International Journal of Engineering Research and Applications (IJERA)
Wireless Sensor Network (WSN) is an area which is deployed with sensors. Those sensors can be multifunctional sensors also. Multifunctional sensors are those sensors which can detect more than one parameter like temp, pressure, CO, ions etc. 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. In this paper, the authors explain and analyses various techniques such as regression, clustering, Bayesian networks and classification with their variants. At the end they have given a detailed comparison in tabular form.