Abstract

Developments in wireless sensor networks (WSNs) are strongly focused on minimizing the power requirements of sensor nodes. As sensors with significantly large resource requirements are introduced into WSN systems, algorithms must be developed to maximise the information returned per sensor reading. The integration of “lab on a chip ” sensors into WSNs widens the focus from power reduction to the reduction of sensor usage, since the limited reagent resources available to such nodes will limit node lifetime. This project builds upon the prototype Gumsense sensor node to create a platform that is suitable for the development and deployment of WSNs that incorporate “autonomous experimentation ” algorithms. Substantial changes are made to the architecture of the Gumsense hardware platform in pursuit of this new philosophy. The platform is upgraded so that data can be sampled whilst remaining in a low power sleep state to minimise resource usage. C and Tcl libraries are developed to enable the rapid development

Citations