Abstract
Raw sensor data collected by monitoring networks requires use-case based post-processing prior to visualization or analysis. However, with larger monitoring projects accumulating raw data in the magnitude of gigabytes, it becomes infeasible to duplicate the entire data set for each analysis use case. Filtering the raw data prior to storage is also not an option since valuable information might be lost or distorted. With modern cloud computing techniques available, it now becomes possible to dynamically filter and process large sets or raw data in real time on a per request base. The paper presents such an approach using cascaded filters for data cross- correlation and visualization which is executed in parallel within a scalable multiprocessing web based environment (cloud).
Originalsprache | englisch |
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Publikationsstatus | Veröffentlicht - 1 Jan. 2015 |
Extern publiziert | Ja |
Veranstaltung | 7th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 2015 - Torino, Italien Dauer: 1 Juli 2015 → 3 Juli 2015 |
Konferenz
Konferenz | 7th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 2015 |
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Land/Gebiet | Italien |
Ort | Torino |
Zeitraum | 1/07/15 → 3/07/15 |
ASJC Scopus subject areas
- Bauwesen
- Tief- und Ingenieurbau
- Artificial intelligence