Artificial Intelligence for Automation in Airports

Airport Runway Foreign Object Debris (FOD) Detection Systems


Automated FOD Detection

Any material that should not be found on an airport taxiway, ramp, runway or airfield is classified as Foreign Object Debris (FOD) and must be removed to increase safety of operation and prevent aircraft damage. 

Your passenger’s and flight’s safety is our main priority, that’s why we have produced A-FOD; A foreign object debris detection system that is used for tracking even the smallest objects in any weather condition in an airport. A-FOD provides comprehensive sets of surveillance and analysis tools in order to have a complete management of the runways.  



we are focused on developing technology for creating innovative solutions



we work towards enhancing the global economic and social evolution in human life


We are focused on developing technology for creating innovative solutions, and enhancing the global economic and social life. Our team of experienced and multi-discipline enthusiast have many international publications and 8 patents on "image processing and artificial intelligence


Our team consists of aircraft designers, software developers, solid mechanics specialist, simulation developers, image process and artificial intelligence developers, neural networks and deep learning developers.




Pattern recognition

  Pattern classification

Pattern recognition: We develop algorithms to find target objects in images. This could range from finding airport runways and planes in satellite images to  finding a 3cm bolt in that runway. 

Pattern classification: Our technology can monitor people and detect at which moment a person watching an advertisement gets bored or feels joy or whether a bolt on a runway threatens the safety of a flight ot not.

Image segmentation

Image segmentation: Our technology can differentiate between settlement, water and woods from satellite images or locate tumors in 3d tomograms or find cars from real time images to find their velocity.

Robot Vision

Robot Vision: We make robots that can understand what they see and make their own decision for the given task. we accomplish that by transforming computer vision knowledge to software products.

Deep learning

Deep learning: People can easily understand cats or dogs when they see it. Yet it is so hard to teach a computer that such a basic task. Thanks to the advances in deep learning, it has become easier to train a computer to recognize what it sees. Historically very challenging tasks can now be accomplished with ordinary computers or even mobile devices. We are now able to surpass the performance of conventional methods with less computational demand.



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