Abstract
Wireless Video Sensor Networks (WVNs) are lively interest in the research community as flexible means for monitoring isolated areas. WVN effectiveness can be augmented when coupled with a network of low-power, low-cost Pyroelectric InfraRed (PIR) detectors to form a multimodal surveillance system. Autonomy is a key issue as battery replacement is often impractical and even using energy scavenging techniques, such as solar harvester, ad-hoc power management policies are essential to extend network lifetime. In this paper we propose a cooperative policy to manage power consumption of a WVN powered by solar scavengers and supported by a network of PIR sensors that perform a coarse classification of movements. A cost function is calculated by each VSN according to its available energy and information from the PIR network. Such functions are used by a distributed energy aware policy that selects the best VSN to observe the activity. This VSN locally analyzes the image and detects whether or not it represents a person, and only this information is forwarded to users. The effectiveness of this technique is evaluated through simulation and compared to an approach presented in previous work. Results show an increase in system lifetime without any loss in people detection ratio.
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References
Boettcher, P.W., Shaw, G.A.: Energy-constrained collaborative processing for target detection, tracking, and geolocation. In: Zhao, F., Guibas, L.J. (eds.) IPSN 2003. LNCS, vol. 2634, pp. 254–268. Springer, Heidelberg (2003)
Brunelli, D., Moser, C., Benini, L., Thiele, L.: An efficient solar energy harvester for wireless sensor nodes. In: Proceedings of the Conference on Design, Automation and Test in Europe, DATE 2008 (2008)
Datcu, D., Yang, Z., Rothkrantz, L.J.M.: Multimodal. In: Multimodal Surveillance: Sensors, Algorithms, and Systems, pp. 311–338. Artech House Publishers, Boston (July 2007)
Dong, Q.: Maximizing system lifetime in wireless sensor networks. In: Proceedings of the 4th International Symposium on Information Processing in Sensor Networks, IPSN 2005, Piscataway, NJ, USA, p. 3. IEEE Press, Los Alamitos (2005)
Esram, T., Chapman, P.: Comparison of photovoltaic array maximum power point tracking techniques. IEEE Transaction on Energy Conversion 2, 439–449 (2007)
Giridhar, A., Kumar, P.R.: Maximizing the functional lifetime of sensor networks. In: Proceedings of the 4th International Symposium on Information Processing in Sensor Networks, IPSN 2005, Piscataway, NJ, USA, p. 2. IEEE Press, Los Alamitos (2005)
He, T., Vicaire, P., Yan, T., Cao, Q., Zhou, G., Gu, L., Luo, L., Stoleru, R., Stankovic, J.A., Abdelzaher, T.F.: Achieving long-term surveillance in vigilnet, pp. 1–12 (April 2006)
Honeywell security and custom electronic. Is-215t datasheet (2008)
Junker, H., Lukowicz, P., Tröster, G.: Sampling frequency, signal resolution and the accuracy of wearable context recognition systems. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 176–177. Springer, Heidelberg (2004)
Yoshinari, M.M.K.: A human motion estimation method using 3-successive video frames. In: Proc. of Int. Conf. on Virtual Systems and Multimedia GIFU, pp. 135–140 (1996)
Kerhet, A., Magno, M., Leonardi, F., Boni, A., Benini, L.: A low-power wireless video sensor node for distributed object detection. Journal of Real-Time Image Processing 2(4), 331–342 (2007)
Lee, Y.-H., Krishna, C.: Voltage-clock scaling for low energy consumption in real-time embedded systems, pp. 272–279 (1999)
Magno, M., Brunelli, D., Zappi, P., Benini, L.: A solar-powered video sensor node for energy efficient multimodal surveillance. In: Proceedings of the 2008 11th EUROMICRO Conference on Digital System Design Architectures, Methods and Tools, DSD 2008, Washington, DC, USA, pp. 512–519. IEEE Computer Society Press, Los Alamitos (2008)
Murata manufacturing. Pyroelectric infrared sensors (2005)
Paradiso, J., Starner, T.: Energy scavenging for mobile and wireless electronics. IEEE Pervasive Computing 4(1), 18–27 (2005)
Elmer, P.: Frequency range for pyroelectric detectors, http://www.perkinelmer.com
Shyi, C.-N., Weng, W.-F., Wu, H.-T.: Low power platform for wireless sensor network, vol. 2, pp. 417–421 (July 2005)
ST Microelectronics. Motionbee(tm) modules. Technical report
Wang, X., Bi, D., Ding, L., Wang, S.: Bidding and voting strategy for energy efficient collaborative target classification in wireless sensor networks. In: Proceedings of the 2008 Congress on Image and Signal Processing, CISP 2008, Washington, DC, USA, vol. 4, pp. 23–27. IEEE Computer Society Press, Los Alamitos (2008)
Zamora, N., Kao, J.-C., Marculescu, R.: Distributed power-management techniques for wireless network video systems, pp. 1–6 (April 2007)
Zappi, P., Farella, E., Benini, L.: Pyroelectric infrared sensors based distance estimation. To be published in Sensor 2008 (2008)
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Magno, M., Brunelli, D., Zappi, P., Benini, L. (2010). Energy Efficient Cooperative Multimodal Ambient Monitoring. In: Lukowicz, P., Kunze, K., Kortuem, G. (eds) Smart Sensing and Context. EuroSSC 2010. Lecture Notes in Computer Science, vol 6446. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16982-3_5
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DOI: https://doi.org/10.1007/978-3-642-16982-3_5
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