Skip to main content
SpringerLink
Log in

A Review of the Use of Computational Intelligence in the Design of Military Surveillance Networks

  • Chapter
  • First Online:
Recent Advances in Computational Intelligence in Defense and Security

Part of the book series: Studies in Computational Intelligence ((SCI,volume 621))

Abstract

This chapter is a review of how computational intelligence methods have been used to help design various types of sensor networks. We examine wireless sensor networks, fixed sensor networks, mobile ad hoc networks and cellular networks. The goal of this review is to describe the state of the art in using computational intelligence methods for sensor network design, to identify current research challenges and suggest possible future research directions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    This figure was created in Google Maps [68, 69] using data from [15] and [70].

References

  1. Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: A survey on sensor networks. IEEE Commun. Mag. 40, 102–114 Aug 2002

    Google Scholar 

  2. Chong, C.Y., Kumar, S.P.: Sensor networks: evolution, opportunities, and challenges. Proc. IEEE 91(8), 1247–1256 (2003)

    Article  Google Scholar 

  3. Ramanathan, R., Redi, J.: A brief overview of ad hoc networks: challenges and directions. IEEE Commun. Mag. 40(5), 20–22 (2002)

    Article  Google Scholar 

  4. Wolfgang, K., Martin, M.: A survey on real-world implementations of mobile ad-hoc networks. In: Ad Hoc Netw. 5(3), 324–339 (2007)

    Google Scholar 

  5. Jourdan, D.B., de Weck, O.L.: Layout optimization for a wireless sensor network using a multi-objective genetic algorithm. In: IEEE Semi Annular Vehicular Technology Conference (2004)

    Google Scholar 

  6. Kulkarni, R.V., Förster, A., Venayagamoorthy, G.K., Computational intelligence in WSN: a survey. IEEE Comm. Surv. Tutorials 13(1) (2011)

    Google Scholar 

  7. Alirezaei, G., Mathar, R., Ghofrani, P.: Power optimization in sensor networks for passive radar applications. In: IEEE WiSEE, pp. 1–7, 7–9 Nov 2013

    Google Scholar 

  8. Lindsey, S., Raghavendra, C.S.: PEGASIS: Power-efficient gathering in sensor information systems. In: IEEE Aerospace Conference, vol. 3, pp. 3–1125, (2002)

    Google Scholar 

  9. Heinzelman, W.B., Chandrakasan, A.P., Balakrishnan, H.: An application-specific protocol architecture for wireless microsensor networks. IEEE Trans. Wireless Commun. 1(4), 660–670 (2002)

    Article  Google Scholar 

  10. Vodel, M., Hardt, W.: Data aggregation and data fusion techniques in WSN/SANET topologies—a critical discussion. In: IEEE TENCON, pp. 1–6, Nov 2012

    Google Scholar 

  11. Madden, S., Franklin, M.J., Hellerstein, J.M., Hong, W.: A tiny aggregation service for Ad-hoc sensor networks. In: Proceeding of 5th Symposium on Operating Systems Design and Implementation (OSDI), 32, 131–146 (2002)

    Google Scholar 

  12. Dasgupta, K., Kalpakis, K., Namjoshi, P.: An efficient clustering-based heuristic for data gathering and aggregation in sensor networks. In: Wireless Communications and Networking, 2003, vol. 3, pp. 1948–1953 20–20 March 2003

    Google Scholar 

  13. Beyer, D.: Accomplishments of the DARPA SURAN Program. IEEE MILCOM 2, 855–862 (1990)

    Google Scholar 

  14. Gage, D.W.: Command control for many-robot systems. In: Proceeding AUVS-92 (1992)

    Google Scholar 

  15. North Warning System. http://en.wikipedia.org/wiki/North_Warning_System. Accesssed 24 June 2015

  16. AN/FPS-117. http://en.wikipedia.org/wiki/AN/FPS-117. Accesssed 24 June 2015

  17. AN/FPS-124. http://en.wikipedia.org/wiki/AN/FPS-124. Accesssed 24 June 2015

  18. Chu, M., Reich, J.E., Zhao, F.: Distributed attention for large video sensor networks. In: Intelligent Distributed Surveillance System 2004 seminar, London, UK (2004)

