An Approach to Data Extraction and Visualisation for Wireless Sensor Networks

Abstract

Ever since Descartes introduced planar coordinate systems, visual representations of data have become a widely accepted way of describing scientific phenomena. Modern advances in measurement and instrumentation have required increasingly sophisticated visual representations, to ensure that scientists can quickly and accurately interpret increasingly complex data. Most recently, wireless sensor networks (WSNs) have emerged as a technology which is capable of collecting a vast amount of data over space and time. The sheer volume of the data makes it difficult to be interpreted by humans into meaningful insights. This presents a number of challenges for developers of visualisation techniques which seek to ``map'' the data sensed by a network. Visualisation techniques helps to turn large amounts of raw data into credible visual information such as graphs, charts, or maps, that can assist in understanding of the meaning of that data. In this paper we propose a map as a suitable data visualisation and extraction tool. We aim to develop an in-network distributed information extraction and visualisation service. Such a service would greatly simplify the production of higher-level information-rich representations suitable for informing other network services and the delivery of field information visualisation.