  The popularity of Internet-of-Things (IoT) has provided us with unprecedented
opportunities to enable a variety of emerging services in a smart home
environment. Among those services, sensing the liquid level in a container is
critical to building many smart home and mobile healthcare applications that
improve the quality of life. This paper presents LiquidSense, a liquid-level
sensing system that is low-cost, high accuracy, widely applicable to different
daily liquids and containers, and can be easily integrated with existing smart
home networks. LiquidSense uses an existing home WiFi network and a low-cost
transducer that attached to the container to sense the resonance of the
container for liquid level detection. In particular, our system mounts a
low-cost transducer on the surface of the container and emits a well-designed
chirp signal to make the container resonant, which introduces subtle changes to
the home WiFi signals. By analyzing the subtle phase changes of the WiFi
signals, LiquidSense extracts the resonance frequency as a feature for liquid
level detection. Our system constructs prediction models for both continuous
and discrete predictions using curve fitting and SVM respectively. We evaluate
LiquidSense in home environments with containers of three different materials
and six types of liquids. Results show that LiquidSense achieves an overall
accuracy of 97% for continuous prediction and an overall F-score of 0.968 for
discrete prediction. Results also show that our system has a large coverage in
a home environment and works well under non-line-of-sight (NLOS) scenarios.
