This article first appeared in the Future Transport-News magazine, Issue 1 2023.
The future of air transport is almost here. Situational Intelligence™ will soon herald its arrival.
Beyond just situational awareness, Situational Intelligence is the ability of a machine to understand and make sense of the current flight environment and then to anticipate and react to threats to flight safety. Put another way, it’s a computer able to sense, analyse and respond to environmental situations – just like a human pilot does. But better.
In the near term, Situational Intelligence will provide indispensable pilot assistance in the fundamentals of flying, conveying to the pilot answers to three essential questions:
Where am I?
Where can I fly?
Where can I land?
One day soon, Situational Intelligence will act upon the answers to these questions enabling aircraft to fly autonomously, always with a human in control, but, quite possibly, without the need for human intervention.
Situational Intelligence will usher in a new era enabling all air transport to reach safety levels now possible only for the heavy infrastructure-burdened airlines and airports. The dream of air taxis and flying cars is now emerging from imagination as the new reality where distance and division are easily overcome. At scale, movement about the planet will be more accessible, providing more opportunity and equity to all.
Coined by Daedalean, the leading software and hardware developer of pilotless flight, the term Situational Intelligence is made possible by a new level of flight control algorithms resulting from recent developments in artificial intelligence, or, more accurately, machine learning.
“Machine learning is central to our work in providing intelligent cockpit systems,” says Luuk van Dijk, who founded Daedalean in 2016 along with Anna Chernova. “It’s a more specific term than the much bandied about ‘AI’. Machine learning is, basically, training systems to learn to do a task without being explicitly programmed to do that task. We train a machine in the lab, for example, to recognise a runway so that it can recognise runways out in the world in real life.”
Out in the world, a live stream of video footage from cameras mounted on the exterior of an aircraft is fed to an onboard computer, which interprets and categorises in real time the various objects it detects: mountains, clouds, lakes, rivers, aircraft (and even specific aircraft types), masts, cranes, wires hanging between utility poles and, of course, runways, and for a rotorcraft – flat, clear areas that could serve as emergency landing options.
Xwing and Daedalean AG have announced a formal collaboration to share data, knowledge, and processes in the field of machine learning and AI.
Daedalean engineer, Giovanni Balduzzi, recently earned his pilots license and chronicled his findings along the way.
Daedalean has been awarded a grant by Innosuisse to develop its BRAVEN (Bimodal Radar for Aviation Environments) Solution.
Daedalean believes one of the three key skills of a human pilot is to fly according to visual flight rules (VFR) and in visual conditions.
At Daedalean, the team has always focused on developing products for aviation with an eye toward future certification.
Daedalean recently looked into accidents related to navigation, flight planning, geographic disorientation & navigation error.
Daedalean’s Visual Awareness System (VXS) relies on the input from several (one to four) cameras installed on an aircraft.
Daedalean leverages the power of artificial intelligence to provide superhuman situational awareness systems to aerospace.
Daedalean’s data-collection aircraft photoshoot in the Swiss Alps illustrates the beauty of nature and technology.
Daedalean hires Dr. Yemaya Bordain to lead its new office in Phoenix, AZ, as the company officially opens for business in the United States.
Daedalean has concluded a joint research project with the FAA on Neural Network-Based Runway Landing Guidance for General Aviation.
Use the form opposite to get in touch with Daedalean directly to discuss any requirements you might have.