Lightweight detection and classification for wireless sensor networks in realistic environments

ABSTRACT

A wide variety of sensors have been incorporated into a spectrum of wireless sensor network (WSN) platforms, providing flexible sensing capability over a large number of low-power and inexpensive nodes. Traditional signal processing algorithms, however, often prove too complex for energy-and-cost-effective WSN nodes. This study explores how to design efficient sensing and classification algorithms that achieve reliable sensing performance on energy-and-cost effective hardware without special powerful nodes in a continuously changing physical environment. We present the detection and classification system in a cutting-edge surveillance sensor network, which classifies vehicles, persons, and persons carrying ferrous objects, and tracks these targets with a maximum error in velocity of 15%. Considering the demanding requirements and strict resource constraints, we design a hierarchical classification architecture that naturally distributes sensing and computation tasks at different levels of the system. Such a distribution allows multiple sensors to collaborate on a sensor node, and the detection and classification results to be continuously refined at different levels of the WSN. This design enables reliable detection and classification without involving high-complexity computation, reduces network traffic, and emphasizes resilience and adaptation to the realistic environment. We evaluate the system with performance data collected from outdoor experiments and field assessments. Based on the experience acquired and lessons learned when developing this system, we abstract common issues and introduce several guidelines which can direct future development of detection and classification solutions based on WSNs.

References

1. Exscal web site. http://www.cast.cse.ohio-state.edu/exscal/index.php?page=main.
2. Honeywell magnetometers. http://www.ssec.honeywell.com/magnetic/.
3. Mica2 mote. http://www.xbow.com/Products/productsdetails.aspx?sid=72.
4. Micropower inpulse radar by advantaca. http://www.advantaca.com/radar.htm.
5. VigilNet web site. http://www.cs.virginia.edu/~control/SOWN/index.html.
6. S. Bhattacharya, H. Kim, S. Prabh, and T. Abdelzaher. Energy-conserving data placement and asynchronous multicast in wireless sensor networks. InIntl. Conf. on Mobile Systems, Applications, and Services (MobiSys), May 2003.
7. R. Brooks, P. Ramanathan, and A. Sayeed. Distributed target classification and tracking in sensor networks. Proceedings of the IEEE, 91(8):1163--1171, 2003.
8. P. Dutta, M. Grimmer, A. Arora, S. Bibyk, and D. Culler. Design of a wireless sensor network platform for detecting rare, random, and ephemeral events. InProc. of Fourth Intl. Conf. on Information Processing in Sensor Networks (IPSN'05), 2005.
9. Z. Feng, S. Jaewon, and R. James. Information-driven dynamic sensor collaboration for target tracking. IEEE Signal Processing Magazine, 19(2), March 2002.
10. T. He, S. Krishnamurthy, J. A. Stankovic, T. Abdelzaher, L. Luo, R. Stoleru, T. Yan, L. Gu, G. Zhou, J. Hui, and B. Krogh. Vigilnet:an integrated sensor network system for energy-efficient surveillance. In submission to ACM Transaction on Sensor Networks, 2004.
11. T. He, S. Krishnamurthy, J. A. Stankovic, T. F. Abdelzaher, L. Luo, R. Stoleru, T. Yan, L. Gu, J. Hui, and B. Krogh. An energy-efficient surveillance system using wireless sensor networks. InProc. of Intl. Conf. on Mobile Systems, Applications, and Services (MobiSys), June 2004.
12. T. He, P. Vicaire, T. Yan, Q. Cao, G. Zhou, L. Gu, L. Luo, R. Stoleru, J. A. Stankovic, and T. Abdelzaher. Achieving Long-Term Surveillance in VigilNet. Insubmission.
13. J. Hill and D. Culler. Mica: A wireless platform for deeply embedded networks. InIEEE Micro, volume 22, pages 12--24, Nov./Dec. 2002.
14. J. Hill, R. Szewczyk, A. Woo, S. Hollar, D. Culler, and K. Pister. System architecture directions for network sensors. Proc. of ASPLOS 2000, Nov. 2000.
15. L. Luo, T. F. Abdelzaher, T. He, and J. A. Stankovic. Design and comparison of lightweight group management strategies in envirosuite. InDistributed Computing in Sensor Systems (DCOSS '05), June 2005.
16. S. Madden, M. Franklin, J. Hellerstein, and W. Hong. TAG: A tiny aggregation service for ad-hoc sensor networks. InProc. of Operating Systems Design and Implementation, Dec. 2002.
17. M. Maroti, B. Kusy, G. Simon, and A. Ledeczi. The flooding time synchronization protocol. InProc. of the 2nd ACM Intl. Conf. on Embedded Networked Sensor Systems (SenSys'04), pages 39--49, New York, NY, USA, 2004.
18. S. Pattem, S. Poduri, and B. Krishnamachari. Energy-quality tradeoffs for target tracking in wireless sensor networks. InProc. of 2nd Intl. Conf. on Information Processing in Sensor Networks (IPSN'03), 2003.
19. G. Simon, M. Maroti, A. Ledeczi, G. Balogh, B. Kusy, A. Nadas, G. Pap, J. Sallai, and K. Frampton. Sensor network-based countersniper system. InProc. of the 2nd ACM Intl. Conf. on Embedded Networked Sensor Systems (SenSys'04), Nov. 2004.
20. R. Stoleru, T. He, and J. A. Stankovic. Walking GPS: A Practical Solution for Localization in Manually Deployed Wireless Sensor Networks. In1st IEEE Workshop on Embedded Networked Sensors EmNetS-I, October 2004.
21. R. Szewczyk, A. Mainwaring, J. Polastre, and D. Culler. An analysis of a large scale habitat monitoring application. InProc. of the 2nd ACM Intl. Conf. on Embedded Networked Sensor Systems (SenSys'04).
22. Q. Wang, W. Chen, R. Zheng, K. Lee, and L. Sha. Acoustic target tracking using tiny wireless sensor devices. Networks (IPSN'03), 2003.
23. N. Xu. Implementation of data compression and FFT in TinyOS. http://enl.usc.edu/~ningxu/papers/lzfft.pdf.
24. P. Zhang, C. Sadler, S. Lyon, and M. Martonosi. Hardware design experiences in zebranet. InProc. of the 2nd ACM Intl. Conf. on Embedded Networked Sensor Systems (SenSys'04), Nov. 2004.
25. F. Zhao, J. Liu, L. Guibas, and J. Reich. Collaborative signal and information processing: An information directed approach. Proceedings of the IEEE, 91(8):1199--1209, 2003.

Index Terms

• Computer systems organization

  • Embedded and cyber-physical systems

  • Real-time systems

• General and reference

  • Cross-computing tools and techniques

    • Design

• Networks

  • Network architectures