Compressive Sensing for Remote Flood Monitoring

Although wireless sensor networks are considered as one of the prominent solutions for flood monitoring, energy constraint nature sensors is still a technical challenge. In this letter, we tackle problem by proposing novel energy-efficient remote monitoring system, enabled compressive sensing. The proposed approach compressively captures water level data using i) random block-based sampler, and ii) gradient-based sensing approach, at very low rate, exploiting variability over time. Through extensive experiments on real water-level dataset, show that number packet transmissions well size packets significantly reduced. results also demonstrate significant reduction in transmission. Moreover, reconstruction from compressed samples high quality with negligible degradation, compared to classic compression techniques, even rates.