CondioSense: high-quality context-aware service for audio sensing system via active sonar

Audio sensing has been applied in various mobile applications for sensing personal and environmental information to improve user's life quality. However, the quality of audio sensing is distorted seriously, while the sensing service is working in incorrect context or the ability of the acoustic sensing is limited (i.e., aging effect of the microphone or interference due to hand covering). To address this challenge, we present CondioSense, a CONtext-aware service for auDIO SENSing system, which identifies the current phone context (i.e., pocket, bag, car, indoor and outdoor) and detects the microphone sensing states. The main idea behind context detection is to extract multipath features from actively generated acoustic signal to identify various contexts since the space size and material among various contexts is different. The sound of physical vibration is explored on microphone sensing state detection, by leveraging that the frequency response of recorded vibration sound changes when the signal propagation in the air is blocked with the microphone covered. We prototype CondioSense on smartphones as an application and perform extensive evaluations. It offers the possibility to recognize various phone contexts with an accuracy exceeding $$92\%$$92% and the accuracy of microphone sensing states detection exceeding $$90\%$$90%.