Boulders and cobbles embedded on the body of landslides are carried downstream under the action of gravity, and the study of their transport can give important insight on their dynamics and hence the related hazard. The study examines the reliability of smart sensors to track movements of a cobble and discern between intensity and mode of movement in laboratory experiments. A tag equipped with accelerometer, gyroscope, and magnetometer sensors was installed inside a 15 cobble. The experiments consisted of letting the cobble fall on an inclined plane. By tilting the inclined plane at different angles, different modes of movement such as rolling, bouncing, or sliding were generated. Sliding was generated by embedding the cobble within a thin layer of sand. The position of the cobble travelling down the slope was derived from camera videos. Raw sensor data allowed detection of movement and separation of two modes of movement, namely rolling, and sliding. Additionally, reliable values for the position, velocity, and acceleration were determined by feeding a Kalman 20 filter with smart sensor measurements and camera-based positions. Furthermore, by testing LoRaWAN wireless transmission through sand, the study showed that the signal strength tended to decrease for thicker sand layers. These findings confirm the potential to use these sensors to improve early warning systems and further studies are in progress to assess practicalities of their use in field settings.