AI and Machine Learning for Post Covid World Airports
When you think about the most crowded institutional places, airports will quickly come to your mind. Approximately 50 thousand people in domestic flights and 152 thousand people in international flights are being served in İstanbul Airport daily. This results in an inevitable need for high and complex security measures. It is not only difficult and important to provide a safe environment in such huge places but also, ensure the safety of so many people.
Due to the COVID-19 pandemic the number of people visiting airports decreased significantly. However, this hasn’t affected the need for high security measures. In fact, safety and security has become way more important with the regulations and health precautions. Moreover, they are the reason why people are hesitating to use airports. So, it is the solution of increasing the number of people.
The tendency to increase the security measures paves the way for AI (artificial intelligence) and ML (machine learning) technologies to rise. These technologies have begun to be implemented in airport security systems because of their various benefits. AI makes a lot of things possible. AI systems improve as more and more information is fed into them. In the case of airport security, machine learning can be used to analyze data and identify threats faster than a human could. Although it can be used in numerous aspects we will be considering the four features of airport security’s which are powered by AI and extremely important in a post covid world.
Facial recognition
A facial recognition system is a technology capable of matching a human face from a digital image or a video frame against a database of faces. This is done by AI. This technology can be implemented to the post covid world as mask detection. Using this basis the mask-wearers and non-mask-wearers within an airport can be detected easily. With this system, if a traveler is found to be without a face mask, their picture is sent to the airport authorities so that they could take quick action. In this way mask safety is ensured.
Social distancing
Although airports tend to be crowded with people, separating passengers safely and maintaining social distancing is an essential of the post covid world. To help authorities maintain and check the distance the usage of cameras and activity recognition is necessary. This can be done using 3D cameras, sensors, ML software and analytics. By capturing the distance between people, the social distancing risk is reduced.
Smaller queues
Having smaller queues means less human interaction, faster circulation and most importantly lower risk of COVID-19 contagion. Therefore, we should be asking ourselves how airports will enforce social distancing, without creating endless, snaking lines. This can be achieved by linking occupancy measures with airport screens, to advise passengers when lines are of a safe size to enter the area, and which queue they should join. Once in the queue, camera sensors can measure the average distance between passengers. Then, the passengers can be redirected and redistributed to different lines.
Thermal cameras
Temperature testing is one of the primary precautions taken and it is believed to stick around for a little while as well. To fasten and make this process more efficient, one way is to use thermal cameras. These cameras can tell the body temperature of each passenger without making them get in a line and spend unnecessary time with this process.
These features are possible with the combined usage of high-skilled cameras and computer vision. The technology provided by AI is inevitable for implementation as it strengthens airport security significantly. Since these covid measures are nowhere close to being gone, it is vital for institutions to find ways to make their airports safer.
