IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v167y2015icp119-127.html
   My bibliography  Save this article

Investigating of antenna selection for the adaptive centroid localization systems

Author

Listed:
  • Yuangyai, Chumpol
  • Pan, Chung-Yu
  • Lin, Yi-Jou
  • Cheng, Chen-Yang

Abstract

Location-based services are widely integrated in our daily lives, and they are used in various ways such as for investigating inventory goods and personal tracking in healthcare. With increasing applications of wireless localization, accuracy of location estimation requirements has become more critical. However, indoor localization suffers from multi-path interference that affects the traditional algorithmic calculation methods based on radio signal strength. The strength of radio signal depends significantly on antenna types and the deployment of wireless sensor network. Therefore, the aim of this paper is to investigate a robust deployment of wireless sensor network considering antennas and optimal signal range to increase signal strength and to reduce receiving signal missing. A bi-response design approach was taken to evaluate antenna selection, signal range, and antenna power rate. The experiment result was applied with existing algorithm to prove effectives. Further, to avoid wireless sensors collision which may result in low accuracy of receiving radio signal, adaptive weight center of gravity localization (AWCG) were proposed. AWCG is based on an assumption of the dynamic relationship between the radio signal strength and the distance in different environments at different times. In the proposed localization algorithm, the error distance was approximately one meter. It is expected to significantly improve the location estimation accuracy with the suggested deployment and proposed algorithm.

Suggested Citation

  • Yuangyai, Chumpol & Pan, Chung-Yu & Lin, Yi-Jou & Cheng, Chen-Yang, 2015. "Investigating of antenna selection for the adaptive centroid localization systems," International Journal of Production Economics, Elsevier, vol. 167(C), pages 119-127.
    • Handle: RePEc:eee:proeco:v:167:y:2015:i:c:p:119-127
    DOI: 10.1016/j.ijpe.2015.05.017
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527315001693
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijpe.2015.05.017?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. Kim, Jindae & Tang, Kaizhi & Kumara, Soundar & Yee, Shang-Tae & Tew, Jeffrey, 2008. "Value analysis of location-enabled radio-frequency identification information on delivery chain performance," International Journal of Production Economics, Elsevier, vol. 112(1), pages 403-415, March.
    2. Muyanja, Andrew W. & Atichat, Tanawat & Porter, J. David, 2013. "An experimental study on the effect of pattern recognition parameters on the accuracy of wireless-based task time estimation," International Journal of Production Economics, Elsevier, vol. 144(2), pages 533-545.
    Full references (including those not matched with items on IDEAS)

    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. Viet, Nguyen Quoc & Behdani, Behzad & Bloemhof, Jacqueline, 2018. "Value of Information to Improve Daily Operations in High-Density Logistics," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 9(1), January.
    2. Mona Haji & Laoucine Kerbache & Mahaboob Muhammad & Tareq Al-Ansari, 2020. "Roles of Technology in Improving Perishable Food Supply Chains," Logistics, MDPI, vol. 4(4), pages 1-24, December.
    3. Nilgun Fescioglu-Unver & Sung Hee Choi & Dongmok Sheen & Soundar Kumara, 2015. "RFID in production and service systems: Technology, applications and issues," Information Systems Frontiers, Springer, vol. 17(6), pages 1369-1380, December.
    4. Masoud Zafarzadeh & Magnus Wiktorsson & Jannicke Baalsrud Hauge, 2021. "A Systematic Review on Technologies for Data-Driven Production Logistics: Their Role from a Holistic and Value Creation Perspective," Logistics, MDPI, vol. 5(2), pages 1-32, April.
    5. Zhang, Yingfeng & Zhang, Geng & Du, Wei & Wang, Junqiang & Ali, Ebad & Sun, Shudong, 2015. "An optimization method for shopfloor material handling based on real-time and multi-source manufacturing data," International Journal of Production Economics, Elsevier, vol. 165(C), pages 282-292.
    6. Kim, Jindae & Ok, Chang-Soo & Kumara, Soundar & Yee, Shang-Tae, 2010. "A market-based approach for dynamic vehicle deployment planning using radio frequency identification (RFID) information," International Journal of Production Economics, Elsevier, vol. 128(1), pages 235-247, November.
    7. T. Saikouk & I. Zouaghi & A. Spalanzani, 2011. "Mitigating Supply Chain System Entropy by the Implementation of RFID," Post-Print halshs-00665653, HAL.
    8. Sarac, Aysegul & Absi, Nabil & Dauzère-Pérès, Stéphane, 2010. "A literature review on the impact of RFID technologies on supply chain management," International Journal of Production Economics, Elsevier, vol. 128(1), pages 77-95, November.
    9. Kelepouris, Thomas & McFarlane, Duncan, 2010. "Determining the value of asset location information systems in a manufacturing environment," International Journal of Production Economics, Elsevier, vol. 126(2), pages 324-334, August.
    10. Ferrer, Geraldo & Dew, Nicholas & Apte, Uday, 2010. "When is RFID right for your service?," International Journal of Production Economics, Elsevier, vol. 124(2), pages 414-425, April.
    11. Garrido-Vega, Pedro & Ortega Jimenez, Cesar H. & de los Ríos, José Luis Díez Pérez & Morita, Michiya, 2015. "Implementation of technology and production strategy practices: Relationship levels in different industries," International Journal of Production Economics, Elsevier, vol. 161(C), pages 201-216.
    12. Toni Greif & Nikolai Stein & Christoph M. Flath, 2023. "Information Value Analysis for Real-Time Silo Fill-Level Monitoring," Interfaces, INFORMS, vol. 53(4), pages 283-294, 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:eee:proeco:v:167:y:2015:i:c:p:119-127. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    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.