The winning project digitally extracts arrival-time differences from the analog output signals of a microphone array, digitizing only the relevant features. Traditional systems digitize a sensor’s entire analog output and then use digital signal processing to extract the features. Direct analog-to-feature extraction is extremely power efficient, as it avoids the need to deal with power-hungry multi-bit analog-to-digital convertors, large memory blocks, or digital computational blocks. The immediate motivation for the project was to improve the power consumption of a pedestrian safety headset that Columbia graduate students are developing in collaboration with graduate students from the University of North Carolina in a project sponsored by the National Science Foundation.