Belief Function Based Algorithm for Material Detection and Tracking in Construction

Emmanuel Duflos 1, 2 Philippe Vanheeghe 1, 2 S.N. Razavi 3 Carl Haas 3
1 SEQUEL - Sequential Learning
LIFL - Laboratoire d'Informatique Fondamentale de Lille, LAGIS - Laboratoire d'Automatique, Génie Informatique et Signal, Inria Lille - Nord Europe
2 LAGIS-SI
LAGIS - Laboratoire d'Automatique, Génie Informatique et Signal
Abstract : Dislocation is defined as the change between discrete sequential locations of critical materials such as special valves or fabricated items, on a large construction project. Dislocations of construction materials on large sites represent critical state changes. Detecting these dislocations in a noisy information environment where low cost Radio Frequency Identification tags are attached to each piece of material, and the material is moved sometimes only a few meters, is the main focus of this study. We propose in this paper a method based on the Transferable Belief Model (TBM) to estimate materials locations and detect dislocations. This method has been implemented and real experiments were carried out. The results of these experiments show the ability of the proposed method to track the materials.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-00781434
Contributor : Philippe Vanheeghe <>
Submitted on : Saturday, January 26, 2013 - 5:44:12 PM
Last modification on : Thursday, February 21, 2019 - 10:52:49 AM

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Emmanuel Duflos, Philippe Vanheeghe, S.N. Razavi, Carl Haas. Belief Function Based Algorithm for Material Detection and Tracking in Construction. BELIEF 2010 : Workshop on the Theory of Belief Functions, Apr 2010, Brest, France. CDROM - 6 p. ⟨hal-00781434⟩

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