IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v27y2016i6d10.1007_s10845-014-0946-z.html
   My bibliography  Save this article

Target coverage in camera networks for manufacturing workplaces

Author

Listed:
  • Samer Hanoun

    (Deakin University)

  • Asim Bhatti

    (Deakin University)

  • Doug Creighton

    (Deakin University)

  • Saeid Nahavandi

    (Deakin University)

  • Phillip Crothers

    (Boeing Research & Technology)

  • Celeste Gloria Esparza

    (GM Holden)

Abstract

In this paper, we investigate the camera network placement problem for target coverage in manufacturing workplaces. The problem is formulated to find the minimum number of cameras of different types and their best configurations to maximise the coverage of the monitored workplace such that the given set of target points of interest are each k-covered with a predefined minimum spatial resolution. Since the problem is NP-complete, and even NP-hard to approximate, a novel method based on Simulated Annealing is presented to solve the optimisation problem. A new neighbourhood generation function is proposed to handle the discrete nature of the problem. The visual coverage is modelled using realistic and coherent assumptions of camera intrinsic and extrinsic parameters making it suitable for many real world camera based applications. Task-specific quality of coverage measure is proposed to assist selecting the best among the set of camera network placements with equal coverage. A 3D CAD of the monitored space is used to examine physical occlusions of target points. The results show the accuracy, efficiency and scalability of the presented solution method; which can be applied effectively in the design of practical camera networks.

Suggested Citation

  • Samer Hanoun & Asim Bhatti & Doug Creighton & Saeid Nahavandi & Phillip Crothers & Celeste Gloria Esparza, 2016. "Target coverage in camera networks for manufacturing workplaces," Journal of Intelligent Manufacturing, Springer, vol. 27(6), pages 1221-1235, December.
    • Handle: RePEc:spr:joinma:v:27:y:2016:i:6:d:10.1007_s10845-014-0946-z
    DOI: 10.1007/s10845-014-0946-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-014-0946-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10845-014-0946-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. B Suman & P Kumar, 2006. "A survey of simulated annealing as a tool for single and multiobjective optimization," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(10), pages 1143-1160, October.
    2. Eglese, R. W., 1990. "Simulated annealing: A tool for operational research," European Journal of Operational Research, Elsevier, vol. 46(3), pages 271-281, June.
    3. Jing Ai & Alhussein A. Abouzeid, 2006. "Coverage by directional sensors in randomly deployed wireless sensor networks," Journal of Combinatorial Optimization, Springer, vol. 11(1), pages 21-41, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Thiago C. Jesus & Daniel G. Costa & Paulo Portugal & Francisco Vasques, 2022. "A Survey on Monitoring Quality Assessment for Wireless Visual Sensor Networks," Future Internet, MDPI, vol. 14(7), pages 1-26, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hachicha, Wafik & Ammeri, Ahmed & Masmoudi, Faouzi & Chachoub, Habib, 2010. "A comprehensive literature classification of simulation optimisation methods," MPRA Paper 27652, University Library of Munich, Germany.
    2. Özcan, Ugur, 2010. "Balancing stochastic two-sided assembly lines: A chance-constrained, piecewise-linear, mixed integer program and a simulated annealing algorithm," European Journal of Operational Research, Elsevier, vol. 205(1), pages 81-97, August.
    3. Hu, Qian & Lim, Andrew, 2014. "An iterative three-component heuristic for the team orienteering problem with time windows," European Journal of Operational Research, Elsevier, vol. 232(2), pages 276-286.
    4. Asma Khalil Alkhamis & Manar Hosny, 2023. "A Multi-Objective Simulated Annealing Local Search Algorithm in Memetic CENSGA: Application to Vaccination Allocation for Influenza," Sustainability, MDPI, vol. 15(21), pages 1-37, October.
    5. Meyr, H., 2000. "Simultaneous lotsizing and scheduling by combining local search with dual reoptimization," European Journal of Operational Research, Elsevier, vol. 120(2), pages 311-326, January.
    6. Ganesan, Viswanath Kumar & Sivakumar, Appa Iyer, 2006. "Scheduling in static jobshops for minimizing mean flowtime subject to minimum total deviation of job completion times," International Journal of Production Economics, Elsevier, vol. 103(2), pages 633-647, October.
    7. Felipe, Ángel & Ortuño, M. Teresa & Righini, Giovanni & Tirado, Gregorio, 2014. "A heuristic approach for the green vehicle routing problem with multiple technologies and partial recharges," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 111-128.
    8. Eva K. Lee & Siddhartha Maheshwary & Jacquelyn Mason & William Glisson, 2006. "Large-Scale Dispensing for Emergency Response to Bioterrorism and Infectious-Disease Outbreak," Interfaces, INFORMS, vol. 36(6), pages 591-607, December.
    9. M Kumral & P A Dowd, 2005. "A simulated annealing approach to mine production scheduling," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(8), pages 922-930, August.
    10. Adeinat, Hamza & Pazhani, Subramanian & Mendoza, Abraham & Ventura, Jose A., 2022. "Coordination of pricing and inventory replenishment decisions in a supply chain with multiple geographically dispersed retailers," International Journal of Production Economics, Elsevier, vol. 248(C).
    11. S.-C. Horng & S.-Y. Lin, 2009. "Ordinal Optimization of G/G/1/K Polling Systems with k-Limited Service Discipline," Journal of Optimization Theory and Applications, Springer, vol. 140(2), pages 213-231, February.
    12. Pavlos S. Georgilakis, 2020. "Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Researc," Energies, MDPI, vol. 13(1), pages 1-37, January.
    13. Regnier-Coudert, Olivier & McCall, John & Ayodele, Mayowa & Anderson, Steven, 2016. "Truck and trailer scheduling in a real world, dynamic and heterogeneous context," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 389-408.
    14. Panta Lučić & Dušan Teodorović, 2007. "Metaheuristics approach to the aircrew rostering problem," Annals of Operations Research, Springer, vol. 155(1), pages 311-338, November.
    15. Rossi, André & Singh, Alok & Sevaux, Marc, 2013. "Lifetime maximization in wireless directional sensor network," European Journal of Operational Research, Elsevier, vol. 231(1), pages 229-241.
    16. Angel Juan & Javier Faulin & Albert Ferrer & Helena Lourenço & Barry Barrios, 2013. "MIRHA: multi-start biased randomization of heuristics with adaptive local search for solving non-smooth routing problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(1), pages 109-132, April.
    17. Dimitrios Karpouzos & Konstantinos Katsifarakis, 2013. "A Set of New Benchmark Optimization Problems for Water Resources Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(9), pages 3333-3348, July.
    18. Ho, Sin C. & Leung, Janny M.Y., 2010. "Solving a manpower scheduling problem for airline catering using metaheuristics," European Journal of Operational Research, Elsevier, vol. 202(3), pages 903-921, May.
    19. Edmund Burke & Jingpeng Li & Rong Qu, 2012. "A Pareto-based search methodology for multi-objective nurse scheduling," Annals of Operations Research, Springer, vol. 196(1), pages 91-109, July.
    20. Nwana, V. & Darby-Dowman, K. & Mitra, G., 2005. "A co-operative parallel heuristic for mixed zero-one linear programming: Combining simulated annealing with branch and bound," European Journal of Operational Research, Elsevier, vol. 164(1), pages 12-23, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:joinma:v:27:y:2016:i:6:d:10.1007_s10845-014-0946-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.