1. Autonomous Localization in Wireless Sensor Networks Michael Allen Cogent Applied Research Centre Coventry University

2. Wireless Sensor Network Applications Industry Process control Automation Predictive maintenance Scientific Research High spatial and temporal density sampling Habitat monitoring Event detection Military Battlefield surveillance Target tracking Health Care Location aware patient monitoring Patient vital signals Disaster Management Event detection (natural disasters – fire, earthquake) Location awareness (fire fighters looking for survivors) Emergency response

3. Data context, localization In many of these applications, sensor nodes will be reporting data, but this data needs context in space and time – when and where it came from Localization addresses this context problem by Estimating the physical position of an unknown target based on information which is known about it “Where is each of the nodes located?” With respect to wireless sensor networks and the nodes that comprise them, we ask: (Based on Savvides et al [1])

4. Examples of different levels of localization High accuracy Node is at (x,y,z) with 95% confidence of 10cm accuracy The level of localization required is informed by the application of the Wireless Sensor Network (WSN) Room level Node is in building A, floor B, room C Global level Node a is at +34° 0’ 0.00”, -118 ° 0’ 0.00” Domain Specific Node is on part A, machine B, room C

5. How can we perform localization? Need to assign positions to sensor nodes, e.g. Could be done manually, when nodes are deployed Could be done by giving each node GPS (consider power, accuracy and availability) Could get the network to do it for us: –Gather ‘known information’: Get sensor nodes to estimate distances between one another –Calculate and refine relative positions based on this information I am interested in real-life localization and how (and when) it can be applied to real-life problems

6. My research goals In applying localization to given applications, I want to produce a system which has these features: Autonomous – Sensor nodes perform the localization without any external control Distributed – Localization computation is shared out between all sensors in the network (no ‘special’ sensors) Scalable – Deployments may be augmented at a later date, these must be integrated automatically Use in real-life application – Having an application as a ‘driver’ for WSN brings in a whole new set of issues which need to be addressed

7. Application ‘drivers’ Geographic Network Discovery (GND): –Given a dense enough network, localized accurately enough over a terrain, build a map of it Soil Monitoring [2][3]: –densely populated monitoring area –metre order node separation –augmentation likely (Pictures taken from real-life deployment @ UCLA this summer)

8. The end… Thank you! Any questions?

9. References/Links [1] Savvides, A.; Srivastava, M.; Girod, L. & Estrin, D. Raghavendra, C.; Sivalingam, K. & Znati, T. (ed.) Wireless Sensor Networks Localization in Sensor Networks Springer, 2005 [2] Cerpa, A., Elson, J., Estrin, D., Girod, L., Hamilton, M., and Zhao, J. 2001. Habitat monitoring: application driver for wireless communications technology. SIGCOMM Comput. Commun. Rev. 31, 2 supplement (Apr. 2001) [3] Energy Budget and AMARSS project - http://egraham.bol.ucla.edu/SubPages/Energy.html http://egraham.bol.ucla.edu/SubPages/Energy.html James Reserve, CA www.jamesreserve.edu (deployment location)www.jamesreserve.edu TinyOS, Wireless Sensor Nodes www.tinyos.net (key site for WSNs)www.tinyos.net Dust Networks www.dustnetworks.com (Example of industrial WSN provider)www.dustnetworks.com

10. (Backup) Problems with localization Not every method can be applied in every situation Lots of theory, little practice Deployments can be small, sparse, easily recorded by hand Real-life conditions bring a whole host of new problems which simulation doesn’t answer adequately

11. (Backup) Real-life Real-life deployment of sensor networks require careful consideration Systems issues –Actually making the network ‘work’ – data sampling, data transport, time stamping, localization Physical issues –Damaging the phenomena you’re studying, harsh terrain, environment affecting communication Application issues –We know where the data’s coming from, but is it reliable – can we trust it? Can we use it?

12. (Backup) Localization – service for WSN Localization is important Other applications/components within a WSN may need to refer to the positions of nodes If this is provided as a service, then the localization takes care of itself, and the components can rely that the most recent data the get is the most accurate