Intelligent Data Fusion for Smart IoT Environment: A Survey

• Published in: Wireless personal communications Vol. 114; no. 1; pp. 409 - 430
• Main Authors: Ullah, Ihsan, Youn, Hee Yong
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.09.2020; Springer Nature B.V
• Subjects: Artificial intelligence; Communications Engineering; Computer Communication Networks; Data collection; Data integration; Decision making; Electronic devices; Engineering; Networks; Signal,Image and Speech Processing; Wireless sensor network; Smart IoT environment; Evidence theory; Decision making; Machine learning; Data fusion; Clustering
• ISSN: 0929-6212; 1572-834X
• DOI: 10.1007/s11277-020-07369-0

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.