    Google Scholar 

  19. He, T., Krishnamurthy, S., Stankovic, J., Abdelzaher, T., Luo, L., Stoleru, R., Yan, T., Gu, L., Hui, J., Krogh, B.: Energy-efficient surveillance system using wireless sensor networks. In: ACM MobiSys ‘04, pp. 270–283. New York, NY, USA (2004)

    Google Scholar 

  20. Hogler, K., Willig, A.: Protocols and Architectures for Wireless Sensor Networks. Wiley, England (2007)

    Google Scholar 

  21. Harte, S., O’Flynn, B., Martinez-Catala, R.V., Popovici, E.M.: Design and implementation of a miniaturised, low power wireless sensor node. In: Proceeding of IEEE ECCTD, pp. 894–897, August 2007

    Google Scholar 

  22. AN/TPS-71 Relocatable Over-The-Horizon Radar (ROTHR). https://janes.ihs.com/CustomPages/Janes/DisplayPage.aspx?DocType=Reference&ItemId=+++1498275&Pubabbrev=JC4IL. Accessed 24 June 2014

  23. Arampatzis, T., Lygeros, J., Manesis, S.: A survey of applications of wireless sensors and wireless sensor networks. In: Proceeding of IEEE International Symposium on Mediterranean Conference on Control and Automation, pp. 719–724, 27–29 June 2005

    Google Scholar 

  24. Dali, W., Chan, H.A.: Analysis of the applications and characteristics of Ad Hoc networks. In: ICCT, pp. 1–4, Nov 2006

    Google Scholar 

  25. Jiejun, K., Jun-Hong, C., Dapeng, W., Gerla, M.: Building underwater ad-hoc networks and sensor networks for large scale real-time aquatic applications. IEEE MILCOM 3, 1535–1541 (2005)

    Google Scholar 

  26. P-18 early-warning radar. https://janes.ihs.com/CustomPages/Janes/DisplayPage.aspx?DocType=Reference&ItemId=+++1498259&Pubabbrev=JC4IL. Accessed 24 June 2014

  27. Doerry, A.W., Dickey, F.M.: Synthetic aperture radar. In: Optics and Photonics News, pp. 28–33, Nov 2004

    Google Scholar 

  28. Lindsey, S., Raghavendra, C.S.: PEGASIS: Power-efficient gathering in sensor information systems. In: IEEE Aerospace Conference, vol. 3, pp. 3–1130 (2002)

    Google Scholar 

  29. Chakrabarty, K., Iyengar, S.S., Qi, H., Cho, E.: Grid coverage for surveillance and target location in distributed sensor networks. IEEE Trans. Comput. 51, 1448–1453 (2002)

    Article  MathSciNet  Google Scholar 

  30. Sakr, Z., Wesolkowski, S.: Sensor network management using multiobjective evolutionary optimization. In: IEEE CISDA, pp. 39–42 (2011)

    Google Scholar 

  31. Oh, S.C., Tan, C.H., Kong, F.W., Tan, Y.S., Ng, K.H., Ng, G.W., Tai, K.: Multiobjective optimization of sensor network deployment by a genetic algorithm. In: IEEE Congress on Evolutionary Computation, pp. 3917–3921 (2007)

    Google Scholar 

  32. Dhillon, S.S., Chakrabarty, K., Iyengar, S.S.: Sensor placement for grid coverage under imprecise detections. In: Conference on Information Fusion, vol. 2, pp. 1581–1587 (2002)

    Google Scholar 

  33. Bose, R.: A smart technique for determining base-station locations in an urban environment. IEEE Trans. Veh. Technol. 50, 43–47 (2001)

    Article  Google Scholar 

  34. Han, J.K., Park, B.S., Choi, Y.S., Park, H.K.: Genetic approach with a new representation for base station placement in mobile communications. In: Proceeding of IEEE Vehicular Technology Conference, vol. 4. pp. 2703–2707, Oct 2001

    Google Scholar 

  35. Meunier, H., Talbi, E., Reininger, P.: A multiobjective genetic algorithm for radio network optimization. In: Proceeding Congress on Evolutionary Computation, vol. 1. pp. 317–324 (2000)

    Google Scholar 

  36. Jiang, X., Chen, Y., Yu, T.: Localized distributed sensor deployment via coevolutionary computation. In: International Conference on Communication and Networking in China (2008)

    Google Scholar 

  37. Amaldi, E., Capone, A., Malucelli, F.. Signori, F.: UMTS radio planning: optimizing base station configuration. In: IEEE Vehicle Conference vol. 2, pp. 768–772, Sept 2002

