Active Acoustic Sensing for “Hearing” Temperature Under Acoustic Interference

Abstract

Though measuring ambient temperature is often deemed as an easy job, collecting large-scale temperature readings in real-time is still a formidable task. The recent boom of network-ready (mobile) devices and the subsequent mobile crowdsourcing applications do offer an opportunity to accomplish this task, yet equipping commodity devices with ambient temperature sensing capability is highly non-trivial and hence has never been achieved. In this paper, we propose <b>Ac</b> o <b>u</b> stic <b>T</b> h <b>e</b> rmometer (AcuTe+) as an interference-resilient ambient temperature sensor empowered by a single commodity smartphone. AcuTe+ utilizes on-board dual microphones to estimate air-borne sound propagation speed, thereby deriving ambient temperature. To accurately estimate sound propagation speed, we leverage the phase of chirp signals to circumvent the low sample rate on commodity hardware. In addition, we propose to use both structure-borne and air-borne propagations to address the multipath problem. Most importantly, we equip AcuTe+ with a mask-based desnoising algorithm to handle intensive acoustic interference. As a mobile, economical, highly accurate sensor, AcuTe+ may potentially enable many relevant applications, in particular large-scale indoor/outdoor temperature monitoring in real-time. We have conducted extensive experiments on AcuTe+; the results demonstrate a median error of 0.6 <inline-formula><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> C even under severe acoustic interference (overall median 0.3 <inline-formula><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> C), and they also showcase the practical ability of AcuTe+ in real-time distributed temperature sensing.