Like many other industries, aviation has identified data science, AI, machine learning and predictive analytics as practices and technologies that can help it become more efficient and profitable. This is not news. Aviation industry experts have been saying it for years.
The main reason that the aviation industry yearns for innovation is its constant struggle to create wide revenue margins. Aircrafts are expensive to purchase and maintain, and oil prices are affecting jet fuel prices. Labor costs also play a major factor, and so are flight delays, which are very frequent and are incredibly costly to airlines. Until the COVID-19 pandemic, airlines and other aviation industry businesses managed to thrive due to great customer demand. But the pandemic changed everything.
No one really saw COVID-19 coming, and that includes the aviation industry, which, along with the tourism industry, took a huge hit in 2020 and 2021. According to an article by IATA’s Airlines Magazine, the aviation industry’s net losses for 2020 are estimated at 137.7 billion dollars. And while 2021 losses have been reduced to 51.8 billion dollars, the industry is still shaken up by these huge financial setbacks. In addition, more uncertainty follows in 2022, as Coronavirus variants continue to spread.
Airlines and airports are now facing an entirely new world. As they continue to adapt to new health, safety and operational regulations brought on by the pandemic – as well as dynamic consumer trends and governmental restrictions – they must introduce new technologies and practices that can help usher in a new era for aviation.
How can Data Science and Analytics Advance the Aviation Industry?
Leveraging real-time data from multiple sources can go a long way in creating an ecosystem that is better positioned to serve its customers, enhance employee efficiency and tackle major challenges. Yet despite the fact that airlines and airports have implemented data science practices and AI technologies to improve a variety of measures, there is still a long way to go. In fact, one can say that in 2022, two years after the initial outbreak of COVID-19, the advanced data era is still waiting for actual takeoff.
There are virtually hundreds of ways in which data analysis and prediction can propel the aviation industry to new heights. Here are several key parameters:
AI Prediction for Aviation: The IntellAct Case Study
At Cockpit Innovation, we are always looking to identify companies and technologies that can advance the aviation industry. Understanding the need for better AI and data science capabilities for aviation cost and operation-efficiency, we realized that some of these technologies are maturing in front of our very eyes, and can already be found in various stages of development and production.
We were introduced to IntellAct and its product at its earliest stages of development. IntellAct’s founders aimed to create an AI-based solution that could utilize data to make airport ground handling and turnaround services quicker, more efficient and more cost-effective.
After realizing IntellAct’s immense potential, we signed on as investors.
What IntellAct can do is truly groundbreaking, and we feel it has the potential to become an integral part of the future of aviation. By using CCTV and other existing infrastructures, IntellAct automatically detects a wide range of ground and turnaround services in real-time, in order to resolve service bottlenecks and minimize delays. By automatically subjecting vast amounts of video-based data to real-time machine learning, IntellAct optimizes gate services, ramp services and jet bridge services – and creates improved operational scenarios for airlines, airports, and all relevant personnel.
As investors, we provided IntellAct with guidance from the pre-seed stage, and gave the team access to the ELAL Airlines premises so that they could perform valuable system testing and evaluation. Today, the IntellAct system has already proving to be useful for clients, and is on its way to making waves in the industry.
The Bottom Line
Innovative and systemic solutions like IntellAct are just what the aviation industry needs. Solutions like IntellAct combine smart technology, out-of-the-box thinking, relatively simple implementation on existing platforms, and flexible volume usage-based pricing. But most importantly, IntellAct has a clear definition of the problem it aims to solve, and an acute understanding of what its success can mean for airlines and airports.
IntellAct is just one example. There are more AI-based solutions for aviation out there, and many of them are very promising. The sooner they are implemented in our industry, the easier it will be for everyone to take off to a better future.