AcuTe
Chao Cai, Zhe Chen, Henglin Pu, Liyuan Ye, Menglan Hu, Jun Luo
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 Acoustic Thermometer (AcuTe) as the first 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. Furthermore, to prevent disruptive audible transmissions, we convert chirp signals into white noises and propose a pipeline of signal processing algorithms to denoise received samples. 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 conduct extensive experiments on AcuTe; the results demonstrate a robust performance, a median accuracy of 0.3° C even at a varying humidity level, and the ability to conduct distributed temperature sensing in real-time.