ICCBEI 2019
4th International Conferenceon Civil and Building Engineering Informatics
November 7-8, 2019, Sendai, Japan

Program and Book of Abstracts

ICCBEI 2019
4th International Conference on Civil and Building Engineering Informatics

Organizers
Asian Group for Civil Engineering Informatics (AGCEI)
Committee on Civil Engineering Informatics,
Japan Society of Civil Engineers (JSCE)

Supporters
Japan Construction Information Center
Miyagi University

Sponsors
Gold Sponsors:
Forum 8 Co., Ltd.
Kajima Corporation
Applied Technology Co., Ltd. and Autodesk Inc.
Sendai Tourism, Convention
and International Association (SenTIA)

Silver Sponsors:
Chodai Co.,Ltd
Chuo Fukken Consultants Co.,Ltd.
JIP Techno Science Corporation
Shimizu Corporation
Trion Corporation
Obayashi Corporation
Yachiyo Engineering Co.Ltd

COPYRIGHT NOTICE: Copyright © 2019 by the authors of the individual abstracts.
All abstracts are distributed under the Creative Commons Attribution-NonCommercialNoDerivatives 4.0 International License (CC-BY-NC-ND 4.0).

Program and Book of Abstracts, ICCBEI 2019

GREETINGS FROM THE CHAIR OF ICCBEI 2019
We are very pleased to hold the International Conference on Civil and Building
Engineering Informatics (ICCBEI 2019) in Sendai City, Miyagi Prefecture, Japan. The
organizer of ICCBEI, Asian Group for Civil and Building Informatics (AGCEI), wasdevelopmentally organized from the series of Asian Construction Information Technology
Roundtable Meeting sponsored by Japan Society of Civil Engineers (JSCE) and Japan
Construction Information Center (JACIC). AGCEI is the sister organization of the International
Society for Computing on Civil and Building Engineering (ISCCBE), which holds theInternational Conference on Computing in Civil and Building Engineering (ICCCBE) in theeven number years. AGCEI decided to hold the international conference in the Asian andPacific region in the odd number year and held the conference in Tokyo in 2013, then Tokyoin 2015, and Taipei in 2017. ICCBEI 2019 is the fourth conference, which is the first conference
outside of Tokyo in Japan.
In a decade, information and communication technologies (ICT) have advanced
continuously and more rapidly. Various new technologies such as 3D scanning using drones,
computer vision, IoT sensors and actuators, robot and machinery control, and so on have beendeveloped and applied to civil and building engineering. Also, artificial intelligence (AI) has
been able to analyze big data generated by accumulating a large amount of information andreplace human knowledge and cognition. Furthermore, the information or data-centric concept
has evolved, and the information and data are becoming a core in linking for Cyber-Physical
Systems. In every phase in the lifecycles of building and infrastructure, building information
modeling(BIM) is becoming increasingly important as the core for storing information. In thistrend, “informatics” in the title of the conference is becoming a key academic area in civil andbuilding engineering, and we should make further progress.
In response to our Call for Papers, 78 abstracts were submitted, and our international
scientific committee has finally accepted 62 full papers after rigorous reviews. These accepted
papers will be presented at the conference. The papers can be categorized into nine academic
categories without industrial/ technical category: Building and Construction Information
Modeling, AI and Data Analysis, Image Processing and Computer Vision, Visualization and
XR(VR/AR/MR), IoT/Sensors and Monitoring, Laser and Image Scanning, Facility andInfrastructure Management, Computational Mechanics/Engineering, and Information andProcess Management. As these categories show, the papers target innovative topics in civil andbuilding informatics. We hope that ICCBEI 2019 and the publication of the proceeding willcontribute to the development and dissemination of Civil and Building Engineering long into
the future. We also invite three key persons in Civil and Building Engineering as keynote
speakers. We hope that the discussion in ICCBEI 2019 will contribute to the development anddissemination of Civil and Building Engineering long into the future.
Furthermore, the Sendai area where ICCBEI 2019 will be held was affected by thedisaster of the large earthquake in 2011. Especially, the coastal area was heavily hit by Tsunami,
and some cities were flown out. Many reconstruction projects in the coastal area are underway,
and many applications of ICT are tried. We hope that our discussions at this conference will be
useful for the reconstruction of disaster areas.
Finally, we hope that you enjoy the conference.
Koji Makanae
Chair, Organizing Committee of ICCBEI 2019
Chair, Committee on Civil Engineering Informatics,
Japan Society of Civil Engineers (JSCE)
Professor, Miyagi University, Japan1

Program and Book of Abstracts, ICCBEI 2019

ICCBEI 2019 TIME SCHEDULE[Day 0] Pre-event and Reception
13:00-16:40
17:30-19:30

November 6 (Wed)[Pre-event] JACIC Session (Japanese Program) *pre-entry required(Studio Theater on 7th Floor)
Reception at Crepuscule Cafe on Ground Floor in Sendai Mediatheque[Day 1] ICCBEI 20199:009:30-9:45
9:45-10:30

November 7 (Thu)

Reception *Entrance of Sendai Mediatheque will be open at 9:00
Opening Ceremony (Open Square on Ground Floor, Sendai Mediatheque)Keynote Lecture-1 (Open Square on Ground Floor, Sendai Mediatheque)Prof. Kincho H. Law (Stanford University)"Information and Communication Technologies (ICT) in Civil and Building Engineering"

10:30-10:45

Coffee Break (Coffee Space in Open Square on Ground Floor)
Session A (Studio Theater on 7th Floor)

10:45-12:00
12:00-13:00
13:00-13:40

Session B (Meeting Room A/B on 7th Floor)

[AI1]
[XR]
AI and Data Analysis-1
Visualization and XR(VR/AR/MR)
Lunch (1F Coffee Space in Open Square on Ground Floor)
Keynote Lecture-2 (Open Square on Ground Floor, Sendai Mediatheque)Prof. Katharina Klemt-Albert"Digitalization in AEC – German perspectives from strategy to implementation"

13:40-15:05

15:05-15:20
15:20-16:35
16:40
16:4518:00-20:00
20:00

Session A (Studio Theater on 7th Floor)

Session B (Meeting Room A/B on 7th Floor)[AI2]
AI and Data Analysis-2[FM]
Facility and Infrastructure Management

Coffee Break (Coffee Space in Open Square on Ground Floor)[CV]
Image Processing and Computer Vision[IS]
Industrial/Technical Session

Meet at OpenSquare for DinnerBus for Dinner Departure at Sendai Mediatheque (15 minutes trip)
Dinner at Sendai Castle Ruins “Honmaru Kaikan”
Bus Departure at Sendai Castle (back to Sendai Mediatheque and Sendai Station)2

Program and Book of Abstracts, ICCBEI 2019[Day 2] ICCBEI 20199:009:20-10:20

10:20-10:35
10:35-11:50

11:50-13:00
13:00-13:45

November 8 (FRI)

