A Stochastic Model for Environment Sensing Correction
Yasser Morgan, Abdul Bais, Moustafa El–Gindy · IETE Journal of Research · 2013
AbstractWireless Sensor Networks (WSN) are growing in popularity and penetrating newer fields of applications more than ever. Gradually, we are relying on WSNs to perform more complex tasks with increasing cognitive abilities. At the core of the WSN research transpires, the need is to achieve accurate sensing at real-time. Unfortunately, confidence in sensors’ readings decreases in harsh environments and as a result of normal reading errors, message loss, or even low battery operations. The complex problem of dealing with corrections and in some cases shredding the outcome of entire deployments leads to loss of effort, time, and money. Classic approaches for correcting laboratory experiments like curve fitting and least square are well known and have been established for decades. But little research attempts have been made to correct and recalibrate sensors observations in real-time. Furthermore, classic approaches for correcting sensor observations require higher interaction between sensors to a level we...