Proceedings ArticleDOI
SoundSense: scalable sound sensing for people-centric applications on mobile phones
Hong Lu,Wei Pan,Nicholas D. Lane,Tanzeem Choudhury,Andrew T. Campbell +4 more
- pp 165-178
TLDR
This paper proposes SoundSense, a scalable framework for modeling sound events on mobile phones that represents the first general purpose sound sensing system specifically designed to work on resource limited phones and demonstrates that SoundSense is capable of recognizing meaningful sound events that occur in users' everyday lives.Abstract:
Top end mobile phones include a number of specialized (e.g., accelerometer, compass, GPS) and general purpose sensors (e.g., microphone, camera) that enable new people-centric sensing applications. Perhaps the most ubiquitous and unexploited sensor on mobile phones is the microphone - a powerful sensor that is capable of making sophisticated inferences about human activity, location, and social events from sound. In this paper, we exploit this untapped sensor not in the context of human communications but as an enabler of new sensing applications. We propose SoundSense, a scalable framework for modeling sound events on mobile phones. SoundSense is implemented on the Apple iPhone and represents the first general purpose sound sensing system specifically designed to work on resource limited phones. The architecture and algorithms are designed for scalability and Soundsense uses a combination of supervised and unsupervised learning techniques to classify both general sound types (e.g., music, voice) and discover novel sound events specific to individual users. The system runs solely on the mobile phone with no back-end interactions. Through implementation and evaluation of two proof of concept people-centric sensing applications, we demostrate that SoundSense is capable of recognizing meaningful sound events that occur in users' everyday lives.read more
Citations
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SpiderWalk: Circumstance-aware Transportation Activity Detection Using a Novel Contact Vibration Sensor
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Improvement of Interruptibility Estimation during PC Work by Reflecting Conversation Status
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Incentive mechanism for participatory sensing under budget constraints
TL;DR: It is found that the distribution of data samples is another important factor to the accuracy of sensing result and a greedy-based incentive strategy is proposed which considers both the amount and distribution of samples in data collection.
Improving Bicycle Safety through Automated Real-Time Vehicle Detection
TL;DR: The design of the prototype CyberPhysical bicycle system and the results of the evaluation using video and audio traces collected from bikers demonstrate both the feasibility of the system, exhibiting a high degree of detection accuracy while operating under the real-time and energy constraints of the problem scenario.
Journal ArticleDOI
Fast, Accurate Event Classification on Resource-Lean Embedded Sensors
Hao Jiang,Jason O. Hallstrom +1 more
TL;DR: In-network implementations of a Bayesian classifier and a condensed kd-tree classifier for identifying events of interest on resource-lean embedded sensors are presented.
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