Demo abstract: A microphone sensor based system for green building applications

Acoustic sensing has influenced many applications in green building energy management, such as designing multi-modal energy disaggregation algorithms through fine-grained appliance state identifications or efficiently controlling the HVAC system based on the occupancy of the environment. In this demo paper we build a low-cost system prototype using off-the-shelf commercially available hardware (Raspberry Pi and super high gain microphone) to handle both acoustic sensing and its processing that is portable and easily deployable in any indoor environment. Our system is useful in detecting appliance noise for fine-grained energy metering and human voice for managing building energy footprint. We use the decibel strength of the sound to determine if it should be filtered out as a silence or stored in as an audio of interest. A fast fourier transform that quickly converts the sinusoidal input of the audio signals into its associated frequencies is implemented along with the Mel-Frequency Cepstral Coefficients (MFCCs) feature to distinguish between a human voice and an appliance noise. We also implement all the computations on-chip to quantify the energy-delay benefits.