Eco: Ultra-Wearable and Expandable Wireless Sensor Platform
BSN '06 Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks
Sensing from the basement: a feasibility study of unobtrusive and low-cost home activity recognition
UIST '06 Proceedings of the 19th annual ACM symposium on User interface software and technology
PIPENETa wireless sensor network for pipeline monitoring
Proceedings of the 6th international conference on Information processing in sensor networks
NAWMS: nonintrusive autonomous water monitoring system
Proceedings of the 6th ACM conference on Embedded network sensor systems
HydroSense: infrastructure-mediated single-point sensing of whole-home water activity
Proceedings of the 11th international conference on Ubiquitous computing
ViridiScope: design and implementation of a fine grained power monitoring system for homes
Proceedings of the 11th international conference on Ubiquitous computing
UbiComp '07 Proceedings of the 9th international conference on Ubiquitous computing
Towards optimal event detection and localization in acyclic flow networks
ICDCN'12 Proceedings of the 13th international conference on Distributed Computing and Networking
TriopusNet: automating wireless sensor network deployment and replacement in pipeline monitoring
Proceedings of the 11th international conference on Information Processing in Sensor Networks
BlimpProbe: an aerial surveillance platform
Proceedings of the 11th international conference on Information Processing in Sensor Networks
A longitudinal study of vibration-based water flow sensing
ACM Transactions on Sensor Networks (TOSN)
Mapping hidden water pipelines using a mobile sensor droplet
ACM Transactions on Sensor Networks (TOSN)
DoubleDip: leveraging thermoelectric harvesting for low power monitoring of sporadic water use
Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems
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This paper presents PipeProbe, a mobile sensor system for determining the spatial topology of hidden water pipelines behind walls. PipeProbe works by dropping a tiny wireless sensor capsule into the source of the water pipelines. As the PipeProbe capsule traverses the pipelines, it gathers and transmits pressure and angular velocity readings. Through spatio-temporal analysis on the sensor readings, our algorithm locates all turning points in the pipelines and maps their 3D spatial topology. We evaluated the PipeProbe system by developing a prototype and using data collected in our experimental testbed. Results show that the PipeProbe system successfully located and estimated 90% of all pipe tube lengths within 8-cm accuracy on average tube lengths of 76 cm. PipeProbe also successfully located 90% of all turning points within 15-cm accuracy on average length paths of 335cm.