Anantharaghavan Sridhar
ABSTRACT
We present dBHound, a mobile sensing analytics app for tracking room occupancy and activities while preserving privacy for users. dBHound takes advantage of audio sensors available on mobile devices to collect data about the environment. dBHound is a layer in the mobile operating system API that gathers decibel (dB) data from the device's onboard audio sensors and strips it of sensitive information. Using mobile devices as sensors has the advantage that users do not have to purchase or manage additional sensing devices within the home. Among the different sensor modalities discussed in [4, 1, 2, 5, 3] many of which are limited to detecting a small subset of activities in-home, sound is a highly general and aligns well with everyday human activity. We demonstrate that having access to decibel-level data streams from multiple devices can give us more insight into activity and occupancy patterns than a single sensor, without compromising privacy.
- A. Beltran, V. L. Erickson, and A. E. Cerpa. Thermosense: Occupancy thermal based sensing for hvac control. In Proceedings of the 5th ACM Workshop on Embedded Systems For Energy-Efficient Buildings, BuildSys'13, pages 11:1--11:8, New York, NY, USA, 2013. ACM. Google Scholar
Digital Library
- D. Chen, S. Barker, A. Subbaswamy, D. Irwin, and P. Shenoy. Non-intrusive occupancy monitoring using smart meters. In Proceedings of the 5th ACM Workshop on Embedded Systems For Energy-Efficient Buildings, BuildSys'13, pages 9:1--9:8, New York, NY, USA, 2013. ACM. Google ScholarDigital Library
- G. Cohn, S. Gupta, J. Froehlich, E. Larson, and S. N. Patel. Gassense: Appliance-level, single-point sensing of gas activity in the home. In Proceedings of the 8th International Conference on Pervasive Computing, Pervasive'10, pages 265--282, Berlin, Heidelberg, 2010. Springer-Verlag. Google ScholarDigital Library
- V. L. Erickson, M. Á. Carreira-Perpiñán, and A. E. Cerpa. Observe: Occupancy-based system for efficient reduction of hvac energy. In Information Processing in Sensor Networks (IPSN), 2011 10th International Conference on, pages 258--269. IEEE, 2011.Google Scholar
- M. Jin, R. Jia, Z. Kang, I. C. Konstantakopoulos, and C. J. Spanos. Presencesense: Zero-training algorithm for individual presence detection based on power monitoring. In Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings, BuildSys '14, pages 1--10, New York, NY, USA, 2014. ACM. Google ScholarDigital Library
Recommendations
Controlling Home and Office Appliances with Smart Phones
Most home and office appliances contain microprocessors. All these appliances have some user interface, but many users become frustrated with their appliances' difficult, complex functions. However, a new framework, the personal universal controller (...
Activity recognition with hand-worn magnetic sensors
Activity recognition is a key technology for realizing ambient assisted living applications such as care of the elderly and home automation. This paper proposes a new activity recognition method that employs hand-worn magnetic sensors to recognize a ...
Movement-assisted sensor redeployment scheme for network lifetime increase
MSWiM '07: Proceedings of the 10th ACM Symposium on Modeling, analysis, and simulation of wireless and mobile systemsSensor deployment in mobile sensor networks has received significant attention in recent years. Goals during sensor deployment include improving coverage, achieving load balance, and prolonging the network lifetime. To improve the initial deployment, ...
Comments