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Sensors 2016, 16(3), 279; doi:10.3390/s16030279

Device Data Ingestion for Industrial Big Data Platforms with a Case Study

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School of Computer Science & Technology, Shandong University, Jinan 250101, China
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Engineering Research Center of Digital Media Technology, Shandong University, Jinan 250101, China
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Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data, North China University of Technology, Beijing 100144, China
This paper is an extended version of our paper Cun, J.; Shijun, L.; Chenglei, Y.; Lei, W.; Li, P. IBDP: An Industrial Big Data Ingestion and Analysis Platform and Case Studies. In Proceedings of the 2015 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI), Beijing, China, 22–23 October 2015; pp. 223–228.
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Authors to whom correspondence should be addressed.
Academic Editors: Yunchuan Sun, Antonio Jara and Shengling Wang
Received: 16 January 2016 / Revised: 15 February 2016 / Accepted: 18 February 2016 / Published: 26 February 2016
(This article belongs to the Special Issue Identification, Information & Knowledge in the Internet of Things)
View Full-Text   |   Download PDF [1823 KB, uploaded 26 February 2016]   |  

Abstract

Despite having played a significant role in the Industry 4.0 era, the Internet of Things is currently faced with the challenge of how to ingest large-scale heterogeneous and multi-type device data. In response to this problem we present a heterogeneous device data ingestion model for an industrial big data platform. The model includes device templates and four strategies for data synchronization, data slicing, data splitting and data indexing, respectively. We can ingest device data from multiple sources with this heterogeneous device data ingestion model, which has been verified on our industrial big data platform. In addition, we present a case study on device data-based scenario analysis of industrial big data. View Full-Text
Keywords: big data; internet of things; industrial internet of things; device data ingestion big data; internet of things; industrial internet of things; device data ingestion
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Ji, C.; Shao, Q.; Sun, J.; Liu, S.; Pan, L.; Wu, L.; Yang, C. Device Data Ingestion for Industrial Big Data Platforms with a Case Study. Sensors 2016, 16, 279.

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