Reception *Entrance of Sendai Mediatheque will open at 9:00
Session A (Studio Theater on 7th Floor)

Session B (Meeting Room A/B on 7th Floor)[BM1]
Building and Construction Information
Modeling(BIM/CIM)-1[CME]
Computational Mechanics/Engineering

Coffee Break (Coffee Space in Open Square on Ground Floor)

[BM2]
[IOT]
Building and Construction
IoT, Sensors, and Monitoring
Information Modeling(BIM/CIM)-2
Lunch (1F Coffee Space in Open Square on Ground Floor)
Keynote Lecture-3(Open Square on Ground Floor, Sendai Mediatheque)Dr. Jack C.P. Cheng"Creation, Integration and Management of BIM Information"

13:45-14:00
14:00-15:00

15:00-15:15
15:15-16:15

Coffee Break (Coffee Space in Open Square on Ground Floor)
Session A (Studio Theater on 7th Floor)

Session B (Meeting Room A/B on 7th Floor)[BM3]
Building and Construction
Information Modeling(BIM/CIM)-3[LIS]
Laser and Image Scanning

Coffee Break (Coffee Space in Open Square on Ground Floor)[BM4]
Building and Construction Information
Modeling(BIM/CIM)-4

16:15-16:30
16:30-16:45[IPM]
Information and Process Management

Break

Closing Ceremony
Best papers and Best Presentation Awards, Closing, Group Photo[Day 3] Excursion
8:50
9:00-16:40*pre-entry required

November 9 (SAT)

Meet at Sendai Station East Exit, Chartered Bus Stop
Tour to the Matushima Islands and the Tsunami Affected Area
Shiogama Shrine, Saura Sake Brewery, Lunch, Zuiganji Temple, Entsu-in Temple,
and “Sendai Arahama Elementary School” in Tsunami Affected Area

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Program and Book of Abstracts, ICCBEI 2019

KEYNOTE LECTURE-1

Information and Communication Technologies (ICT)in Civil And Building Engineering
Prof. Kincho H. Law
Professor, Civil and Environmental Engineering, Stanford University, USA. Email: law@stanford.edu
Abstract: Civil and Building Engineering has had a long and successful history in adopting computing
technologies, from computer graphics, CAD, engineering analyses, virtual simulations, to project management.
As technologies continue to advance, there are many new opportunities that can take advantage of information
science and computing technologies in engineering. Technologies such as building information modeling, virtual
reality, computer vision, sensors, Internet and cloud computing, etc., are now being deployed in civil andconstruction engineering. This presentation will provide an overview of current trends of computing technologies
in the AEC domain. Specifically, the discussions will focus on technologies related to building information
modeling and enterprise integration, and the applications of Internet of Things (IoT) and machine learning in thecivil and building industry.

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Program and Book of Abstracts, ICCBEI 2019

Profile of Prof. Kincho H. Law
Dr. Kincho H. Law is Professor of Civil and Environmental Engineering at Stanford University. He received his
B.Sc. in Civil Engineering and B.A. in Mathematics from the University of Hawaii in 1976, and M.S. and Ph.D.
in Civil Engineering from Carnegie Mellon University in 1979 and 1981, respectively. After serving as AssistantProfessor at Rensselaer Polytechnic Institute from 1982 to 1988, he joined Stanford University in 1988. Prof.
Law’s research interests focus on computational and information science in engineering. His research has dealt
with various aspects of high performance computing; sensing, monitoring and control of engineering systems;
legal and engineering informatics; smart manufacturing; web services, cloud and Internet computing.
Prof. Law was the recipient of the ASCE Computing in Civil Engineering Award in 2011. He has received anumber of best paper awards from ASCE, ASME, IEEE and Digital Government Society; these include Best Paper(on Data Analytics for Advanced Manufacturing) at IEEE Big Data Conference in 2016, Best Paper at the ASME
Manufacturing Science and Engineering Conference in 2015, Best Paper in the ASCE Journal of Computing in
Civil Engineering in 2014, Best Research Paper (on Resilience and Smart Structures) at the International
Workshop on Computing in Civil Engineering in 2013, Best Research and Practice Paper at 6th International
Conference on Electronic Governance in 2012, Meritorious Paper at the 4th International Conference on Electronic
Governance in 2010, Best Research Paper at the 9th International Conference on Digital Government Research in
2008, and others. Prof. Law was elected Distinguished Member of the American Society of Civil Engineers in
2017, Fellow of the American Society of Mechanical Engineers in 2017, Life Member of the American Society of
Civil Engineers in 2018, and Senior Member of the Institute of Electrical and Electronics Engineers in 2019.

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Program and Book of Abstracts, ICCBEI 2019

KEYNOTE LECTURE-2

Digitalization in AEC– German perspectives from strategy to implementation
Prof. Katharina Klemt-Albert
Professor for Construction Management und Digital Engineering, Leibniz Universität Hannover, Germany. Email:klemt-albert@icom.uni-hannover.de
Abstract: Germany has recognized the potential of the BIM method and is proceeding to develop necessary
guidelines and framework conditions at national level as well as implementation acts. This process is driven by
the Federal Ministry of Transport and Digital Infrastructure (BMVI) and the Federal Ministry of the Interior,
Building and Home Affairs (BMI). In 2015, BMVI published the phased plan Digital Planning and Building as a
strategy for the introduction of BIM for federal traffic infrastructure. The plan describes the step-wise path to thegradual introduction of BIM in the area of responsibility of the BMVI. Selected transport infrastructure projectsof the road, rail and waterways are currently carried out as pilot projects. Federal institutions are pursuing an open
exchange of data (OpenBIM). An examination of the application of BIM in building construction projects of theFederal Government with an estimated investment volume of EUR 5 million or higher is demanded by BMI.
Starting in 2020, both ministries will run the national BIM competence center in order to coordinate the BIM
implementation as well as to act as a service hub of BIM-related knowledge and technology transfer.
In addition, guidelines and instructions for applying the BIM methodology are developed and issued by major
German private and public companies. They include BIM execution plans (BEP) and employer’s information
requirements (EIR) as well as legal designs (contract) and tender procedures. Noteworthy here is, for example,
Deutsche Bahn as a major public contractor in the infrastructure sector, which has developed specifications for theapplication of the BIM method for railway projects. The federal project company in the field of road infrastructure,
DEGES, has published guidelines and templates for road construction. Other private companies have proceeded
in a similar manner. These guidelines include specifications for framework conditions, such as processes, roles
and project standards, as well as BIM use cases, such as specifications for collaboration and information
requirements (including platform concepts and integrated communication tools). Specific and crucial roles bothon employer’s and contractor’s side (e.g. BIM manager and BIM coordinator) are defined to guarantee satisfying
project execution due to BIM use.
All sectors require a solid, consistent and state-of-the-art training and education of engineers and specialists. Thisis executed both in the public and the private sector. Legal entities both on national and state level can and mustbe partner of (regional) economies in order to support especially SMEs in the change process. The Institute ofConstruction Management and Digital Engineering (ICoM) is a leading German educator not only on theuniversity level, but also transferring knowledge to working professionals from beginner to expert levels via useof new methodical approaches as well as their digital laboratories (X-Lab). Innovative methods of education (e.g.
blended learning and virtual reality) find their way into the educational programs. Post-educational, certified
courses for professionals and specialists round off academic qualification.

