Parallel dynamic post processing and analysis of recorded sensor data in real time with cloud computing

Markus Krüger, E. Price

Research output: Contribution to conferencePaperResearchpeer-review

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).

Original languageEnglish
Publication statusPublished - 1 Jan 2015
Externally publishedYes
Event7th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 2015 - Torino, Italy
Duration: 1 Jul 20153 Jul 2015

Conference

Conference7th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 2015
CountryItaly
CityTorino
Period1/07/153/07/15

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ASJC Scopus subject areas

  • Building and Construction
  • Civil and Structural Engineering
  • Artificial Intelligence

Cite this

Krüger, M., & Price, E. (2015). Parallel dynamic post processing and analysis of recorded sensor data in real time with cloud computing. Paper presented at 7th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 2015, Torino, Italy.