Making Sense of Sensor Networks

Sensor networks are novel data routing and processing structures that allow for the emergence of data-centric applications, such as the controlled irrigation of agricultural fields and the continuous monitoring of an elderly person’s health. Numerous challenges exist including sensor coverage, power consumption, interoperability, security, integrated display and user bandwidth. In this white paper, we concentrate on the challenges presented in trying to make sense of the collected data. We first introduce the conventional techniques emphasizing the prominent ones: neural networks, Bayesian networks, Kalman filters and Dempster-Shafer methods. We then briefly present our solution, and the steps involved in its development.