Survey of Context Information Fusion for Sensor Networks based Ubiquitous Systems

TL;DR

This survey reviews various context information fusion techniques in sensor networks, emphasizing their importance for enabling context-aware ubiquitous systems and highlighting the lack of comprehensive analysis in this area.

Contribution

It provides a comparative analysis of multiple context information fusion methods, architectures, and models used in sensor networks for ubiquitous computing.

Findings

Different fusion techniques help in noise reduction and data inference.

Fusion architectures vary based on application needs.

The survey identifies gaps in current research.

Abstract

Sensor Networks produce a large amount of data. According to the needs this data requires to be processed, delivered and accessed. This processed data when made available with the physical device location, user preferences, time constraints; generically called as context-awareness; is widely referred to as the core function for ubiquitous systems. To our best knowledge there is lack of analysis of context information fusion for ubiquitous sensor networks. Adopting appropriate information fusion techniques can help in screening noisy measurements, control data in the network and take necessary inferences that can help in contextual computing. In this paper we try and explore different context information fusion techniques by comparing a large number of solutions, their methods, architectures and models.