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Program and Book of Abstracts, ICCBEI 2019

Profile of Prof. Katharina Klemt-Albert
Prof. Dr.-Ing. Katharina Klemt-Albert leads the Institute for Construction Management and Digital Engineering
at Leibniz University Hanover since 2016. Her focus in research and teaching is on digital transformation anddigitalization of the building and construction industry. She started her academic career studying civilengineering at Ruhr University Bochum. In 2001 she received her doctorate with distinction from Technical
University of Darmstadt in cooperation with Northwestern University/USA. Professor Klemt-Albert is anexperienced leader and manager of mega projects in Germany and worldwide. For 14 years, she held positions ofhigh responsibility at Deutsche Bahn AG, most recently as Member of the Board of an international engineering
company with 1,500 employees. Her personal interest has always been the development and implementation oftechnical innovations. Her work focuses on the integration of science and practice. Major research topics at her
institute are GreenBIM, Digital Methodologies in AEC, Digital Construction and Major Projects. Professor
Klemt-Albert is honored as one of Germany‘s Top 25 most influential women in engineering. She won the prize
for excellence in teaching of Leibniz Universität Hannover. She initiated several BIM networks such as the BIM
Cluster Lower Saxony, a statewide association of government, industry and academia. Furthermore, Professor
Klemt-Albert is founder and CEO of albert.ing GmbH, which offers engineering services and consulting indigital construction.

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Program and Book of Abstracts, ICCBEI 2019

KEYNOTE LECTURE-3

Creation, Integration and Management of BIM Information
Dr. Jack C. P. Cheng
Associate Professor, Department of Civil and Environmental Engineering, The Hong Kong University of Scienceand Technology, Hong Kong. E-mail: cejcheng@ust.hk
Abstract: Building information modeling (BIM) technology is increasingly used in various architecture,engineering, construction and operations applications. BIM is even compulsory for public projects in somecountries and regions like UK and Hong Kong. This leads to the opportunities yet challenges to the availability,
representation, use and management of building information models. In this presentation, the generation andrepresentation of building information models will be discussed firstly. In specific, model requirement definition
and advanced approaches based on machine learning and AI to automatically generate building information models
from point cloud data will be presented. Secondly, examples and lesson learnt of integrating BIM information withother technologies such as GIS, Internet of Things and robotics will be presented. Thirdly, this presentation will
discuss the storage, sharing and management of building information models and associated information in a multiuser, collaborative environment. Potential opportunities and challenges of relevant technologies and infrastructures
such as blockchain and common data environment will be discussed.

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Program and Book of Abstracts, ICCBEI 2019

Profile of Dr. Jack C. P. Cheng
Dr. Jack Cheng is an Associate Professor of Civil and Environmental Engineering, Director of the RFID
Center, and Associate Director of the GREAT Smart Cities Institute at the Hong Kong University of Scienceand Technology (HKUST). He obtained his PhD degree from Stanford University. His research interests
include BIM, Internet of Things (IoT), computer vision and deep learning, construction informatics,
construction and facility management, green and low carbon buildings, and sustainable construction. He iscurrently the Chair of the Hong Kong Construction Industry Council (CIC) BIM Standards (Phase 2) Task
Force, Chair of ASCE Global Center for Excellence in Computing, Chairman of Autodesk Industry Advisory
Board (AIAB), President-Elect of ASCE Hong Kong Section, and Honorary Treasurer of Hong Kong
Institution of Building Information Modeling (HKIBIM). He is a Professional Member of HKIBIM, CIC
Certified BIM Manager, and Certified Carbon Auditor Professional (CAP). He has received the Construction
Industry Outstanding Young Person Award in 2019 and the Young BIMer of the Year Award in 2014 fromthe CIC. He has co-authored over 200 referred journal and conference publications.

9Program and Book of Abstracts, ICCBEI 2019

PARALLEL SESSIONS[Day 1] 10:45-12:00
Session A (Studio Theater on 7th Floor):[AI1] AI and Data Analysis-1

Chair: Prof. Kei Kawamura (Yamaguchi University)[AI1-1] NLP-based Method for Auto-Correcting Public Constructions Data

Meng-Lin Yu (National Taiwan University of Science and Technology), Hao-Yung Chan (National
Taiwan University of Science and Technology), Meng-Han Tsai (National Taiwan University of
Science and Technology)[AI1-2] Analysis of Power Usage and Building Residents Relationships for Energy
Savings Using Social Network Analysis

Ru-Guan Wang (National Central University), Chien-Cheng Chou (National Central University)[AI1-3] As-built Detection of Steel Frame Structure Using Deep Learning

Ryu Izutsu (Osaka University), Nobuyoshi Yabuki (Osaka University), Tomohiro Fukuda (Osaka
University)[AI1-4] Video-based Construction Vehicles Type Recognition

Chen-Hsuan Wang (National Taiwan University of Science and Technology), I-Tung Yang
(National Taiwan University of Science and Technology), Meng-Han Tsai (National Taiwan
University of Science and Technology)[AI1-5] GA-based Optimization for Construction Sequence of Precast and Cast-in-place
Concrete Components
Songyang Li (Tsinghua University), Zhiliang Ma (Tsinghua University)

Session B (Meeting Room A/B on 7th Floor):[XR] Visualization and XR(VR/AR/MR)

Chair: Prof. Amir Behzadan (Texas A&M University)[XR-1] Efficient Access to Inspection Data Based on Augmented Reality Using a“BRIDGE - CARD”

Hisao Emoto (KOSEN), Hiroki Komuro (KOSEN), Takehiko Midorikawa (KOSEN), Hideaki
Nakamura (Yamaguchi University), Kei Kawamura(Yamaguchi University)[XR-2] Bidirectional Linking Of 4D-BIM Planning with Virtual and Augmented Reality
Felix Dreischerf (University of Applied Science Erfurt), Habeb Astour (University of Applied
Science Erfurt)[XR-3] Verification About Work Efficiency Improvement by Using an Augmented Reality
and Wearable Computer
Satoshi Yamanaka (Obayashi Corporation), Shinya Sugiura (Obayashi Corporation), Ryo Tajima(Obayashi Corporation), Takafumi Yamanaka (Obayashi Corporation)[XR-4] Visualization of Construction Process by Construction Site Sensing and Digital
Twins
Atsushi Takao (Okumura Corporation), Nobuyoshi Yabuki (Osaka University), Kohei Seto
(Okumura Corporation), Iwao Miyata (Okumura Corporation)[XR-5] AR Visualization of Physical Barrier for Wheelchair Users Using Depth Imaging
Rio Takahashi (Kansai University), Hiroshige Dan (Kansai University), Yoshihiro Yasumuro(Kansai University)

