Abstract
At present, modern manufacturing and management concepts such as digitization, networking, and intelligence are widely used in the industry. Industry automation and information have been unprecedentedly improved, and therefore the entire life of industrial production link involves massive amounts of data, and the status monitoring data of industrial machine have large, multiple source, heterogeneous, and complex data characteristics. What is more, the traditional processing methods and tools could not meet the requirements for massive data, and may miss the best time to repair machine. So, to resolve the challenges that the industrial sensory big data faces, this paper proposes the sensory data collection and storage based on Hadoop platform.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Liu, F.C., Shen, F.: Building a research data science platform from industrial machines. In: IEEE Conference (2015)
Manwal, M., Gupta, A.: Big Data and Hadoop A Technological Survey, Emerging Trends in Computing and Communication Technologies (ICETCCT), February (2018)
Lyu, Y., Fan, X., Liu, K.: An optimized strategy for small files storing and accessing in HDFS. In: IEEE International Conference on Computational Science and Engineering (CSE), vol. 1, pp. 611–614 (2017)
Sarnovsky, M., Bajus, D.: Building environment analysis based on clustering methods from sensory data on top of the Hadoop platform. In: IEEE Conference (2017)
Xie, J.: Construction for the city taxi trajectory data analysis system by Hadoop platform. In: IEEE Conference (2017)
Zhonghua, M.: Seismic data attribute extraction based on Hadoop platform. In: IEEE Conference (2017)
Longley, P.A., Goodchild, M.F., Maguire, D.J., Rhind, D.W.: Geographic Information Systems and Science. Wiley, New York (2001)
Mazumdar, S., Dhar, S.: Hadoop as big data operating system—the emerging approach for managing challenges of enterprise big data platform. In: IEEE Conference (2015)
Ding, X., Tian, B.: A scheme of structured data compression and query on Hadoop platform. In: IEEE Conference (2015)
Yan, H., Song, G.: Based on the Hadoop cloud computing experiment platform. J. Shenyang Norm. Univ. (Natural Sciences) 1, 85–89 (2013)
Acknowledgements
This work was funded by the National Intelligent Manufacturing Project.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Bai, Z., Cui, S., Zhao, C. (2020). Design and Implementation of Sensory Data Collection and Storage Based on Hadoop Platform. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 517. Springer, Singapore. https://doi.org/10.1007/978-981-13-6508-9_106
Download citation
DOI: https://doi.org/10.1007/978-981-13-6508-9_106
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-6507-2
Online ISBN: 978-981-13-6508-9
eBook Packages: EngineeringEngineering (R0)