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Location Sensing using Wireless Sensor Networks (D)

Status: Abgeschlossen


During the past years three classes of positioning techniques have evolved: Triangulation, Scene Analysis, and Proximity. In Scene Analysis the value of a feature in the environment is observed and matched to previous readings using a fingerprinting technique. Examples of such systems include RADAR [1] which uses RF, or PowerLine Positioning [4] which uses high-frequency sound. Almost during the same time wireless sensor networks (WSNs) have evolved dramatically and are now even commercially available. In WSNs location is of great interest especially for data analysis and routing [3], and a range of solutions to the positioning problem have been proposed, e.g. [2]. However, most of these solutions involve only one homogeneous and dedicated sensor network.

Description of work

Goal of this thesis is to build a location sensing system for heterogeneous wireless sensor networks. The general approach is to have at least one location aware sensor network in operation, and then have the other networks infer their location over time. Location inference can occur at different levels, like the network layer or the physical layer. In order to demonstrate the results the set of sensor networks later should be fused to one homogeneous sensor network and be visible to the outside world through web-services. This work could be structured in the following manner:

  1. Research on the current state of the art in positioning for wireless sensor networks
  2. Structuring of the problem and modeling the solution approach
  3. Implementation of a prototype including web-services for accessing sensor data and merging readings of the different sensor networks
  4. Evaluation of obtained results and benchmarking with other approaches.


There are no specific requirements for this thesis. However, it would be helpful to have some knowledge in sensor networks, web-services, and machine learning.


[1] Paramvir Bahl and Venkata N. Padmanabhan. RADAR: An in-building RF- based user location and tracking system. In INFOCOM (2), pages 775-784, 2000.
[2] Lazos L., Radha Poovendran, and Capkun S. Rope: robust position estimation in wireless sensor networks. In Fourth International Symposium on Information Processing in Sensor Networks (IPSN 2005), pages 324-331, Los Angeles, California, USA, April 2005.
[3] Kay Römer. Time and location in sensor networks. GI/ITG FachgesprÄach Sensornetze, Berlin, pages 57-60, July 2003.
[4] Patel S.N., Truong K.N., and Abowd G.D. Powerline positioning: A practical sub-room-level indoor location system for domestic use. In Proceedings of Ubicomp 2006, Orange County, California, 2006.
Student/Bearbeitet von: Max Cornelius Meisterhans
Contact/Ansprechpartner: Moritz Köhler

ETH ZurichDistributed Systems Group
Last updated May 7 2012 07:19:03 PM MET mk