    Google Scholar 

  38. Osmani, A., Dehghan, M., Pourakbar, H., Emdadi, P.: Fuzzy-based movement-assisted sensor deployment method in wireless sensor networks. In: IEEE Proceeding of the International Conference on Computational Intelligence, Communication System and Networks, India, (2009)

    Google Scholar 

  39. Church, R., ReVelle, C.: The maximal covering location problem. In: Papers of the Regional Science Association, 32, 101–118 (1974)

    Google Scholar 

  40. Howard, A., Matarić, M.J., Sukhatme, G.S.: An incremental self-deployment algorithm for mobile sensor networks. Auton. Robots Special Issue Intell. Embedded Syst. 13(2), 113–126 (2002)

    MATH  Google Scholar 

  41. Howard, A., Matarić, M.J., Sukhatme, G.S.: Mobile sensor network deployment using potential fields: a distributed, scalable solution to the area coverage problem. In: Proceeding International Conference on Distributed Autonomous Robotic Systems, pp. 299–308 (2002)

    Google Scholar 

  42. Zou, Y., Chakrabarty, K.: Sensor deployment and target localization based on virtual forces. Proc. IEEE INFOCOM 2, 1293–1303 (2003)

    Google Scholar 

  43. Madden, S., Franklin, M.J., Hellerstein, J.M., Hong, W.: A tiny aggregation service for Ad-hoc sensor networks. In: Proceeding of 5th Symposium on Operating Systems Design and Implementation (OSDI), vol. 32, pp. 131–146 (2002)

    Google Scholar 

  44. El Kateeb A., Ramesh A., Azzawi, L.: Wireless sensor nodes processor architecture and design. In: Proceeding of IEEE CCECE, pp. 1031–1034, May 2008

    Google Scholar 

  45. Antolin, D., Medrano, N., Calvo, B.: Analysis of the operating life for battery-operated wireless sensor nodes. In: IEEE IECON, pp.3883–3886, Nov 2013

    Google Scholar 

  46. Qela, B., Wainer, G., Mouftah, H.: Simulation of large wireless sensor networks using Cell-DEVS. In: WinterSim Conference, pp. 3189–3200, 13–16 Dec 2009

    Google Scholar 

  47. Schurgers, C., Tsiatsis, V., Ganeriwal, S., Srivastava, M.: Optimizing sensor networks in the energy-latency-density design space. IEEE Trans. Mob. Comput. 1(1), 70–80 (2002)

    Article  Google Scholar 

  48. Geetha, D.D., Nalini, N., Biradar, R.C.: Active node based fault tolerance in wireless sensor network. In: IEEE INDICON, pp. 404–409, 7–9 Dec 2012

    Google Scholar 

  49. Kateeb, A.El., Ramesh, A., Azzawi, L.: Wireless sensor nodes processor architecture and design. In: Proceeding of IEEE CCECE, pp. 1031–1034, May 2008

    Google Scholar 

  50. Harte, S., O’Flynn, B., Martinez-Catala, R.V., Popovici, E.M.: Design and implementation of a miniaturised, low power wireless sensor node. In: Proceeding of IEEE 28th ECCTD, pp. 894–897, August 2007

    Google Scholar 

  51. Cerpa, A., Estrin, D.: ASCENT: adaptive self-configuring sensor networks topologies. IEEE INFOCOM 3, 1278–1287 (2002)

    Google Scholar 

  52. Sousa, M.P., de Alencar, M.S., Kumar, A., Araujo Lopes, W.T.: Scalability in an adaptive cooperative system for wireless sensor networks. In: Ultra Modern Telecommunications and Workshops, ICUMT ‘09. pp. 1–6, 12–14 Oct 2009

    Google Scholar 

  53. Đurišić, M.P., Tafa, M.P., Dimić, G., Milutinović, V.: A survey of military applications of wireless sensor networks. In: Mediterranean Conference on Embedded Computing (2012)

    Google Scholar 

  54. Liu, J.X., Perrone, L.F., Nicol, D.M., Liljenstam, M., Elliott, C., Pearson, D.: Simulation modeling of large-scale ad-hoc sensor networks. In: European Simulation Interoperability Workshop 2001

