A power optimised and reprogrammable system for smart wireless vibration monitoring
Structural health monitoring (SHM) applications generally utilise high sampling rates, which low-power wireless protocols are not well equipped to handle. Smart sensing approaches can overcome this, by using the processing capability of the sensor nodes to reduce the volume of data prior to communic...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020
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| Online Access: | https://hdl.handle.net/1721.1/126603 |
| _version_ | 1811092219964162048 |
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| author | Long, James Buyukozturk, Oral |
| author2 | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Long, James Buyukozturk, Oral |
| author_sort | Long, James |
| collection | MIT |
| description | Structural health monitoring (SHM) applications generally utilise high sampling rates, which low-power wireless protocols are not well equipped to handle. Smart sensing approaches can overcome this, by using the processing capability of the sensor nodes to reduce the volume of data prior to communication. Most smart sensing approaches are preprogrammed and static. This causes two issues: First, the data processing logic cannot be easily modified, making it difficult to update and improve algorithms once deployed. Secondly, there is limited ability to adapt to changes in the environment or degradation of hardware. To address these problems, we have developed a system that allows users to remotely specify their computational logic on the fly in a MapReduce style syntax. We model these user-specified tasks as a directed acyclic graph, and combine this model with statistics of the performance of each node in the network to formulate an optimisation problem. Solving this problem optimally allocates data processing operations to nodes in the network, such that the total time spent is minimised. We demonstrate a field deployment of this system, which illustrates the advantages of the proposed approach for a typical SHM application, and examines robustness of the system under environmental variations. |
| first_indexed | 2024-09-23T15:14:59Z |
| format | Article |
| id | mit-1721.1/126603 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T15:14:59Z |
| publishDate | 2020 |
| publisher | Wiley |
| record_format | dspace |
| spelling | mit-1721.1/1266032022-10-02T01:38:45Z A power optimised and reprogrammable system for smart wireless vibration monitoring Long, James Buyukozturk, Oral Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Structural health monitoring (SHM) applications generally utilise high sampling rates, which low-power wireless protocols are not well equipped to handle. Smart sensing approaches can overcome this, by using the processing capability of the sensor nodes to reduce the volume of data prior to communication. Most smart sensing approaches are preprogrammed and static. This causes two issues: First, the data processing logic cannot be easily modified, making it difficult to update and improve algorithms once deployed. Secondly, there is limited ability to adapt to changes in the environment or degradation of hardware. To address these problems, we have developed a system that allows users to remotely specify their computational logic on the fly in a MapReduce style syntax. We model these user-specified tasks as a directed acyclic graph, and combine this model with statistics of the performance of each node in the network to formulate an optimisation problem. Solving this problem optimally allocates data processing operations to nodes in the network, such that the total time spent is minimised. We demonstrate a field deployment of this system, which illustrates the advantages of the proposed approach for a typical SHM application, and examines robustness of the system under environmental variations. 2020-08-14T22:44:34Z 2020-08-14T22:44:34Z 2019-11 2019-05 2020-08-14T12:22:15Z Article http://purl.org/eprint/type/JournalArticle 1545-2255 1545-2263 https://hdl.handle.net/1721.1/126603 Long, James and Oral Büyüköztürk. "A power optimised and reprogrammable system for smart wireless vibration monitoring." Structural Control and Health Monitoring 27, 2 (February 2020): e2468 © 2019 John Wiley & Sons, Ltd en http://dx.doi.org/10.1002/stc.2468 Structural Control and Health Monitoring Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Wiley Prof. Buyukozturk via Elizabeth Soergel |
| spellingShingle | Long, James Buyukozturk, Oral A power optimised and reprogrammable system for smart wireless vibration monitoring |
| title | A power optimised and reprogrammable system for smart wireless vibration monitoring |
| title_full | A power optimised and reprogrammable system for smart wireless vibration monitoring |
| title_fullStr | A power optimised and reprogrammable system for smart wireless vibration monitoring |
| title_full_unstemmed | A power optimised and reprogrammable system for smart wireless vibration monitoring |
| title_short | A power optimised and reprogrammable system for smart wireless vibration monitoring |
| title_sort | power optimised and reprogrammable system for smart wireless vibration monitoring |
| url | https://hdl.handle.net/1721.1/126603 |
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