- I wanted to explore the possibilities of using drones in search and rescue as a complementary tool to helicopters, says the 39-year-old.

The idea has always been to save time for critically ill and/or injured individuals through the use of applied technology. Despite having good coverage of rescue helicopters in Norway, drones would be a valuable tool to gain time and initiate searches before other resources arrive at the scene, says Jørgen Skogmo (39).

He is studying applied machine learning at Noroff while working as a project manager in the Norwegian Air Ambulance's technology department.

I believe we have taken a quantum leap when it comes to the use of technology in search and rescue operations, Jørgen says.

Video sent from 5G-powered drones

The idea is that when a crisis occurs, a mobile 5G network on wheels is deployed near the rescue operation area. A drone is dispatched from the vehicle and transmits video back to the mobile control room.

Inside the NOW control room, the video is processed by an Intel-developed Machine Learning algorithm trained to recognize relevant elements, such as humans, dogs, and vehicles.

This is probably just the beginning of a rapidly evolving field, Jørgen says enthusiastically.

At a training camp for Norwegian SAR (Search and Rescue) operators in September, Telenor, along with Intel and the Norwegian Air Ambulance, demonstrated the use of a proof-of-concept mobile 5G network in a disaster scenario.

Watch the here:

We ran a classification algorithm on a real-time video stream from a drone via a mobile 5G network. This was to demonstrate that applied technology can enhance the capabilities of drone pilots and provide them with better decision support. Ultimately, this means a significant amount of time saved for the patient, Jørgen explains passionately.

Studying applied machine learning

I had some hypotheses and ideas about new methodologies for using machine learning in prehospital emergency medicine but lacked expertise and the theoretical foundation. To achieve what I wanted to do, I simply had to acquire the knowledge.

This led Jørgen to apply for the applied machine learning program at Noroff Online Studies.

Throughout the one-year program, you can learn how to teach systems to learn from data. The goal is to enable systems to identify patterns without further programming, making this approach highly valuable for companies.

Studying applied machine learning is incredibly interesting but also very demanding. When you reach the point where you can translate theory into practice, that's when you truly see the immense possibilities of machine learning.

Online studies have start dates four times a year. The next start date is already on January 10. See which studies are starting here

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