    Google Scholar 

  55. Afolabi, D., Man, K.L., Liang, H.-N., Lim, E.G., Shen, Z., Lei, C.-U., Krilavicius, T., Yang, Y., Cheng, L., Hahanov, V., Yemelyanov, I.: A WSN approach to unmanned aerial surveillance of traffic anomalies: some challenges and potential solutions. In: Design and Test Symposium 2013, pp. 1–4, 27–30 Sept 2013

    Google Scholar 

  56. Akshay, N., Kumar, M.P., Harish, B., Dhanorkar, S.: An efficient approach for sensor deployments in wireless sensor network. In: Emerging Trends in Robotics and Communication Technologies INTERACT, pp. 350–355, 3–5 Dec 2010

    Google Scholar 

  57. Song, B., Choi, H., Lee, H.S.: Surveillance tracking system using passive infrared motion sensors in wireless sensor network. In: ICOIN 2008. International Conference on Information Networking, pp. 1–5, Jan 2008

    Google Scholar 

  58. Hussain, M.A., Khan, P., Sup, K.K.: WSN research activities for military application. In: Adv. Comm. Tech. 2009. ICACT 2009, pp. 271–274, Feb 2009

    Google Scholar 

  59. Heurtefeux, K., Valois, F.: Topology control algorithms: a qualitative study during the sensor networks life. MASS 2007, 1–7 (2007)

    Google Scholar 

  60. Butun, I., Morgera, S.D., Sankar, R.: A Survey of intrusion detection systems in wireless sensor networks. IEEE Comm. Surv. Tutorials 16(1), 266–282, First Quarter 2014

    Google Scholar 

  61. Butun, I., Sankar, R.: A brief survey of access control in wireless sensor networks. In: IEEE CCNC, pp. 1118–1119, Jan 2011

    Google Scholar 

  62. Jenkins, L.: Challenges in deployment of wireless sensor networks. In: Industrial and Information Systems (ICIIS), Dec 2014

    Google Scholar 

  63. Lee, S.H., Lee, S., Song, H., Lee, H.S.: Wireless sensor network design for tactical military applications. In: Remote large-scale environments. IEEE MILCOM, pp. 1–7, 18–21 Oct 2009

    Google Scholar 

  64. IMO—Automatic Identification System. http://www.imo.org/OurWork/Safety/Navigation/Pages/AIS.aspx. Accessed 24 June 2015

  65. RADARSAT-2—Canadian Space Agency. http://www.asc-csa.gc.ca/eng/satellites/radarsat2/. Accessed 24 June 2015

  66. SPOT 1 to 5. http://www.geo-airbusds.com/en/4388-spot-1-to-spot-5-satellite-images. Accessed 24 June 2015

  67. Herd, A.W.G.: A Practicable Project: Canada, the United States, and the construction of the DEW line. In: Calgary Papers in Military and Strategic Studies Occasional Paper Nr 4, 2011—Can. Arctic Sovereignty and Sec.: Hist. Perspectives, pp. 171–200 (2011)

    Google Scholar 

  68. North Warning System. https://maps.google.com/maps?q=http://tools.wmflabs.org/kmlexport/%3Farticle%3DNorth_Warning_System%26section%3DStations%26usecache%3D1&output=classic&dg=feature. Accessed 12 Feb 2015

    Google Scholar 

  69. List of DEW Line Sites. https://maps.google.com/maps?q=http://tools.wmflabs.org/kmlexport/%3Farticle%3DList_of_DEW_Line_Sites%26usecache%3D1&output=classic&dg=feature. Accessed 12 Feb 2015

    Google Scholar 

  70. List of DEW Line Sites. http://en.wikipedia.org/wiki/List_of_DEW_Line_Sites. Accessed 24 June 2015

  71. Miranda, S.L.C., Baker, C.J., Woodbridge, K., Griffiths, H.D.: Fuzzy logic approach for prioritisation of radar tasks and sectors of surveillance in multifunction radar. IET Radar Sonar Navig. 1(2), 131–141 (2007)

    Article  Google Scholar 

  72. Amato, A., Di Lecce, V., Piuri, V.: Neural network based video surveillance system. In: IEEE International Conference on CI for Homeland Security and Personal Safety (2005)

