Abstract
Recent developments in image and video technologies enabled easy access to a new type of sensor-based networks, Visual Sensor Networks (VSN). VSNs are gaining a lot of attention lately. They are used in several applications including surveillance and telepresence. They consist of several low-cost, low-power visual nodes with sensing, data processing, and communication capabilities. These tiny nodes are able to collect large volumes of images, process them, and send extracted data to each other and to the base station for further analysis. Unfortunately, the huge amount of data captured and processed is faced with the limited resources of such platforms. There are several challenges involved with the design and implementation of VSNs. This chapter presents an overview of visual nodes, architectures, and challenges. It also reviews available VSN platforms and compares their processing capabilities, highlighting the need for new lightweight but efficient image processing algorithms and architectures.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
W. Dargie and C. Poellabauer, Fundamentals of wireless sensor networks: theory and practice, John Wiley and Sons, 2010.
S. Soro and W. Heinzelman, “A survey of visual sensor networks,” Advances in Multimedia, vol. 2009, 2009.
Y. Charfi, B. Canada, N. Wakamiya and M. Murata, “Challenging issues in visual sensor networks,” IEEE Wireless Communications, pp. 44-49, 2009.
D. M. Sheen, D. L. McMakin and T. E. Hall, “Three-dimensional millimeter-wave imaging for concealed weapon detection,” IEEE Transactions on Microwave Theory and Techniques, vol. 49, no. 9, pp. 1581-1592, 2001.
J. Wang, C. Qimei, Z. De and B. Houjie, “Embedded wireless video surveillance system for vehicle,” in International Conference on Telecommunications, Chengdu, China, 2006.
G. Barrenetxea, F. Ingelrest, G. Schaefer and M. Vetterli, “Wireless sensor networks for environmental monitoring: the SensorScope experience,” in IEEE International Zurich Seminar on Communications, Zurich, 2008.
T. H. Chen, P. H. Wu and Y. C. Chiou, “An early fire-detection method based on image processing,” in IEEE International Conference on Image Processing, Singapore, 2004.
L. Cutrona, W. Vivian, E. Leith and G. Hall, “A high-resolution radar combat-surveillance system,” IRE Transaction on Military Electronics, Vols. MIL-5, no. 2, pp. 127-131, 2009.
M. Skolnik, G. Linde and K. Meads, “Senrad: an advanced wideband air-surveillance radar,” IEEE Transactions on Aerospace and Electronic Systems, vol. 37, no. 4, pp. 1163-1175, 2001.
S. Fleck and W. Strasser, “Smart camera based monitoring system and its application to assisted living,” Proceedings of the IEEE, vol. 96, no. 10, pp. 1698-1714, 2008.
O. Schreer, P. Kauff and T. Sikora, 3D Videocommunication, Chichester, UK: John Wiley and Sons, 2005.
W. C. Feng, E. Kaiser, M. Shea and B. L., “Panoptes: scalable low-power video sensor networking technologies,” ACM Transactions on Multimedia Computing, Communications, and Applications, vol. 1, no. 2, pp. 151-167, 2005.
P. Chen, P. Ahammed, C. Boyer, S. Huang, L. Lin, E. Lobaton, M. Meingast, S. Oh, S. Wang, P. Yan, A. Y. Yang, C. Yeo, L. C. Chang, D. Tygar and S. S. Sastry, “CITRIC: a low-bandwidth wireless camera network platform,” in Proc. International Conference on Distributed Smart Cameras, 2008.
S. Hengstler, D. Prashanth, S. Fong and H. Aghajan, “MeshEye: a hybrid-resolution smart camera mote for applications in distributed intelligent surveillance,” in 6th International Symposium on Information Processing in Sensor Networks, Cambridge, 2007.
“Security & surveillance: envisioning a safer world,” [Online]. Available: http://www.ovt.com/applications/application.php?id=10.
J. Boice, X. Lu, C. Margi, G. Stanek, G. Zhang, R. Manduchi and K. Obraczka, “Meerkats: a power-aware, self-managing wireless camera network for wide area monitoring,” in Proceedings Workshop on Distributed Smart Cameras, 2006.
