Reliable sensor location for object positioning and surveillance via trilateration. (November 2018)

• Record Type: Journal Article
• Authors: An, Kun; Xie, Siyang; Ouyang, Yanfeng
• Is Part Of: Transportation research. Volume 117(2018)Part B
• Page Start: 956
• Page End: 970
• Publication Date: 2018-11
• Subjects: Sensor location -- Disruption -- Trilateration -- Lagrangian relaxation; Transportation -- Research -- Periodicals; Transportation -- Mathematical models -- Periodicals
• DOI: 10.1016/j.trb.2017.11.012
• Languages: English
• ISSNs: 0191-2615

Abstract

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.