Paper Info
Title
SoQr: sonically quantifying the content level inside containers
Abstract
In this paper, we present SoQr, a sensor that can be attached to an external surface of a household item to estimate the amount of content inside it. The sensor consists of a speaker and a microphone. It outputs a short duration sine wave probing sound to excite a container and its content, and then records the container's impulse response. SoQr then extracts Mean Mel-Frequency Cepstral Coefficients from impulse response recordings of a container with different content levels and learns a support vector machine classifier. Results from a 10-fold cross validation of the prediction models on 19 common household items demonstrate that SoQr can correctly estimate the content level for these products with an average overall F-Measure above 0.96. We then further evaluated SoQr's robustness in different usage scenarios to gain an understanding of how the system performs and specific challenges that might arise when users interact with these products and the sensor.
Year
DOI
Venue
2015
10.1145/2750858.2804264
ACM International Conference on Ubiquitous Computing
Keywords
Field
DocType
Content level measurement, container, active probing, impulse response
Impulse response,Mel-frequency cepstrum,Pattern recognition,Simulation,Computer science,Support vector machine classifier,Robustness (computer science),Human–computer interaction,Artificial intelligence,Cross-validation,Microphone,Sine wave
Conference
Citations 
PageRank 
References 
9
0.56
11
Authors
2
Name
Order
Citations
PageRank
Mingming Fan14810.29
Khai N. Truong22002162.82