M. Rahimi, R. Baer, O. I. Iroezi, J. C. Garcia, J. Warrior, D. Estrin and M. Srivastava, “Cyclops: in situ image sensing and interpretation in wireless sensor networks,” in International Conference on Embedded Networked Sensor Systems, New York, 2005.
A. Kerhet, M. Magno, F. Leonardi, A. Boni and L. Benini, “A low-power wireless video sensor node for distributed object detection,” Journal on Real-Time Image Processing, vol. 2, pp. 331-342, 2007.
A. Rowe, D. Goal and R. Rajkumar, “FireFly Mosaic: a vision-enabled wireless sensor networking system,” in IEEE International Real-Time Systems Symposium, 2007.
M. Zhang and W. Cai, “Vision mesh a novel video sensor networks platform for water conservation engineering,” in IEEE International Conference on Computer Science and Information Technology, 2010.
“CC1000: single chip very low power RF transceiver,” [Online]. Available: http://www.ti.com/lit/ds/symlink/cc1000.pdf.
“CC2420: 2.4 GHz IEEE 802.15.4/ZigBee-ready RF transceiver,” [Online]. Available: http://inst.eecs.berkeley.edu/~cs150/Documents/CC2420.pdf.
“A look at the basics of bluetooth wireless technology,” [Online]. Available: http://www.bluetooth.com/Pages/basics.aspx.
B. P. Crow, I. Widjaja, J. G. Kim and P. T. Sakai, “IEEE 802.11 wireless local area networks,” IEEE Communications Magazine, vol. 35, no. 9, pp. 116-126, 2002.
“Wireless sensor networks powered by ambient energy harvesting (WSN-HEAP) - survey and challenges,” in International Conference on Wireless Communication, Vehicular Technology, Information Theory and Aerospace & Electronic Systems Technology, Aalborg, 2009.
D. Niyato, E. Hossain, M. M. Rashid and V. K. Bhargava, “Wireless sensor networks with energy harvesting technologies: a game-theoretic approach to optimal energy management,” IEEE Wireless Communications Magazine, vol. 14, no. 4, pp. 90-96, 2007.
B. Tavli, K. Bicakci, R. Zilan and J. M. Barcelo-Ordinas, “A survey of visual sensor network platforms,” Multimedia Tools and Applications, vol. 60, no. 3, pp. 689-726, 2011.
P. Kulkarni, D. Ganesan, P. Shenoy and Q. Lu, “SensEye: a multi tier camera sensor network,” in ACM International Conference on Multimedia, 2005.
A. M. McIvor, “Background subtraction techniques,” in Image and Vision Computing New Zealand, Hamilton, 2000.
L. Wang, W. Hu and T. Tan, “Recent developments in human motion analysis,” Pattern recognition, vol. 36, no. 3, pp. 585-601, March 2003.
A. Redondi, M. Cesana and M. Tagliasacchi, “Low bitrate coding schemes for local image descriptors,” in IEEE International Workshop on Multimedia Signal Processing, 2011.
D. L. Donoho, “Compressed sensing,” IEEE Transactions on Information Theory, vol. 52, no. 4, pp. 1289-1306, 2006.
M. Fornasier and H. Rauhu, “Compressive sensing,” in Handbook of mathematical methods in imaging, Springer, 2011, pp. 187-228.
J. W. D. Slepian, “Noiseless coding of correlated information sources,” IEEE Transactions on Information Theory, vol. 19, pp. 471-480, 1973.
A. D. Wyner and J. Ziv, “The rate-distortion function for source coding with side information at the decoder,” IEEE Transactions on Information Theory, vol. 22, no. 1, pp. 1-10, 1976.
J. Di, A. Men, B. Yang, F. Ye and X. Zhang, “An improved distributed video coding scheme for wireless video sensor network,” in IEEE Vehicular Vehicular, 2011.
C. Li, J. Zou, H. Xiong and C. W. Chen, “Joint coding/routing optimization for distributed video sources in wireless visual sensor networks,” IEEE Transactions on Circuits, Systems and Video Technology, vol. 21, no. 2, pp. 141-155, 2011.
X. Wang, G. Xing, Y. Zhang, C. Lu, R. Pless and C. Gill, “Integrated coverage and connectivity configuration in wireless sensor networks,” in International Conference on Embedded Networked Sensor Systems, 2003.
