Early-stage landslides and rockfalls are often characterized by very small internal accelerations associated with creep and progressive deformation, which are difficult to capture using conventional surface-based displacement monitoring techniques. To address this, the study presents the design and laboratory validation of a prototype in-mass inertial monitoring device, referred to as a Smart Rock, intended for embedded monitoring of rock mass motion. The developed device integrates low-noise inertial measurements with on-board processing to enable real-time characterization of motion signatures within a moving mass. Two sensing configurations, including a low-noise accelerometer-only configuration and a full inertial measurement unit (IMU) configuration, were implemented to evaluate their relative performance for in-mass motion monitoring. Embedded signal processing approaches suitable for landslide motions were developed to identify quasi-static, step-change, and impact-related motion regimes. Laboratory experiments using a controlled robotic testbed generated repeatable motion scenarios representative of creep-like movement, abrupt displacement changes, and impact events. Results showed that Smart Rock resolved very low-magnitude acceleration signatures on the order of 10−5 g and distinguished these from higher-energy motion and impact events, with improved signal stability observed for IMU-based configurations. These findings demonstrated the feasibility of in-mass inertial devices for characterizing landslide and rockfall motion in geotechnical applications. These results should be interpreted as proof-of-concept laboratory validation under controlled conditions.
Shahsavar et al. (Mon,) studied this question.