Abstract
In this paper, we propose SWIFTNET: a fast-reactive data acquisition scheme. SWIFTNET is built on the synergies between compressive sensing and prediction algorithms and limits the energy consumption in environmental monitoring and surveillance networks. We show how this approach dramatically reduces the amount of communication required to monitor the sensor readings in a deployment. We use a wildfire monitoring application that requires high reactiveness with continuous data updates of the monitoring process. Experimental results show that over 50% communication reduction is achieved without loss in accuracy over the common prediction approach. In addition, reactiveness is guaranteed by adjusting the sampling rate from 5 minutes up to 15 seconds.