Device Data Ingestion for Industrial Big Data Platforms with a Case Study†
AbstractDespite 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
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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.
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(3):279.Chicago/Turabian Style
Ji, Cun; Shao, Qingshi; Sun, Jiao; Liu, Shijun; Pan, Li; Wu, Lei; Yang, Chenglei. 2016. "Device Data Ingestion for Industrial Big Data Platforms with a Case Study." Sensors 16, no. 3: 279.
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