    Google Scholar 

  73. The cooperative engagement capability. In: Johns Hopkins APL Tech. Dig. 16(4) (1995)

    Google Scholar 

  74. Jensen, D.: SIVAM: Communication, navigation and surveillance for the Amazon. Avionics Mag. http://www.aviationtoday.com/av/military/SIVAM-Communication-Navigation-and-Surveillance-for-the-Amazon_12730.html. Accessed 04 June 2014

  75. Kant, L., Young, K., Younis, O., Shallcross, D., Sinkar, K., Mcauley, A., Manousakis, K., Chang, K., Graff, C.: Network science based approaches to design and analyze MANETs for military applications. IEEE Commun. Mag. 46(11), 55–61 (2008)

    Article  Google Scholar 

  76. Jiejun, K., Jun-Hong, C., Dapeng, W., Gerla, M.: Building underwater ad-hoc networks and sensor networks for large scale real-time aquatic applications. IEEE MILCOM 3, 1535–1541 (2005)

    Google Scholar 

  77. Ilker, B., Ozgur, K.S., Samil, T.: Flying Ad-Hoc networks (FANETs): a survey. Ad Hoc Netw. 11(3), 1254–1270, ISSN 1570-8705 (2013)

    Google Scholar 

  78. Haiyang, C., Cao, Y., Chen, Y.Q.: Autopilots for small fixed-wing unmanned air vehicles: a survey. In: Mechatronics and Automation, 2007, ICMA (2007)

    Google Scholar 

  79. Bow-Nan, C., Moore, S.: A comparison of MANET routing protocols on airborne tactical networks. MILCOM 2012, 1–6 (2012)

    Google Scholar 

  80. Bow-Nan, Ch., Wheeler, J., Veytser, L.: Radio-to-router interface technology and its applicability on the tactical edge. IEEE Commun. Mag. 50(10), 70–77 (2012)

    Article  Google Scholar 

  81. Sethi, S., Udagata, S.K.: The efficient ant routing protocol for MANET. Int. J. Comput. Sci. Eng. 2(7), 2414–2420 (2010)

    Google Scholar 

  82. Lekova, A., Skjelsvik, K., Plagemann, T., Goebel, V.: Fuzzy logic-based event notification in sparse MANETs. AINAW’07 2, 296–301 (2007)

    Google Scholar 

  83. Global Discovery’ Maritime Patrol Aircraft. https://janes.ihs.com/CustomPages/Janes/DisplayPage.aspx?DocType=Reference&ItemId=+++1598078&Pubabbrev=JC4IA. Accessed 24 June 2015

  84. Wojtaszek, D., Wesolkowski, S.: Military fleet mix computation and analysis. IEEE Comput. Intell. Mag. 7(3), 53–61 (2012)

    Article  Google Scholar 

  85. Zhao, F., Shin, J., Reich, J.: Information-driven dynamic sensor collaboration for tracking applications. IEEE Sig. Process. Mag. 19, 61–72 (2002)

    Article  Google Scholar 

  86. Wu, X., Cho, J., d’Auriol, B.J., Lee, S.: Mobility-assisted relocation for self-deployment in wireless sensor networks. IEICE Trans. 90-B(8), 2056–2069 (2007)

    Article  Google Scholar 

  87. Boeing E-767 AWACS.: https://janes.ihs.com/CustomPages/Janes/DisplayPage.aspx?DocType=Reference&ItemId=+++1337360&Pubabbrev=JAU_. Accessed 24 June 2015

  88. Boeing E-3 Sentry.: https://janes.ihs.com/CustomPages/Janes/DisplayPage.aspx?DocType=Reference&ItemId=+++1337336&Pubabbrev=JAU_. Accessed 24 June 2015

  89. P-18.: “Spoon Rest D”. http://www.radartutorial.eu/19.kartei/karte909.en.html. Accessed 24 June 2015

  90. Vostok-D/E mobile surveillance radar. https://janes.ihs.com/CustomPages/Janes/DisplayPage.aspx?DocType=Reference&ItemId=+++1721035&Pubabbrev=JC4IL. Accessed 24 June 2015

  91. Bonissone, P.P., Subbu, R., Lizzi, J.: Multicriteria decision making (MCDM): a framework for research and applications. IEEE CI Mag. 4(3), 48–61 (2009)

    Google Scholar 

  92. Bellavista, P., Cardone, G., Corradi, A., Foschini, L.: Convergence of MANET and WSN in IoT urban scenarios. IEEE Sens. J. 13(10), 3558–3567 (2013)

