Autonomous Localization in Wireless Sensor Networks

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

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

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 (Based on Savvides et al [1]) • With respect to wireless sensor networks and the nodes that comprise them, we ask: “Where is each of the nodes located?”

4. Examples of different levels of localization Global level Node a is at +34° 0’ 0.00”, -118 ° 0’ 0.00” Room level Node is in building A, floor B, room C Domain Specific Node is on part A, machine B, room C 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)

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 • James Reserve, CA www.jamesreserve.edu (deployment location) • TinyOS, Wireless Sensor Nodes www.tinyos.net (key site for WSNs) • Dust Networks www.dustnetworks.com (Example of industrial WSN provider)

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