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Graphical-Information Central of Composite Analysis on Big Sensor-Data of Engineering Inspection

Published: 20 October 2015 Publication History

Abstract

The amounts of data volume are escalated in the scientific and engineering fields by the improvement of instruments as higher resolution or rates commence more precise or accurate analyses. The aim of this work is to comprise an information system for maintenance of one physical system, a train consist. The information of the entity is provided by collecting, managing and analyzing the sensor data along the part's lifetime. The data gathered at local storages is staged as time goes on and the data volume overwhelms the processing capacity of an ordinary computing system. The big data processing would be constituted with desktop PCs and a few server machines.

References

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Guinard, D., Trifa, V., Karnouskos, S., Spiess, P., and Savio, D. 2010. Interacting with the SOA-Based Internet of Things: Discovery, Query, Selection, and On-Demand Provisioning of Web Services. IEEE Tran. Serv. Comp. 3, 3, 223--235.
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Jacobs. A. 2009. The Pathologies of Big Data. Comm.ACM 52, 8, 36--44.
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Giner, P., Cetina, C., Fons, J., and Pelechano, V. 2010. Developing Mobile Workflow Support in the Internet of Things. IEEE Perv. Comp. 9, 2, 18--26.
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Chu, X., Nadiminti, K., Jin, C., Venugopal, S., and Buyya, R. 2007. Aneka: Next-Generation Enter-prise Grid Platform for e-Science and e-Business Applications. In Proceedings of the e-Science and Grid Computing. IEEE, 151--159.

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BigDAS '15: Proceedings of the 2015 International Conference on Big Data Applications and Services
October 2015
321 pages
ISBN:9781450338462
DOI:10.1145/2837060
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 October 2015

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Author Tags

  1. Big Sensor-Data
  2. Composite Analysis
  3. Data-Intensive Computing
  4. Measured Data in the Train

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