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Program and Book of Abstracts, ICCBEI 2019[Day 1] 13:50-15:05
Session A (Studio Theater on 7th Floor):[AI2] AI and Data Analysis-2

Chair: Prof. Nobuyoshi Yabuki (Osaka University)[AI2-1] Basic Study on Detecting Breaking Sounds of Structural Members by Using
Machine Learning

Takeo Izumita (Tokyo University of Science), Masayuki Saeki (Tokyo University of Science)[AI2-2] Computer Vision-based In-building Human Demand Estimation for Installationof Automated External Defibrillators
Wen-Xin Qiu (National Taiwan University), Albert Y. Chen (National Taiwan University)[AI2-3] Multi-Dimensional Sequence Alignment for Context-Aware Human Action
Analysis of Body-Sensor Data

Nipun Nath (Texas A&M University), Amir Behzadan (Texas A&M University), Prabhat Shrestha(Texas A&M University)[AI2-4] Application of Intelligent Systems in the Underground Excavation Industry: A
Short Review
Mohsen Ramezanshirazi (Sapienza University of Rome), Mohammad Norizadeh Cherloo(University of science and technology), Orod Zarrin[AI2-5] Determination of Automated Construction Operations from Sensor Data Using
Machine Learning
Aparna Harichandran (Curtin University), Benny Raphael (Indian Institute of Technology
Madras), Abhijit Mukherjee (Curtin University)

Session B (Meeting Room A/B on 7th Floor):[FM] Facility and Infrastructure Management

Chair: Dr. Veerasak Likhitruangsilp (Chulalongkorn University)[FM-1] Steel Bridge Information Delivery Model for Earned Value Management (EVM)
Teruaki Kageyama (Japan Construction Information Center), Nobuyoshi Yabuki (Osaka
University)[FM-2] A Proposal of Deterioration Prediction Model for Tunnel Lighting Facilities Using
Markov Stochastic Process
Noriaki Maeda (Yamaguchi University), Kei Kawamura (Yamaguchi University)[FM-3] VRP-based Model for Lane Marking Assessment with MRU Vehicle

Yu-Chun Lin (National Taiwan University), Si-Ting Liao (National Taiwan University), Chieh
Wang (National Taiwan University), Albert Y. Chen (National Taiwan University)[FM-4] The Gateway to Integrating User Behavior Data in “Cognitive Facility
Management”

Jinying Xu (The University of Hong Kong), Weisheng Lu (The University of Hong Kong), Jing
Wang (The University of Hong Kong)

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Program and Book of Abstracts, ICCBEI 2019[Day 1] 15:20-16:35
Session A (Studio Theater on 7th Floor):[CV] Image Processing and Computer Vision
Chair: Dr. Lei Hou (RMIT University)[CV-1] Study on Automatic Chalk Marks Recognition for Concrete Tunnel Inspection
Using Deep Learning

Yao Zhang (Yamaguchi University), Kei Kawamura (Yamaguchi University), Cuong Nguyen Kim(Mientrung University of Civil Engineering), Koji Oshikiri (Ricoh Company, Ltd.), Taro Kikuchi(Ricoh Company, Ltd.)[CV-2] GA-CNN Based Automatic Crack Detection and Classification Method forConcrete Infrastructures

Cuong Nguyen Kim (Mientrung University of Civil Engineering), Kei Kawamura (Yamaguchi
University), Yao Zhang (Yamaguchi University)[CV-3] As-built Modeling of Steel Structures Using Symmetry

Takuya Suzuki (Nihon University), Tomohiro Mizoguchi (Nihon University)[CV-4] A Review of Research on Advanced Autonomous Technologies for Bridge
Inspection

Rina Hasuike (Gifu University), Koji Kinoshita (Gifu University), Lei Hou (RMIT University)[CV-5] A Performance Evaluation of Feature Detectors and Descriptors for Unmodified
Infrastructure Site Digital Images

Natthapol Saovana (Osaka University), Nobuyoshi Yabuki (Osaka University), Tomohiro Fukuda(Osaka University)

Session B (Meeting Room A/B on 7th Floor):[IS] Industrial/Technical Session

Chair: Prof. Teppei Ishiuchi (Miyagi University)[IS-1] Collection Data Using New Tool to Satisfy Specifications
Yasushi Kawanai (Japan Construction Information Center)[IS-2] Educational Activity Aimed at Improving Productivity in Japanese Construction
Industries Through 3D-CAD
Yasuyuki Kikyo (Japan Construction Information Center)[IS-3] Improvement of Electronic Bidding Core System
Hiroyuki Ishiwata (Japan Construction Information Center)[IS-4] Integration of 3D Models of Structures and Geological Composition as an
Underground Infrastructure Model

Toshiaki Hakoda (JGC Corporation), Syoichi Nishiyama (OYO Corporation), Takaki Omori(Nikken Sekkei Civil Engineering Ltd.), Isao Shiozaki (Engineering Advancement Association ofJapan), Mamoru Narusawa (ESCA-SC), Nobuyuki Yabuki (Osaka University)

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Program and Book of Abstracts, ICCBEI 2019[Day 2] 9:20-10:20
Session A (Studio Theater on 7th Floor):[BM1] Building and Construction Information Modeling(BIM/CIM)-1
Chair: Prof. Zhiliang Ma (Tsinghua University)[BM1-1] Research on BIM Based Infrastructure Platforms with International Standards
Katsunori Miyamoto (Japan Construction Information Center)[BM1-2] A BIM-based AR Application for Construction Quality Inspection
Nai-Wen Chi (National Taiwan University of Science and Technology), Yi-Wen Chen
(Moldex3D Co., Ltd.), Shang-Hsien Hsieh (National Taiwan University), Jen-Yu Han(National Taiwan University), Lung-Mao Huang (Reiju Construction Co., Ltd.)[BM1-3] Application of BIM Technology on Virtual Mock-up and Implementation for
General Contractor in Construction
Rodrigo Samuel Ortiz Chaparro (National Taipei University of Technology), Yu-Cheng Lin(National Taipei University of Technology)[BM1-4] Deep Learning-based Scan-to-BIM Framework for Complex MEP Scenes Using
Laser Scan Data
Chao Yin (The Hong Kong University of Science and Technology), Boyu Wang (The Hong
Kong University of Science and Technology), Jack C.P. Cheng (The Hong Kong University of
Science and Technology)

Session B (Meeting Room A/B on 7th Floor):[CME] Computational Mechanics/Engineering

