szenzorfúzióból

Szenzorfúzióból is a Hungarian term that translates to "sensor fusion" in English. It refers to the process of combining data from multiple sensors to obtain more accurate, complete, or reliable information than would be possible from a single sensor. This integration of data can overcome the limitations of individual sensors, such as their narrow field of view, susceptibility to noise, or specific measurement constraints.

The core idea behind sensor fusion is that different sensors often provide complementary information. For example, a camera might detect objects visually, while a lidar sensor can provide precise depth information. By fusing the data from both, a system can achieve a more robust understanding of its environment. This can involve various techniques, including statistical methods, Kalman filters, and artificial intelligence algorithms, to weigh and integrate the incoming data streams.

Sensor fusion finds applications in a wide range of fields. In robotics and autonomous vehicles, it is crucial for perception, enabling vehicles to navigate safely by understanding their surroundings. In medical imaging, fusing data from different modalities like MRI and CT scans can lead to more comprehensive diagnoses. It is also used in weather forecasting, industrial automation, and even in consumer electronics like smartphones for enhanced user experience. The ultimate goal is to produce a unified, more informative representation of reality.