Machine Learning Based Techniques for Node Localization in WSN: A Survey

Abstract

Wireless Sensor Network (WSN) encompasses various tiny sensor nodes. The prime objective of these nodes is the monitoring of the environment. These nodes collect and forward the data for efficient information transmission. During the data transmission, it becomes crucial to localize the nodes. Apart from this, these networks are highly dynamic, and traditional localization techniques are not sufficient to deal with the issues generated by rapidly moving sensor nodes. Hence, machine learning (ML) techniques take place which can tackle such issues conveniently and efficiently. This survey provides a thorough study of various ML techniques used for localization in WSN along with localization techniques. A detailed literature survey has also been produced to show the advantages of using ML techniques for localization.