Chair: Prof. Masayuki Saeki (Tokyo University of Science)[CME-1] Evaluation of Pile Performance in Different Layers of Soil Investigating Pile
Behavior by OpenSeesPL
Orod Zarrin (The University of Newcastle), Mohsen Ramezanshirazi (Sapienza University of
Rome)[CME-2] Development of Static and Dynamic Modeling Approaches Using Frame
Models for City Seismic Response Analysis

Pher Errol B. Quinay (University of the Philippines Diliman), Aileen Rachelle Fader (WallcreteCompany, Inc.), Franz Marius Carangan (Al Abbar Aluminum Philippines, Inc.)[CME-3] Structural Shape Grammars Used in Intelligent Generation Design of Discrete
Structures
Xianzhong Zhao (Tongji University), Ruifeng Luo (Tongji University)[CME-4] Numerical Evaluation of Seismic Response of Anchorage Foundation Installed
in Switchboard Cabinet
Sang-Moon Lee (Gangneung-Wonju University), Woo-Young Jung (Gangneung-Wonju
University), Ga-Ram Kim (Gangneung-Wonju University)

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Program and Book of Abstracts, ICCBEI 2019[Day 2] 10:35-11:50
Session A (Studio Theater on 7th Floor):[BM2] Building and Construction Information Modeling(BIM/CIM)-2
Chair: Prof. Brian Guo (University of Canterbury)[BM2-1] Conversation-based Building Information Delivery System for Facility
Management

Kuan-Lin Chen (National Taiwan University of Science and Technology), Meng-Han Tsai(National Taiwan University of Science and Technology)[BM2-2] Development of a New District in the State of Hessen “FlexQuartier” ProjectJose Alberto Lagunes Ronzon (Technische Hochschule Mittelhessen), Moritz Hofmann(Technische Hochschule Mittelhessen), Milena Potpara (Technische Hochschule Mittelhessen),
Dirk Metzger (Technische Hochschule Mittelhessen), Joaquin Diaz (Technische Hochschule
Mittelhessen)[BM2-3] Process Re-engineering in Owner Organizations to Improve BIM-based Project
Delivery Using Requirements Management Platform
Ali Motamedi (École de technologie supérieure), Sylvain Vaudou (École de technologie
supérieure), Romain Leygonie (École de technologie supérieure), Daniel Forgues (École detechnologie supérieure)[BM2-4] A Framework for Visual BIM-based Maintenance Management in MRT Stations
Yi-Shian Huang (National Taipei University of Technology), Yu-Cheng Lin (National Taipei
University of Technology)[BM2-5] Modeling the Last-mile Problem of BIM Adoption

Jing Wang (the University of Hong Kong), Weisheng Lu (the University of Hong Kong), Jinying
Xu (the University of Hong Kong)

Session B (Meeting Room A/B on 7th Floor):[IOT] IoT, Sensors, and Monitoring
Chair: Prof. Hiroaki Date

(Hokkaido University)[IOT-1] Framework for a BIM-based Real-time Evacuation Guidance System in Smart
Buildings
Kayla Manuel (Osaka University), Nobuyoshi Yabuki (Osaka University), Tomohiro Fukuda(Osaka University)[IOT-2] Development of a Method to Detect Earthquake-Related Changes in Images
Taken by CCTV Cameras Surveying Civil Infrastructure

Arata Konno (Ministry of Land, Infrastructure, Transport and Tourism), Hirotaka Sekiya (Ministryof Land, Infrastructure, Transport and Tourism), Hideyuki Ashiya (Ministry of Land,
Infrastructure, Transport and Tourism)[IOT-3] A Human Following Robot for Assisting Tunnel Inspectors

Chia-Hsing Ho (Turing Drive Inc.), Yo-Ming Hsieh (National Taiwan University of Science andTechnology)[IOT-4] A Building Structural Health Management System by BIM and IoT Collaboration
Narito Kurata (Tsukuba University of Technology), Kenro Aihara (National Institute ofInformatics), Takahiro Konishi (Applied Technology Co., Ltd.), Hirofumi Yamaoka (Applied
Technology Co., Ltd.), Shinichi Kondo (Applied Technology Co., Ltd.)[IOT-5] Development of an Anomaly Detection System of Road Signs Using Mems
Accelerometers

Naomasa Haibara (Tokyo University of Science), Masayuki Saeki (Tokyo University of Science)

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Program and Book of Abstracts, ICCBEI 2019[Day 2] 14:00-15:00
Session A (Studio Theater on 7th Floor):[BM3] Building and Construction Information Modeling(BIM/CIM)-3
Chair: Prof. Shang-Hsien (Patrick) Hsieh (National Taiwan University)[BM3-1] BIM-based Wall Framing Calculation Algorithms for Detailed Quantity Takeoff
Chavanont Khosakitchalert (Osaka University), Nobuyoshi Yabuki (Osaka University), Tomohiro
Fukuda (Osaka University)[BM3-2] BIM-Supported Compliance Verification of Performance-based Car-park
Ventilation Design

Johannes Dimyadi (Compliance Audit Systems Limited), Robert Amor (University of Auckland)[BM3-2] The Study of Automatic CIM Models Development for Infrastructure Projects
Tzu-Tin Huang (National Taipei University of Technology), Yu-Cheng Lin (National Taipei
University of Technology)[BM3-4] An Automated BIM-integrated System for Change Order Cost Impact
Evaluation

Veerasak Likhitruangsilp (Chulalongkorn University), Tantri Handayani (Universitas GadjahMada), Nobuyoshi Yabuki (Osaka University), Photios Ioannou (University of Michigan)

Session B (Meeting Room A/B on 7th Floor):[LIS]Laser and Image Scanning

Chair: Prof. Yoshihiro Yasumuro (Kansai University)[LIS-1] Automatic Indoor Environment Modeling from Laser-scanned Point Clouds
Using Graph-Based Regular Arrangement Recognition
Hayato Takahashi (Hokkaido University), Hiroaki Date (Hokkaido University), Satoshi
Kanai(Hokkaido University)[LIS-2] Detecting Building Facade Deteriorations: Evaluation of 3D Laser Scanning andImage-Based Reconstruction Approaches to Determine Feasible Sttings in Data
Collection
Zhuoya Shi (NYU Tandon School of Engineering), Semiha Ergan (NYU Tandon School ofEngineering)[LIS-3] Automated UAV Route Planning for Bridge Inspection Using BIM-GIS Data

Yang Zou (University of Auckland), Molood Barati (University of Auckland), Enrique Del Rey
Castillo (University of Auckland), Robert Amor (University of Auckland), Brian H.W. Guo(University of Canterbury), Jiamou Liu (University of Auckland)[LIS-4] Measuring Railway Facilities by Using Two Mobile Laser Scanners Directly
Above the Rails
Kohei Yamamoto (PASCO Corp.), Nobuyoshi Yabuki (Osaka University)

