Biomechanically influenced mobile and participatory pedestrian data for bridge monitoring
Future structural health monitoring systems are evolving toward crowdsourced, autonomous, sustainable forms based on which damage-indicative structural features can be identified. Unlike conventional sensor systems, they serve as non-stationary, mobile, and distributed sensor network components. For...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi - SAGE Publishing
2017-04-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147717705240 |
| _version_ | 1797766693180669952 |
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| author | Ekin Ozer Maria Q Feng |
| author_facet | Ekin Ozer Maria Q Feng |
| author_sort | Ekin Ozer |
| collection | DOAJ |
| description | Future structural health monitoring systems are evolving toward crowdsourced, autonomous, sustainable forms based on which damage-indicative structural features can be identified. Unlike conventional sensor systems, they serve as non-stationary, mobile, and distributed sensor network components. For example, smartphone sensors carried by pedestrians decouple from the structure of interest, making it difficult to measure structural vibration. Taking bridges as instances, smartphone sensor data contain not only the bridge vibration but also the pedestrians’ biomechanical features. In this article, pedestrians’ smartphone data are used to conduct force estimation and modal identification for structural health monitoring purposes. Two major pedestrian activities, walking and standing, are adopted to estimate walk-induced forces on structures and identify modal parameters, respectively. First, vibration time history of a walking pedestrian combined with pedestrian weight is a measure of dynamic forces imposed on the structure. Second, standing pedestrian’s smartphone sensors provide spectral peaks which are mixtures of structural and biomechanical vibrations. Eliminating biomechanical content reveals structural modal properties which are sensitive to structural integrity. This study presents the first structural health monitoring application recruiting pedestrians in a testbed bridge monitoring example. Orchestrating pervasive and participatory pedestrian data might bring new frontiers to structural health monitoring through a smart, mobile, and urban sensing framework. |
| first_indexed | 2024-03-12T20:28:51Z |
| format | Article |
| id | doaj.art-f5e7ab7e5c584d8ab8c53a70e31a996a |
| institution | Directory Open Access Journal |
| issn | 1550-1477 |
| language | English |
| last_indexed | 2024-03-12T20:28:51Z |
| publishDate | 2017-04-01 |
| publisher | Hindawi - SAGE Publishing |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj.art-f5e7ab7e5c584d8ab8c53a70e31a996a2023-08-02T00:19:49ZengHindawi - SAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772017-04-011310.1177/1550147717705240Biomechanically influenced mobile and participatory pedestrian data for bridge monitoringEkin OzerMaria Q FengFuture structural health monitoring systems are evolving toward crowdsourced, autonomous, sustainable forms based on which damage-indicative structural features can be identified. Unlike conventional sensor systems, they serve as non-stationary, mobile, and distributed sensor network components. For example, smartphone sensors carried by pedestrians decouple from the structure of interest, making it difficult to measure structural vibration. Taking bridges as instances, smartphone sensor data contain not only the bridge vibration but also the pedestrians’ biomechanical features. In this article, pedestrians’ smartphone data are used to conduct force estimation and modal identification for structural health monitoring purposes. Two major pedestrian activities, walking and standing, are adopted to estimate walk-induced forces on structures and identify modal parameters, respectively. First, vibration time history of a walking pedestrian combined with pedestrian weight is a measure of dynamic forces imposed on the structure. Second, standing pedestrian’s smartphone sensors provide spectral peaks which are mixtures of structural and biomechanical vibrations. Eliminating biomechanical content reveals structural modal properties which are sensitive to structural integrity. This study presents the first structural health monitoring application recruiting pedestrians in a testbed bridge monitoring example. Orchestrating pervasive and participatory pedestrian data might bring new frontiers to structural health monitoring through a smart, mobile, and urban sensing framework.https://doi.org/10.1177/1550147717705240 |
| spellingShingle | Ekin Ozer Maria Q Feng Biomechanically influenced mobile and participatory pedestrian data for bridge monitoring International Journal of Distributed Sensor Networks |
| title | Biomechanically influenced mobile and participatory pedestrian data for bridge monitoring |
| title_full | Biomechanically influenced mobile and participatory pedestrian data for bridge monitoring |
| title_fullStr | Biomechanically influenced mobile and participatory pedestrian data for bridge monitoring |
| title_full_unstemmed | Biomechanically influenced mobile and participatory pedestrian data for bridge monitoring |
| title_short | Biomechanically influenced mobile and participatory pedestrian data for bridge monitoring |
| title_sort | biomechanically influenced mobile and participatory pedestrian data for bridge monitoring |
| url | https://doi.org/10.1177/1550147717705240 |
| work_keys_str_mv | AT ekinozer biomechanicallyinfluencedmobileandparticipatorypedestriandataforbridgemonitoring AT mariaqfeng biomechanicallyinfluencedmobileandparticipatorypedestriandataforbridgemonitoring |