Walking-induced loads on office floors can generate unwanted vibrations. The current multi-person loading models are limited since they do not take into account nondeterministic factors such as pacing rates, walking paths, obstacles in walking paths, busyness of floors, stride lengths, and interactions among the occupants. This study proposes a novel video-vibration monitoring system to investigate the complex human walking patterns on floors. The system is capable of capturing occupant movements on the floor with cameras, and extracting walking trajectories using image processing techniques. To demonstrate its capabilities, the system was installed on a real office floor and resulting trajectories were statistically analyzed to identify the actual walking patterns, paths, pacing rates, and busyness of the floor with respect to time. The correlation between the vibration levels measured by the wireless sensors and the trajectories extracted from the video recordings were also investigated. The results showed that the proposed video-vibration monitoring system has strong potential to be used in training data-driven crowd models, which can be used in future studies to generate realistic multi-person loading scenarios.
|Journal||Advances in Engineering Software|
|State||Published - Jan 2020|
Bibliographical noteFunding Information:
The authors would like to thank Qatar Rail Company for providing an access to the office floor monitored in this work. The financial support for this research was provided by Qatar National Research Fund , QNRF (a member of Qatar Foundation) via the National Priorities Research Program (NPRP), Project Number: NPRP 8-836-2-353 . The statements made herein are solely the responsibility of the authors.
- Homography computations
- Human walking patterns
- Occupant induced floor vibrations
- Probabilistic occupancy map algorithm
- Vibration monitoring
- Vibration serviceability
- Video monitoring
- Video-vibration monitoring
- Walking trajectory extraction
ASJC Scopus subject areas
- Engineering (all)