1 / 13

Cuong (Charlie) Pham

eTrack : Target Localization System in Surveillance Sensor Networks Graduate Research Symposium May 04, 2012. Cuong (Charlie) Pham. Challenges. Accuracy Time Cost Noisy environment Anchor locations need to be known in advance. Main Contributions: - Low cost

zeus-rivers
Download Presentation

Cuong (Charlie) Pham

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. eTrack: Target Localization System in Surveillance Sensor NetworksGraduate Research SymposiumMay 04, 2012 Cuong (Charlie) Pham

  2. Challenges • Accuracy • Time • Cost • Noisy environment • Anchor locations need to be known in advance • Main Contributions: • - Low cost • Working with noisy environment • Anchor locations unknown

  3. Can we do better than this? Of course, we do (APIT, Spotlight, Diffusion, etc.)

  4. Equipment • ArduinoUno SMD • ATmega328 microcontroller • 32k Flash Memory • 16Mhz Clock Speed • Xbee Series 1 (802.15.4) • 250kbps Max data rate • 300ft (100m) range Base Station - Network sink

  5. The Machine Learning Approach • Do classification to get location • Define classes • Get training data • Build model • Predict location Data Training Data Learning Class Model

  6. Classes + Training Data 3 4 5 6 1 2 Class 1 Class 2

  7. Location Estimation Xi Xi+1 Yj Yj+1 • The sensor is • In class Xi+1 but not in Xi • In class Yj+1 but not in Yj

  8. Binary Search Xh 6

  9. Accuracy 6

  10. Demo Video • http://www.youtube.com/watch?v=BA6hUwSmWQ8

  11. References [1] XUANLONG NGUYEN, MICHAEL I. JORDAN, and BRUNO SINOPOLI. A Kernel-Based Learning Approach to Ad Hoc Sensor Network Localization [2] Duc A. Tranand Thinh Nguyen. Localization in Wireless Sensor Networks based on Support Vector Machines. IEEE Transactions on Parallel and Distributed Systems (TDPS), 19(7): 981-994, July 2008. [3] Wang, J., Ghosh, R., and Das, S. A survey on sensor localization. Journal of Control Theory and Applications 8, 1 (2010), 2-11. [4] Lingxuan Hu and David Evans. Localization for Mobile Sensor Networks. In Tenth Annual International Conference on Mobile Computing and Networking (MobiCom 2004). Philadelphia, 26 September - 1 October 2004 [5] Tian He, Chengdu Huang, Brian M. Blum, John A. Stankovic, TarekAbdelzaher. Range-Free Localization Schemes for Large Scale Sensor Networks.

  12. Come visit NISLab (S-3-124B)

More Related