Ultra-Low Power Architecture for Offline and Online Inertial Measurements

Inertial Measurement Units (IMUs) have become important components in various IoT (Internet of Things) and wearable applications, providing continuous monitoring of motion and orientation. However, one of the most significant challenges in using IMUs in long-term deployments is the optimization of their power consumption. This paper presents an ultra-low-power architecture designed to optimize IMU power consumption for both offline and online inertial measurements. The proposed architecture combines techniques such as duty cycling and adaptive sensing with careful selection and integration of components, enabling continuous and punctual motion tracking. The focus is on developing a method for measuring the inertial dynamics in critical contexts over extended periods, while also facilitating position tracking and online data transmission when possible. Although tested in a laboratory environment, this set-up provides promising results for application fields requiring sustained observation despite intermittent movements.