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Reliable sensor location for object positioning and surveillance via trilateration

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  • An, Kun
  • Xie, Siyang
  • Ouyang, Yanfeng

Abstract

Object positioning and surveillance has been playing an important role in various indoor location-aware applications. Signal attenuation or blockage often requires multiple local sensors to be used jointly to provide coverage and determine object locations via mobile devices. The deployment of sensors has a significant impact on the accuracy of positioning and effectiveness of surveillance. In this paper, we develop a reliable sensor location model that aims at optimizing the location of sensors so as to maximize the accuracy of object positioning/surveillance under the risk of possible sensor disruptions. We formulate the problem as a mixed-integer linear program and develop solution approaches based on a customized Lagrangian relaxation algorithm with an embedded approximation subroutine. A series of hypothetical examples and a real-world Wi-Fi access point design problem for Chicago O’Hare Airport Terminal 5 are used to demonstrate the applicability of the model and solution algorithms. Managerial insights are also presented.

Suggested Citation

  • An, Kun & Xie, Siyang & Ouyang, Yanfeng, 2018. "Reliable sensor location for object positioning and surveillance via trilateration," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 956-970.
    • Handle: RePEc:eee:transb:v:117:y:2018:i:pb:p:956-970
    DOI: 10.1016/j.trb.2017.11.012
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    References listed on IDEAS

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    Cited by:

    1. Yu, Xinyao & Ma, Shoufeng & Zhu, Ning & Lam, William H.K. & Fu, Hao, 2023. "Ensuring the robustness of link flow observation systems in sensor failure events," Transportation Research Part B: Methodological, Elsevier, vol. 178(C).
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    3. Xie, Siyang & An, Kun & Ouyang, Yanfeng, 2019. "Planning facility location under generally correlated facility disruptions: Use of supporting stations and quasi-probabilities," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 115-139.
    4. Shahriar Mohammadi & Karim Ismail & Amir H. Ghods, 2021. "Investigating Wi-Fi, Bluetooth, and Bluetooth Low-Energy Signal Characteristics for Integration in Vehicle–Pedestrian Collision Warning Systems," Sustainability, MDPI, vol. 13(19), pages 1-20, September.
    5. Zhang, Yanzi & Diabat, Ali & Zhang, Zhi-Hai, 2021. "Reliable closed-loop supply chain design problem under facility-type-dependent probabilistic disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 146(C), pages 180-209.
    6. Wang, Zhaodong & Xie, Siyang & Ouyang, Yanfeng, 2022. "Planning reliable service facility location against disruption risks and last-mile congestion in a continuous space," Transportation Research Part B: Methodological, Elsevier, vol. 165(C), pages 123-140.

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