Demo Abstract: Hibernets: Energy-Efficient Sensor Networks Using Analog Signal Processing

In-network processing is recommended for many sensor network applications to reduce communication and improve energy efficiency. However, constraints on memory, speed, and energy currently limit the processing capabilities within a sensor network. By integrating ultra-low-power analog circuitry with sensor nodes, we can reduce the node's power consumption and extend the node's processing capacity. We present a custom analog front-end which performs spectral analysis at a fraction of the power used by a digital counterpart. This front-end has been combined with a TelosB mote to (1) selectively wake up the mote based upon spectral content of the signal, thus increasing battery life without missing interesting events, and to (2) achieve low-power signal analysis using an analog spectral decomposition block, freeing up digital computation resources for higher-level analysis.