A review of new developments in Reliability and Connectivity of wireless sensor Technology over recent years

Abstract

Sensors are a crucial component of any intelligent control system. Wireless sensor networks (WSNs) are one of the most rapidly developing information technologies and promise to have a variety of applications in the Internet of Things and for mission critical and safety relevant applications. Clustering is one of the important methods for prolonging the network lifetime in WSNs. It involves grouping of sensor nodes into clusters and electing cluster heads for all the clusters. Reliability is one of the most important attribute of such systems. The main drawback of the wireless sensor network is the restricted power sources of the sensing elements. A unique strength of our study design is that both EEG and fMRI reliability are measured within the same cohort. Our methods are further strengthened by the fact that fMRI and EEG data was collected on the same day for every subject, thus eliminating between-day variability in EEG and fMRI measurements. Thus, observed differences in reliability, agreement and between-subject variance between EEG and fMRI can be largely attributed to the difference in modality as opposed to studies where both modality and cohort vary.