15

Program and Book of Abstracts, ICCBEI 2019[Day 2] 15:15-16:15
Session A (Studio Theater on 7th Floor):[BM4] Building and Construction Information Modeling(BIM/CIM)-4
Chair: Prof. Weng Tat Chan (National University of Singapore)[BM4-1] Simulation and Optimization of Utility Tunnels Construction as Linear Projects

Mohamed Sherif (The American University in Cairo), Abdelhamid Abdallah (Helwan University),
Khaled Nasser (The American University in Cairo)[BM4-2] Integrating BIM into Green Residential Building Assessment: A Case Study
Fatma Abdelaal (University of Canterbury), Brian Guo (University of Canterbury), Yang Zou(University of Auckland), Mazharuddin Syed Ahmed (Ara Institute of Canterbury)[BM4-3] Enhanced Underground Utilities Management Integrated CIM Technologies
Sheng-Lun Zhuo (National Taipei University of Technology), Yu-Cheng Lin (National Taipei
University of Technology)[BM4-4] Developing Efficient Mechanisms for BIM Model Simplification

Jack C.P. Cheng (The Hong Kong University of Science and Technology), Keyu Chen (The Hong
Kong University of Science and Technology), Weiwei Chen (The Hong Kong University of
Science and Technology)

Session B (Meeting Room A/B on 7th Floor):[IPM]Information and Process Management
Chair: Prof San-Ho Lee (Yonsei University)[IPM-1] A Feasibility Study for LDAP Certification in Collaboration with Exiting
Accounts in RDBMS
Yoshiyuki Yokoyama (Japan Construction Information Center)[IPM-2] Semantic Modeling of Building Construction Emission Knowledge

Wenkai Luo (RMIT University), Guomin Zhang (RMIT University), Lei Hou (RMIT University),
Malindu Sandanayake (Victoria University)[IPM-3] Application and Analysis of System Architecture Model for Construction Project
Tatsuru Tomii (Kokusai Kogyo Co., Ltd.), Koji Makanae (Miyagi University), Raj Kapur Shah(Liverpool John Moores University)[IPM-4] Smart Construction Objects (SCOs): A New Theory of Smart Construction Is
Born?
Weisheng Lu (The University of Hong Kong), Yuhan Niu (Construction Industry Council),
Chimay Anumba (University of Florida)16

Program and Book of Abstracts, ICCBEI 2019

Organization of ICCBEI 2019

CEI Asian Group for Civil Engineering Informatics (AGCEI)Board of Director
President:
Nobuyoshi Yabuki, Osaka University, Japan

Members:
Weng Tat Chan, National University of Singapore, Singapore
Atsushi Fukasawa, Japan Construction Information Center, Japan
Shang-Hsien (Patrick) Hsieh, National Taiwan University, Taiwan
Jun Shang Kuang, The Hong Kong University of Science and Technology, Hong Kong
Sang-Ho Lee, Yonsei University, Korea
Veerasak Likhitruangsilp, Chulalongkorn University, Thailand
Zhiliang Ma, Tsinghua University, China
Koji Makanae, Miyagi University, Japan
Xiangyu Wang, Curtin University, Australia

Committee on Civil Engineering Informatics,

Japan Society of Civil Engineers (JSCE)
Chair:
Koji Makanae, Miyagi University, Japan
Vice Chair:
Katsutoshi Yasui, Obayashi Corporation, Japan
Osamu Okamoto, Ibaraki National College of Technology, Japan
Secretary General:
Hiroaki Mori, Chuo Fukken Consultants Co., Ltd., Japan
Members:
27 Standing Committee Members and Other Sub-committee members.

Supporters:
Japan Construction
Information Center17

Program and Book of Abstracts, ICCBEI 2019

Committees of ICCBEI 2019
Organizing Committee:
Chair:
Koji Makanae, Miyagi University, Japan
Vice Chair:
Nobuyoshi Yabuki, Osaka University, Japan
Members:
Yoichiro Chiba, Pacific Consultants International Group, Japan
Hiroshi Fukumori, Shimizu Corporation, Japan
Teppei Ishiuchi, Miyagi University, Japan
Hirotoshi Ito, Eight-Japan Engineering Consultants Inc., Japan
Hirofumi Matsuda, Trion Corporation, Japan
Hiroaki Mori, Chuo Fukken Consultants Co., Ltd., Japan
Masaki Sawa, Hazama Ando Corporation, Japan
Yoshihide Sekimoto, University of Tokyo, Japan
Masato Shiozaki, Mitsui Sumitomo Construction Co., Ltd., Japan
Ko Ueyama, CTI Engineering Co., Ltd., Japan
Katsutoshi Yasui, Obayashi Corporation, Japan

International Scientific Committee:
Chair:

Nobuyoshi Yabuki, Osaka University, Japan
Vice Chair:
Koji Makanae, Miyagi University, Japan
Members:
Robert Amor, The University of Auckland, New ZealandWeng Tat Chan, National University of Singapore, Singapore
Albert Y. Chen, National Taiwan University, Taiwan
Jack C. P. Cheng, The Hong Kong University of Science and Technology, Hong Kong
Hiroshige Dan, Kansai University, Japan
Tomohiro Fukuda, Osaka University, JapanLei Hou, Royal Melbourne Institute of Technology, Australia
Patrick Shang-Hsien Hsieh, National Taiwan University, Taiwan
Satoshi Kanai, Hokkaido University, Japan
Teppei Ishiuchi, Miyagi University, JapanKei Kawamura, Yamaguchi University, JapanJun Shang Kuang, The Hong Kong University of Science and Technology, Hong Kong
Sang-Ho Lee, Yonsei University, Korea
Veerasak Likhitruangsilp, Chulalongkorn University, Thailand
Vincent Yu-Cheng Lin, National Taipei University of Technology, Taiwan
Wilson W.S. Lu, The University of Hong Kong, Hong Kong
Zhiliang Ma, Tsinghua University, China
Tomohiro Mizoguchi, Nihon University, Japan
Kantaro Monobe, Tohoku Gakuin University, JapanAli Motamedi, École de Technologie Supérieure, Canada
Tatsunori Sada, Nihon University, Japan
Masayuki Saeki, Tokyo University of Science, Japan
Raj Kapur Shah, Liverpool John Moores University, UK
Yoshihiro Yasumuro, Kansai University, Japan
Xiangyu Wang, Curtin University, Australia
Yang Zou, The University of Auckland, New Zealand18

Program and Book of Abstracts, ICCBEI 2019

Book of Abstracts“Proceeding of the 4th International Conference on Civil and Building
Engineering Informatics” (ISBN978-4-600-00276-3)
can be downloaded fromhttps://www.iccbei2019.com

