Multimodal Asynchronous Kalman Filter for monitoring unstable rock slopes
AbstractUnstable rock slopes pose a hazard to inhabitants and infrastructure in their vicinity, necessitating advanced monitoring methodologies for timely risk assessment and mitigation. Recent geotechnical monitoring techniques often rely on sensor data fusion to enhance forecasting for imminent fa...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2023-12-01
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| Series: | Geomatics, Natural Hazards & Risk |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/19475705.2023.2272575 |
| _version_ | 1797389186931621888 |
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| author | Lukas Schild Thomas Scheiber Paula Snook Reza Arghandeh Stig Frode Samnøy Alexander Maschler Lene Kristensen |
| author_facet | Lukas Schild Thomas Scheiber Paula Snook Reza Arghandeh Stig Frode Samnøy Alexander Maschler Lene Kristensen |
| author_sort | Lukas Schild |
| collection | DOAJ |
| description | AbstractUnstable rock slopes pose a hazard to inhabitants and infrastructure in their vicinity, necessitating advanced monitoring methodologies for timely risk assessment and mitigation. Recent geotechnical monitoring techniques often rely on sensor data fusion to enhance forecasting for imminent failures. Our investigation extends beyond a single sensor type to data fusion for heterogeneous sensor networks using a Multimodal Asynchronous Kalman Filter. We illustrate the application of the proposed method on a case study data set consisting of data from an on-site sensor network enriched by remote sensing data. Employing a Multimodal Asynchronous Kalman Filter, we capitalise on the distinct resolutions inherent in each sensor input. The outcome was a combined dataset with a high spatiotemporal resolution. Our approach facilitates the estimation of essential physical attributes for monitored objects, encompassing translation, rotation, velocities and accelerations. The case study site was an unstable rock section of ca. 50.000 m3 in Aurland, Norway, which collapsed as a multi-stage failure in July 2023. Our method can be transposed to various sites with distinct sensor networks, enhancing state estimations for objects on unstable rock slopes. These estimations can significantly improve applications such as risk assessment and robust early-warning systems, enhancing predictions of critical failure points. |
| first_indexed | 2024-03-08T22:52:13Z |
| format | Article |
| id | doaj.art-14293c17eddd42238f12c2ec40e8d0a8 |
| institution | Directory Open Access Journal |
| issn | 1947-5705 1947-5713 |
| language | English |
| last_indexed | 2024-03-08T22:52:13Z |
| publishDate | 2023-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geomatics, Natural Hazards & Risk |
| spelling | doaj.art-14293c17eddd42238f12c2ec40e8d0a82023-12-16T08:49:47ZengTaylor & Francis GroupGeomatics, Natural Hazards & Risk1947-57051947-57132023-12-0114110.1080/19475705.2023.2272575Multimodal Asynchronous Kalman Filter for monitoring unstable rock slopesLukas Schild0Thomas Scheiber1Paula Snook2Reza Arghandeh3Stig Frode Samnøy4Alexander Maschler5Lene Kristensen6Department of Environmental Sciences, Western Norway University of Applied Sciences, Sogndal, NorwayDepartment of Environmental Sciences, Western Norway University of Applied Sciences, Sogndal, NorwayDepartment of Environmental Sciences, Western Norway University of Applied Sciences, Sogndal, NorwayDepartment of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, NorwayDepartment of Civil Engineering, Western Norway University of Applied Sciences, Bergen, NorwayDepartment of Environmental Sciences, Western Norway University of Applied Sciences, Sogndal, NorwayNorwegian Water Resources and Energy Directorate, Trondheim, NorwayAbstractUnstable rock slopes pose a hazard to inhabitants and infrastructure in their vicinity, necessitating advanced monitoring methodologies for timely risk assessment and mitigation. Recent geotechnical monitoring techniques often rely on sensor data fusion to enhance forecasting for imminent failures. Our investigation extends beyond a single sensor type to data fusion for heterogeneous sensor networks using a Multimodal Asynchronous Kalman Filter. We illustrate the application of the proposed method on a case study data set consisting of data from an on-site sensor network enriched by remote sensing data. Employing a Multimodal Asynchronous Kalman Filter, we capitalise on the distinct resolutions inherent in each sensor input. The outcome was a combined dataset with a high spatiotemporal resolution. Our approach facilitates the estimation of essential physical attributes for monitored objects, encompassing translation, rotation, velocities and accelerations. The case study site was an unstable rock section of ca. 50.000 m3 in Aurland, Norway, which collapsed as a multi-stage failure in July 2023. Our method can be transposed to various sites with distinct sensor networks, enhancing state estimations for objects on unstable rock slopes. These estimations can significantly improve applications such as risk assessment and robust early-warning systems, enhancing predictions of critical failure points.https://www.tandfonline.com/doi/10.1080/19475705.2023.2272575Data fusionmonitoringlandslideunstable rock slopeKalman Filtersensor network |
| spellingShingle | Lukas Schild Thomas Scheiber Paula Snook Reza Arghandeh Stig Frode Samnøy Alexander Maschler Lene Kristensen Multimodal Asynchronous Kalman Filter for monitoring unstable rock slopes Geomatics, Natural Hazards & Risk Data fusion monitoring landslide unstable rock slope Kalman Filter sensor network |
| title | Multimodal Asynchronous Kalman Filter for monitoring unstable rock slopes |
| title_full | Multimodal Asynchronous Kalman Filter for monitoring unstable rock slopes |
| title_fullStr | Multimodal Asynchronous Kalman Filter for monitoring unstable rock slopes |
| title_full_unstemmed | Multimodal Asynchronous Kalman Filter for monitoring unstable rock slopes |
| title_short | Multimodal Asynchronous Kalman Filter for monitoring unstable rock slopes |
| title_sort | multimodal asynchronous kalman filter for monitoring unstable rock slopes |
| topic | Data fusion monitoring landslide unstable rock slope Kalman Filter sensor network |
| url | https://www.tandfonline.com/doi/10.1080/19475705.2023.2272575 |
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