Probabilistic Models for Data Collection in Wireless Sensor Networks – A Comparative Analysis

摘要

Applying machine learning techniques in Wireless Sensor Network (WSN) has always been a topic of interest for all. Various techniques can be applied for collection of data from various sensor nodes which detect events such as fire. This paper explains and analyses various techniques such as regression, clustering, Bayesian networks and classification with their variants. At the end we have given a detailed comparison in tabular form.