A Comprehensive study on Distinct Data Collection Techniques using Machine Learning Approaches for WSN

Abstract

Currently in Wireless Sensor Networks, data collection plays a pivotal role. The primary purpose of data collection is to acquire a significant quantity of data while to cut down data dropping due to sensor node memory limitations. Sensor network performance can be improved by employing effective data collection techniques. The primary purpose of data collecting algorithms is to acquire and aggregate data in an energy-efficient manner in order to extend network lifetime. In this study, we cover data collecting Techniques and we applied few Machine Learning Algorithms to enhance PEGASIS so as to increase the Network life span.