With a self-learning drone, we mean that the drone itself will recognize objects such as damage, leaks and dirt. The drone can learn how damage looks and recognize it. The drone will also learn which areas may be sensitive to damage and can thus predict damage.
The drone takes photos of the object and constantly compares them with pictures of the object in its ideal state to see if there are any differences. If there are differences between the photos, the drone will indicate this. The drone will have to begin the process with photos of the ideal state, so it cannot immediately recognize damage. The drone won’t know what an ideal state is if it has never seen it.
The drone can recognize damage and differences. So, if you have an object and that same object with damage or as a different color, the drone will indicate that the object is different than the original.
This system can be used with all kinds of cameras.
For example, it can be used for solar panel inspections using an infrared camera. The first time the drone will have to see the solar panels to recognize what is a functional or dysfunctional state. With an infrared camera you can see the difference between broken and working solar cells due to the differences in temperature – broken solar cells become warmer than working ones.
The drone would be able to recognize this independently with the smart drone.
The drone could be considered as a new employee, but cheaper.
In the same way a new employee also needs to learn, the drone needs to recognize what is good and bad. If the drone is unsure, it will ask your colleague what the answer is. The big difference is that the drone stores it forever, you only need to teach it once.
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