    Article  Google Scholar 

  93. Gang-Hoon, K., Silvana, T., Ji-Hyong, Ch.: Big-data applications in the government sector. Commun. ACM 57, 78–85 (2014)

    Google Scholar 

  94. Zhou, Zhi-Hua, Chawla, N.V., Jin, Yaochu, Williams, G.J.: Big data opportunities and challenges: discussions from data analytics perspectives. IEEE CI Mag. 9(4), 62–74 (2014)

    Google Scholar 

  95. Choi, A.J.: Internet of things: evolution towards a hyper-connected society. In: IEEE Solid-State Circuits Conference (A-SSCC), pp. 5–8, 10–12 Nov 2014

    Google Scholar 

  96. Shu, H., Liang, Q., Gao, J.: Wireless sensor network lifetime analysis using interval type-2 fuzzy logic systems. IEEE Trans. Fuzzy Syst. 16(2), 416–427 (2008)

    Article  Google Scholar 

  97. Zhang, H., Hou, J.C.: Maintaining sensing coverage and connectivity in large sensor networks. Ad Hoc & Sens. Wireless Netw. 1, 89–124 (2005)

    Google Scholar 

  98. Abielmona, R., Petriu, E.M., Harb, M., Wesolkowski, S.: Mission-driven robotic intelligent sensor agents for territorial security. IEEE CI Mag. 6(1), 55–67 (2011)

    Google Scholar 

  99. Garcia-Rodriguez, J., Angelopoulou, A., Mora-Gimeno, F.J., Psarrou, A.: Building visual surveillance systems with neural networks. In: Computational Intelligence for Privacy and Security, pp. 181–198 (2012)

    Google Scholar 

  100. Bulusu, N., Heidemann, J., Estrin, D.: Adaptive beacon placement. In: Proceeding of International Conference on Distributed Computing System, pp. 489–498, April (2001)

    Google Scholar 

  101. Li, D., Wong, K.D., Hu, Y.H., Sayeed, A.M.: Detection, classification, and tracking of targets. IEEE Signal Process. Mag. 19, 17–29 (2002)

    Google Scholar 

  102. Meesookho, C., Narayanan, S., Raghavendra, C.: Collaborative classification applications in sensor networks. In: Proceeding of IEEE Multichannel and Sensor Array Signal Processing Workshop, Arlington, VA (2002)

    Google Scholar 

  103. Sinopoli, B., Sharp, C., Schenato, L., Shaffert, S., Sastry, S.S.: Distributed control applications within sensor networks. Proc. IEEE 91(8), 1235–1246 (2003)

    Google Scholar 

  104. Arora, A., Dutta, P., Bapat, S., Kulathumani, V., Zhang, H., Naik, V., Mittal, V., Cao, H., Demirbas, M., Gouda, M., Choi Y., Herman, T., Kulkarni, S., Arumugam, U., Nesterenko M., Vora A., Miyashita, M.: A line in the sand: a wireless sensor network for target detection, classification, and tracking, computer networks. Int. J. Comput. Telecom. Netw. 46(5), 605–634, 5 Dec 2004

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Defence Research and Development Canada, Ottawa, Canada

    Mark G. Ball, Blerim Qela & Slawomir Wesolkowski

Authors
  1. Mark G. Ball
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Blerim Qela
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Slawomir Wesolkowski
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mark G. Ball .

Editor information

Editors and Affiliations

  1. Larus Technologies Corporation, Ottawa, Ontario, Canada

    Rami Abielmona

  2. Larus Technologies Corporation, Ottawa, Ontario, Canada

    Rafael Falcon

  3. Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada

    Nur Zincir-Heywood

  4. School of Engineering and Information Technology, University of New South Wales, Canberra, Aust Capital Terr, Australia

    Hussein A. Abbass

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Ball, M.G., Qela, B., Wesolkowski, S. (2016). A Review of the Use of Computational Intelligence in the Design of Military Surveillance Networks. In: Abielmona, R., Falcon, R., Zincir-Heywood, N., Abbass, H. (eds) Recent Advances in Computational Intelligence in Defense and Security. Studies in Computational Intelligence, vol 621. Springer, Cham. https://doi.org/10.1007/978-3-319-26450-9_24

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-26450-9_24

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26448-6

  • Online ISBN: 978-3-319-26450-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation