency in operations—in this case, aeronautical—undeniably depends on implementing data science and artificial intelligence systems. What do they bring to this field? Quite simply, the ability to optimize the entire air logistics process—from movements at airports to route design, including the administrative procedures required for transactions. Let us look at all the possibilities that Aeronautics 4.0 can offer.

Artificial intelligence, towards Aeronautics 4.0

If we follow the chronological order, we first encounter the need to establish efficient routes that make the most of each flight. Artificial intelligence and big data have enabled the development of route planners that allow us to optimize flights based on obvious variables such as fuel consumption, pilots’ flight time, and delivery deadlines, while also taking into account considerations such as refuelling costs or aircraft maintenance expenses in different countries.

Another type of planner, this time for cargo, helps make the most of every square centimetre of the holds, based on parameters such as volume, weight, fragility, recipient, etc. However, many procedures are required before the aircraft is loaded (quotes, permits, tariffs, and a long list of others). Those that are repetitive and mechanical can be digitized with Robotic Process Automation (Robotic Process Automation – RPA) systems, which autonomously handle large volumes of so-called desktop tasks.

Once the cargo has been received at the airport—both at origin and destination—it can be tracked and distributed thanks to digital location systems such as barcodes, RFID encoding, or the Internet of Thinks (IoT), which will also enable, through Business Intelligence developments, product traceability as it moves through the different stages of the logistics process.

To give a few more examples, predictive maintenance systems make it possible to monitor aircraft performance and service them precisely when they truly need it, avoiding scheduled downtime periods; with digital twins (digital twins), we can replicate real operations to work with them virtually, creating a test environment in which to trial new cargo flows within airport receiving, dispatch, and delivery areas; test the outcome of route changes; design human resources operations…; and another major tool developed with artificial intelligence, computer vision, is highly useful for carrying out inventories in fractions of a second through automated counting.

Digital transformation: greater efficiency and sustainability

As we can see, the leap towards digital transformation in the aeronautical and airport sectors simplifies decision-making processes because it provides information not only about the current reality of operations, but also about future ones; and it increases efficiency ratios and, consequently, profitability.

In addition, we must not forget that route optimization directly improves the sustainability levels of air logistics processes. Making use of available cargo space and being able to design efficient journeys reduces flight kilometres and their footprint in the atmosphere.