Implicit Study of Techniques and Tools for Data Analysis of Complex Sensory Data

Abstract

The utility as well as contribution of applications in Wireless Sensor Network (WSN) has been experienced by the users from more than a decade. However, with the evolution of time, it has been found that there is a massive growth of data generation even in WSN. The smaller size of sensor with limited battery life and minimal computational capability cannot handle processive such a massive stream of complex data efficiently. Although, there are various types of mining techniques being practiced today, but such tools and techniques cannot be efficiently used for analyzing such complex and massively growing data. This paper therefore discusses about the generation of large data and issues of the existing research techniques by reviewing the literatures and frequently used tools. The study finally briefs about the significant research gap that calls for need of data analytical tools in extracting knowledge from complex sensory data.