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Intelligent Data Fusion for Smart IoT Environment: A Survey

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Abstract

Efficient data collection and communication are key tasks in smart IoT environment consisting of a large number of devices. Here imprecise data are generated due to the interferences between the devices and harsh operation condition, and therefore data fusion is needed to gather and extract useful data from multiple sources. A number of approaches for data fusion have been proposed which are based on probability, artificial intelligence, or evidence theory to efficiently aggregate the data. The techniques allow the system to be cognitive and intelligent in terms of decision-making under the uncertainty of data and limited resource. In this paper a comprehensive survey on the data fusion techniques for smart IoT system is presented. The challenges and opportunities with data fusion are also delineated. It will be useful for the researchers in developing the applications and services based on smart IoT environment, which require intelligent decision making.

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Acknowledgements

This work was partly supported by Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIT) (No. 2016-0-00133, Research on Edge computing via collective intelligence of hyperconnection IoT nodes) Korea, under the National Program for Excellence in SW supervised by the IITP(Institute for Information & communications Technology Promotion) (2015-0-00914), Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2019R1I1A1A01058780, Efficient Management of SDN-based Wireless Sensor Network Using Machine Learning Technique) the second Brain Korea 21 PLUS project.

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  1. Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Korea

    Ihsan Ullah

  2. College of Software, Sungkyunkwan University, Suwon, Korea

    Hee Yong Youn

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Ullah, I., Youn, H.Y. Intelligent Data Fusion for Smart IoT Environment: A Survey. Wireless Pers Commun 114, 409–430 (2020). https://doi.org/10.1007/s11277-020-07369-0

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