Abstract
In this paper, we propose a novel approach for knowledge management in Internet of Things. By utilizing Decisional DNA and deep learning technologies, our approach enables Internet of Things of experiential knowledge discovery, representation, reuse, and sharing among each other. Rather than using traditional machine learning and knowledge discovery methods, this approach focuses on capturing domain’s decisional events via Decisional DNA, and abstracting knowledge through deep learning process based on captured events data. The Decisional DNA is a flexible, domain-independent, and standard experiential knowledge repository solution that allows knowledge to be represented, reused, and easily shared. The main features, architecture, and an initial experiment of this approach are introduced. The presented conceptual approach demonstrates how knowledge can be discovered through its domain’s experiences, and stored and shared as Decisional DNA.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Atzori, L., Antonio, I., Morabito, G.: The internet of things: a survey. Comput. Networks 54(15), 2787–2805 (2010)
Bandyopadhyay, D., Sen, J.: Internet of things: applications and challenges in technology and standardization. Wireless Pers. Commun. 58(1), 49–69 (2011)
Zhang Haoxi, S.C., Szczerbicki, E.: Applying decisional DNA to Internet of Things: the concept and initial case study. Cybern. Syst. 46, 84–93(10) (2015)
Tsai, C., et al.: Data mining for Internet of Things: a survey. IEEE Commun. Surveys Tutorials 16(1), 77–97 (2015)
Sánchez López, T. et al.: Adding sense to the Internet of Things. Pers. Ubiquitous Comput. 16(3), 291–308 (2012)
Zhang Haoxi, S.C., Szczerbicki, E.: Experience-oriented enhancement of smartness for Internet of Things. Intelligent Information and Database Systems, pp. 506–515.Springer (2015)
LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436–444 (2015)
Davenport, T.H.: Saving IT’s Soul: human centered information management. Harvard Bus. Rev. 72(2), 119–131 (1994)
Duhon, B.: It’s all in our Heads. Inform 12(8) (1998)
O’Dell, C., Hubert, C.: The new edge in knowledge: how knowledge management is changing the way we do business. Wiley (2011)
Liao, S.H.: Knowledge management technologies and applications—literature review from 1995 to 2002. Expert Syst. Appl. 25, 155–164 (2003)
Matayong, S., Mahmood, A.K.: The studies of Knowledge Management System in organization: a systematic review. In: Computer & Information Science (ICCIS), 2012 International Conference, IEEE, vol. 1, pp. 221–226 (2012)
Li, B.M., Xie, S.Q., Xu, X.: Recent development of knowledge-based systems, methods and tools for one-of-a-kind production. Knowl. Based Syst. 24(7), 1108–1119 (2011)
Mazilescu, V.: A real-time algorithm for intelligent control embedded in knowledge based systems. Risk Contemp. Econ. 1, 144–152 (2011)
Sun, Z., Finnie, G.: Brain-like architecture and experience based reasoning. In: Proceedings of the 7th JCIS, Cary, North Carolina, USA, pp. 1735–1738 (2003)
Sharma, N., Singh, K., Goyal, D.P.: Is technology universal panacea for knowledge and experience management? Answers from Indian IT Sector. Information Systems, Technology and Management, pp. 187–198. (2012)
Lao, G. et al.: Research on organizational knowledge sharing framework based on CAS theory. International Conference on Service Systems and Service Management, pp. 1–6 (2008)
Sanin, C., Toro, C., Zhang, H. et al.: Decisional DNA: a multi-technology shareable knowledge structure for decisional experience. Neurocomputing 88(7), 42–53 (2012)
Haoxi, Z.: Experience-Oriented Smart Embedded System. The University of Newcastle’s Digital Repository, NOVA (2013)
Ranzato, M., Hinton, G., Lecun, Y.: Guest editorial: deep learning. Int. J. Comput. Vision 2015(113), 1–2 (2015)
Harrington, P.: Machine Learning in Action. Manning Publications Co. (2012)
Acknowledgement
The authors would like to thank the editors and anonymous reviewer for their valuable comments and suggestions on this paper. This work was supported as part of the Project KYTZ201422 by the Scientific Research Foundation of CUIT.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Zhang, H., Sanin, C., Szczerbicki, E. (2016). Experience-Oriented Knowledge Management for Internet of Things. In: Król, D., Madeyski, L., Nguyen, N. (eds) Recent Developments in Intelligent Information and Database Systems. Studies in Computational Intelligence, vol 642. Springer, Cham. https://doi.org/10.1007/978-3-319-31277-4_20
Download citation
DOI: https://doi.org/10.1007/978-3-319-31277-4_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-31276-7
Online ISBN: 978-3-319-31277-4
eBook Packages: EngineeringEngineering (R0)