Abstract
Many of the physical systems in the real world together with their surrounding environments and the networks used for monitoring these systems can be mathematically modeled as a graph. We present a graph-based optimization technique for source localization in such systems. The proposed technique uses the detection times of any particular event or phenomenon of interest at different measurement points within the system to determine the actual location or source of the event. The graphical model represents the propagation characteristics of the physical phenomenon as well as the topology of the monitoring network. The source localization algorithm is validated using experimental data from a wireless sensor network test bed used for monitoring the drinking water distribution system. We also present a method for analyzing the sensitivity of the localization result to estimation errors in the parameters of the graphical model.
| Original language | English |
|---|---|
| Title of host publication | 2013 IEEE Wireless Communications and Networking Conference, WCNC 2013 |
| Pages | 1127-1132 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2013 |
| Externally published | Yes |
| Event | 2013 IEEE Wireless Communications and Networking Conference, WCNC 2013 - Shanghai, China Duration: 7 Apr 2013 → 10 Apr 2013 |
Publication series
| Name | IEEE Wireless Communications and Networking Conference, WCNC |
|---|---|
| ISSN (Print) | 1525-3511 |
Conference
| Conference | 2013 IEEE Wireless Communications and Networking Conference, WCNC 2013 |
|---|---|
| Country/Territory | China |
| City | Shanghai |
| Period | 7/04/13 → 10/04/13 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 6 Clean Water and Sanitation
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