Antonio Adan

Dr. Antonio Adan

Castilla La Mancha University
orcid

Research Focus & Metrics

Academic Career Length

30Years (1997-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 May 2013 in Automation in Construction
Verified
Journal Article
Closed access
XXXuehan Xiong
Xuehan Xiong
Antonio AdanAntonio Adan
Antonio Adan
BABurcu Akinci
Burcu Akinci
DHDaniel Huber
Daniel Huber

3 July 2015 in Sensors
Verified
Journal Article
Open access
PDF file
EVEnrique Valero
Enrique Valero
Antonio AdanAntonio Adan
Antonio Adan
CCCarlos Cerrada
Carlos Cerrada
Radio frequency identification (RFID) technology has been widely used in the field of construction during the last two decades. Basically, RFID facilitates the control on a wide variety of processes in different stages of the lifecycle of a building, from its conception to its inhabitance. The main objective of this paper is to present a review of RFID applications in the construction industry, pointing out the existing developments, limitations and gaps. The paper presents the establishment of the RFID technology in four main stages of the lifecycle of a facility: planning and design, construction and commission and operation and maintenance. Concerning this last stage, an RFID application aiming to facilitate the identification of pieces of furniture in scanned inhabited environments is presented. Conclusions and future advances are presented at the end of the paper.

1 May 2011
Verified
Conference Paper
Closed access
Antonio AdanAntonio Adan
Antonio Adan
DHDaniel Huber
Daniel Huber
Laser scanners are often used to create 3D models of buildings for civil engineering applications. The current manual process is time-consuming and error-prone. This paper presents a method for using laser scanner data to model predominantly planar surfaces, such as walls, floors, and ceilings, despite the presence of significant amounts of clutter and occlusion, which occur frequently in natural indoor environments. Our goal is to recover the surface shape, detect and model any openings, and fill in the occluded regions. Our method identifies candidate surfaces for modeling, labels occluded surface regions, detects openings in each surface using supervised learning, and reconstructs the surface in the occluded regions. We evaluate the method on a large, highly cluttered data set of a building consisting of forty separate rooms.

1 August 2018 in Advanced Engineering Informatics
Verified
Journal Article
Closed access
Antonio AdanAntonio Adan
Antonio Adan
BQBlanca Quintana
Blanca Quintana
SPSamuel A. Prieto
Samuel A. Prieto
FBFrédéric Bosché
Frédéric Bosché

1 December 2016 in Measurement
Verified
Journal Article
Closed access
EVEnrique Valero
Enrique Valero
Antonio AdanAntonio Adan
Antonio Adan

1 January 2018 in Automation in Construction
Verified
Journal Article
Closed access
BQBlanca Quintana
Blanca Quintana
SPSamuel A. Prieto
Samuel A. Prieto
Antonio AdanAntonio Adan
Antonio Adan
FBFrédéric Bosché
Frédéric Bosché