19Program and Book of Abstracts, ICCBEI 2019

AI1-1

NLP-BASED METHOD FOR AUTO-CORRECTING PUBLIC CONSTRUCTIONS DATA
Meng-Lin Yu1, Hao-Yung Chan2, Meng-Han Tsai3
1) Graduate Student, Department of Civil and Construction Engineering, National Taiwan University of Science and Technology,
Taipei, Taiwan. Email: m10705510@mail.ntust.edu.tw2) Ph.D. student, Department of Civil and Construction Engineering, National Taiwan University of Science and Technology, Taiwan.
Email: d10705005@mail.ntust.edu.tw
3) Assistant Professor, Department of Civil and Construction Engineering, National Taiwan University of Science and Technology,
Taiwan. Email: menghan@mail.ntust.edu.tw

Abstract: This research developed a term dictionary in the construction area for increasing segmentation quality of autocorrecting the data in the public construction cost estimate system (PCCES) data. According to the administrative rules in
Taiwan, all the information, such as bidding price, construction time, construction material, etc., of infrastructure projects
need to be recorded into the PCCES. The database with enormous amounts of historical data allows the government tohave statistical analysis and learn from the historical experience. However, in the database, most of the data is stored as
non-structural formats, mainly texts, which makes analyzing those data a tedious and time-consuming work. Therefore,
this research aims to structuralize the non-structural data in the PCCES database through natural language process (NLP)
methods. We construct a dictionary to eliminate inconsistency of terms and common names automatically. This dictionary
contains the terms and common names used in the field of civil engineering in Taiwan to facilitate the use of NLP parsing
and classification to correct erroneous data.
Keywords: natural language processing (NLP), public construction cost estimate system (PCCES), Chinese segmentation

AI1-2

ANALYSIS OF POWER USAGE AND BUILDING RESIDENTS RELATIONSHIPS FOR
ENERGY SAVINGS USING SOCIAL NETWORK ANALYSIS
Ru-Guan Wang1 and Chien-Cheng Chou2
1) Graduate Research Assistant, Information Technology for Disaster Prevention Program, Department of Civil Engineering, National
Central University, Taoyuan, Taiwan. Email: rubyw666@gmail.com
2) Professor, Information Technology for Disaster Prevention Program, Department of Civil Engineering, National Central University,
Taoyuan, Taiwan. Email: ccchou@ncu.edu.tw

Abstract: Reducing carbon footprints in the building sector can be achieved by altering power consumption behavior ofbuilding residents. Due to the influence of today’s declining birth rate and population aging, the structure of humansociety is changed, requiring the identification of key persons active in a community to persuade the others into saving
electricity. This research aims at applying the technique of social network analysis (SNA) to a publicly available smart
meter data set for building residents in Germany. Traditionally the head of a community can serve as the role ofbroadcasting energy-saving information, although its effectiveness varies with different circumstances. In the proposed
SNA-based approach, the German data set is firstly examined and pre- processed, such as augmenting building occupancy
data and relationships among residents. Then, different SNA indexes are explored in order to derive a generalized
procedure for such identification of key persons. More sustainable societies can be established if key persons of acommunity can be identified and get involved by using the proposed approach. Energy-saving information specific to eachtype of home appliance can be broadcast effectively and efficiently so that building residents can persuade easily.
Keywords: Social network analysis; smart meter data analytics; energy conservation.

20

Program and Book of Abstracts, ICCBEI 2019

AI1-3

AS-BUILT DETECTION OF STEEL FRAME STRUCTURE
USING DEEP LEARNING
Ryu Izutsu1, Nobuyoshi Yabuki2, and Tomohiro Fukuda3
1) Master Course Student, Division of Sustainable Energy and Environmental Engineering, Osaka University, Suita, Japan. Email:izutsu@it.see.eng.osaka-u.ac.jp
2) Ph.D., Prof., Division of Sustainable Energy and Environmental Engineering, Osaka University, Suita, Japan. Email:yabuki@see.eng.osaka-u.ac.jp
3) Ph.D., Assoc. Prof., Division of Sustainable Energy and Environmental Engineering, Osaka University, Suita, Japan. Email:fukuda@see.eng.osaka-u.ac.jp

Abstract: At the construction site, as-built management is generally performed by taking pictures and comparing themwith drawings or Building Information Modeling (BIM) models. Since this work is time-consuming and prone to humanerror, a more accurate and efficient method of capturing the progress is desired. The purpose of this research is toconstruct a system that can efficiently capture the progress of the construction by detecting each structural steel framecomponent such as a beam and a column under construction from images taken by a camera. First, we developed a
Convolutional Neural Network (CNN) that could detect structural steel frame components under construction fromimages by fine-tuning the existing Object Detection and Segmentation CNNs. Next, we constructed a system that cancapture each structural steel frame member from an image by integrating two constructed CNN models. Finally, we
conducted accuracy verification and evaluated the developed system.
Keywords: Convolutional Neural Network, Deep Learning, As-built Detection, Steel Frame, Segmentation.

AI1-4

Video-based construction vehicles type recognition
Chen-Hsuan Wang1, I-Tung Yang2, Meng-Han Tsai3
1) Graduate Student, Department of Civil and Construction Engineering, National Taiwan University of Science and Technology,
Taiwan. Email: m10705506@mail.ntust.edu.tw
2) Chairman, Professor, Department of Civil and Construction Engineering, National Taiwan University of Science and Technology,
Taiwan. Email: ityang@mail.ntust.edu.tw
3) Assistant Professor, Department of Civil and Construction Engineering, National Taiwan University of Science and Technology,
Taiwan. Email: menghan@mail.ntust.edu.tw

Abstract: This research is an ongoing project that aims to recognize construction vehicles automatically for saving thelabor cost. Monitoring the construction vehicle that enters and leaves the construction site can help with tracking theconstruction progress and recognizing the abnormal vehicles. In modern construction sites, IP cameras have been widely
utilized for security purposes. The enormous amounts of gathered videos bring opportunities for us to monitor theconstruction vehicle without assigning a gate guard. However, although IP cameras can store all the historical images, it
is very complicated and time-consuming to calculate the traffic flow of each vehicle type from the surveillance imagesof the day. Therefore, this research proposed a real-time construction vehicle recognition system. The proposed system
contained three major parts: an image recognition algorithm for recognizing the vehicle type, a database for storing therecognition results, and a dialogue system for supplying the structuralized results to the site manager. For the image
recognition algorithm, the YOLOv3 algorithm was utilized for processing the video frame by frame and recognizing thevehicle type. The results of the recognition would be analyzed and stored in a structuralized database for further use.
Lastly, a chatbot-based dialogue system was developed to provide the site information and push instant warning to therelated personnel. After a feasibility test, the unstructured construction video data could be transferred into structured
information autonomously. Also, additional labor resources could be saved and thus increase the efficiency of the overall
process of construction site management.
Keywords: object detection, object location, image segmentation, YOLOv3 algorithm, dialogue system.