C.-F. Huang, Y.-C. Tseng and L.-C. Lo, “The coverage problem in three-dimensional wireless sensor networks,” Journal of Interconnection Networks, vol. 8, no. 3, pp. 209-227, 2007.
S. Soro and W. B. Heinzelman, “On the coverage problem in video-based wireless sensor networks,” in IEEE Conference on Broadband Networks, 2005.
A. Yoshida, K. Aoki and S. Araki, “Cooperative control based on reaction-diffusion equation for surveillance system,” in Knowledge-Based Intelligent Information and Engineering Systems, 2005.
Y. Charfi, N. Wakamiya and M. Murata, “Adaptive and reliable multipath transmission in wireless sensor networks using forward error correction and feedback,” in IEEE Conference on Wireless Communications and Networking, 2007.
K.-Y. Chow, K.-S. Lui and E. Y. Lam, “Efficient on-demand image transmission in visual sensor networks,” EURASIP Journal on Applied Signal Processing, vol. 2007, pp. 1-11, 2007.
C. D.-F. V. Lecuire and N. Krommenacker, “Energy-efficient transmission of wavelet-based images in wireless sensor networks,” EURASIP Journal on Image Video Processing, 2007.
S. B. Wicker and V. K. Bhargava, Reed-Solomon codes and their application, John Wiley and Sons, 1999.
J. J. Ong, L. Ang and K. Seng, “FPGA implementation reed solomon encoder for visual sensor networks,” in International Conference on Computer Communication and Management, 2011.
H. Wu and A. A. Abouzeid, “Error resilient image transport in wireless sensor networks,” Computer Networks, vol. 50, no. 15, pp. 2873-2887, 2006.
M. Maimour, C. Pham and J. Amelot, “Load repartition for congestion control in multimedia wireless sensor networks with multipath routing,” in International Symposium on Wireless Pervasive Computing, 2008.
S. Misra, M. Reisslein and G. Xue, “A survey of multimedia streaming in wireless sensor networks,” IEEE Communications Surveys and Tutorials, vol. 10, no. 4, pp. 18-39, 2008.
W. Ye, J. Heidemann and D. Estrin, “An energy-efficient MAC protocol for wireless sensor networks,” in International Annual Joint Conference of the IEEE Computer and Communication Societies, 2002.
Y. Andreopoulos, N. Mastronarde and M. v. d. Schaar, “Cross-layer optimized video streaming over wireless multi-hop mesh networks,” IEEE Journal on Selected Areas in communications, vol. 24, no. 11, pp. 2104-2115, 2006.
Q. Li and M. V. D. Schaar, “Providing adaptive qos to layered video over wireless local area networks through real-time retry limit adaptation,” IEEE Transactions on Multimedia, vol. 6, no. 2, pp. 278-290, 2004.
M. v. d. Schaar and D. Turaga, “Content-based cross-layer packetization and retransmission strategies for wireless multimedia transmission,” IEEE Transactions on Multimedia, vol. 9, no. 1, pp. 185-197, 2007.
D. Lymberopoulos and A. Savvides, “XYZ: a motion-enabled, power aware sensor node platform for distributed sensor network applications,” in International Conference on Information Processing in Sensor Networks, 2005.
R. Kleihorst, A. Abbo, B. Schueler and A. Danillin, “Camera mote with a high-performance parallel processor for realtime frame-based video processing,” in International Conference on Distributed Smart Cameras, 2008.
“Crossbow technology,” [Online]. Available: http://www.xbow.com.
“CMUcam: open source programmable embedded color vision sensors,” [Online]. Available: http://www.cmucam.org/.
“Tmote sky,” [Online]. Available: http://www.eecs.harvard.edu/~konrad/projects/shimmer/references/tmote-sky-datasheet.pdf.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Al Najjar, M., Ghantous, M., Bayoumi, M. (2014). Visual Sensor Nodes. In: Video Surveillance for Sensor Platforms. Lecture Notes in Electrical Engineering, vol 114. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1857-3_2
Download citation
DOI: https://doi.org/10.1007/978-1-4614-1857-3_2
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-1856-6
Online ISBN: 978-1-4614-1857-3
eBook Packages: EngineeringEngineering (R0)