Flight Sensor

Flight sensor research focuses on developing robust and efficient systems for various aviation applications, primarily aiming to enhance safety and automation. Current efforts concentrate on utilizing diverse sensor modalities (infrared, vision, and multi-sensor fusion) and advanced algorithms, including deep learning architectures like convolutional neural networks (CNNs) such as YOLO and VGG16, to process data for tasks such as object detection, attitude prediction, and fault diagnosis. These advancements have significant implications for improving aircraft safety, enabling autonomous flight capabilities, and optimizing maintenance procedures, ultimately contributing to more efficient and reliable aviation systems.