DoorINet: A Deep-Learning Inertial Framework for Door-Mounted IoT Applications

arXiv:2402.09427v1 Announce Type: cross
Abstract: Many Internet of Things applications utilize low-cost, micro, electro-mechanical inertial sensors. A common task is orientation estimation. To tackle such a task, attitude and heading reference system algorithms are applied. Relying on the gyroscope readings, the accelerometer readings are used to update the attitude angles, and magnetometer measurements are utilized to update the heading angle. In indoor environments, magnetometers suffer from interference that degrades their performance. This mainly influences applications focused on estimating the heading …

abstract algorithms applications arxiv attitude cost cs.ai cs.lg eess.sp framework internet internet of things iot low micro reference sensors type update