21

Program and Book of Abstracts, ICCBEI 2019

AI1-5

GA-BASED OPTIMIZATION FOR CONSTRUCTION SEQUENCE OF PRECAST AND
CAST-IN-PLACE CONCRETE COMPONENTS
Songyang Li1, Zhiliang Ma2
1) Ph.D. Candidate, Department of Civil Engineering, Tsinghua University, Beijing, P.R. China. Email: skuyinlee@gmail.com
2) Ph.D., Prof., Department of Civil Engineering, Tsinghua University, Beijing, P.R. China. Email: mazl@tsinghua.edu.cn

Abstract: To reduce the time and cost, as well as to improve the efficiency and safety of precast concrete construction,
the construction sequence of precast concrete (PC) components and cast-in-place (CiP) components needs to be optimized.
To solve this problem, a Genetic Algorithm-based method is proposed in this paper. Firstly, based on the real projectexperience and some reasonable assumptions, the construction sequence of PC and CiP components problem is analyzed
and several optimization objectives and constraints are summarized. Then a GA- based method to solve the construction
sequence problem is implemented, which includes the coding method, fitness function as well as crossover, mutation andselection operations. Finally, a case study is conducted to verify the proposed method. The results indicate that the method
can effectively find the optimal solution for the construction sequence of PC components and CiP components.
Keywords: Precast concrete buildings, Construction sequence, Genetic Algorithm, Optimization

AI2-1

BASIC STUDY ON DETECTING BREAKING SOUNDS OF STRUCTURAL MEMBERSBY USING MACHINE LEARNING
Takeo Izumita1, Masayuki Saeki2
1) Master’s Student, Tokyo University of Science, Chiba, Japan. Email: 7618503@ed.tus.ac.jp
2) Dr. Eng., Prof., Tokyo University of Science, Chiba, Japan. Email: saeki@rs.noda.tus.ac.jp

Abstract: In case of a large earthquake, it is necessary to grasp the damage state of structures in disaster areas as soon as
possible. Therefore, we have been trying to develop a sensor which is able to detect the destruction of structuralmembers.
In this research, we focus on the breaking sound of wood that is easily recorded using a smartphone and is expected to bediscerned from any other sounds with the help of machine learnings. As a basic research, first experiments were carriedout to record the breaking sounds of woods as well as other sounds such as talking voice, crashing dishes, closing door, etc.
Second, Mel Frequency Cepstral Coefficients (MFCC), that is widely used as acoustic features in the field of speech
recognition, were calculated by analyzing the recorded samples. Third, Multi-Layer Perceptron (MLP) and Support
Vector Machine (SVM) were applied to the MFCCs to categorize them into two groups which were destruction soundand the others. In the analysis, 156 MFCCs were prepared as training data. In case of SVM, about 70% of these data
were properly recognized. On the other hand, MLP with one hidden layer gave a success rate of about 90%. In addition,
the effect of the selection of training data sets and the MLP models on the success rate was investigated.
Keywords: Mel Frequency Cepstral Coefficients, Machine Learning, breaking sound, damage estimation

22

Program and Book of Abstracts, ICCBEI 2019

AI2-2

COMPUTER VISION-BASED IN-BUILDING HUMAN DEMAND ESTIMATION FOR
INSTALLATION OF AUTOMATED EXTERNAL DEFIBRILLATORS
Wen-Xin Qiu1, Albert Y. Chen2
1) Graduate student, Civil Engineering, National Taiwan University, Taipei, Taiwan. Email: r07521505@ntu.edu.tw
2) Assoc. Prof., Civil Engineering, National Taiwan University, Taipei, Taiwan. Email: AlbertChen@ntu.edu.tw

Abstract: To support a better indoor location distribution of automated external defibrillators (AEDs), the real demand,
the actual human distribution, should be known. In this research, a computer vision-based process is proposed. The data
are collected in the form of image sequences, such as surveillance cameras, in the building. Image based humandetection and tracking are applied, and the depth estimation from a deep neural network is utilized to estimate thelocation of each person. The appearing and disappearing locations are clustered to estimate the node in the indoor
traveling network to other spaces in the image. The amount of people are accumulated, for locations in the building, toserve as the demand distribution, and a network based model for AED location optimization can be further integrated.
Keywords: Automated external defibrillators, Human detection and tracking, Depth estimation

AI2-3

MULTI-DIMENSIONAL SEQUENCE ALIGNMENT FOR CONTEXT-AWARE
HUMAN ACTION ANALYSIS OF BODY-SENSOR DATA
Nipun D. Nath1, Amir H. Behzadan2, and Prabhat Shrestha3
1) Ph.D. Student, Zachry Department of Civil Engineering, Texas A&M University, College Station, Texas, USA. Email:nipundebnath@tamu.edu
2) Associate Professor, Department of Construction Science, Texas A&M University, College Station, Texas, USA. Email:abehzadan@tamu.edu
3) M.S. Student, Department of Construction Science, Texas A&M University, College Station, Texas, USA. Email:prabhat1993@tamu.edu

Abstract: Time-motion human data are critical to analyzing activities of construction field crew and their spatiotemporalinteractions. A major limitation of the current practice, however, is that the context in which data is collected is rarely
incorporated in data analysis. This paper investigates the problem of incorporating context into human activity recognition(HAR). This is achieved by using a multi-dimensional sequence alignment (MSA) method that transforms raw bodymounted sensor data to basic human actions in a one-step process. In this paper, an action is defined as a single, isolated
effort (e.g., kneeling, pushing), while an activity refers to an ongoing process over a period of time (e.g., pipefitting,welding). When grouped together, actions performed in a specific sequence form an activity. The designed MSA method
enables the recognition of human actions through comparing the similarities between several time series sequences ofbody-sensor data, thus fusing contextual information on temporal dependency with classification. The method is tested ona publicly available dataset in subject-dependent and subject-independent classifications. It is found that in both cases, the5-fold cross-validation classification accuracy is >97% which is on par with or higher than the performances achieved inprevious studies.
Keywords: Multi-dimensional sequence alignment, machine learning, human activity recognition, smartphone sensors.

23

Program and Book of Abstracts, ICCBEI 2019

AI2-4

APPLICATION OF INTELLIGENT SYSTEMS IN THE UNDERGROUNDEXCAVATION INDUSTRY: A SHORT REVIWE
Mohsen Ramezanshirazi1, Mohammad Norizadeh cherloo2, Orod Zarrin3
1) Ph.D., Department of structural and geotechnical engineering, Sapienza University of Rome, Italy.Email:Mohsen.ramezanshirazi@uniroma1.it
2) Eng., University of science and technology (IUST). Email: M.norizadeh1369@gmail.com

Abstract: According to the growing trend of the world population, the need for underground transportation is increasing. To satisfy theurban development the use of the underground space acquired increasing importance and consequently tunnels are playing an essential
role in the development of urban infrastructures.
A variety of construction methods have been developed for tunneling; in an urban area, the mechanized excavation by using atunnel boring machine (TBM) is the more effective option. Tunnels are constructed under various kinds of geological conditions,different from hard rock to very soft soils. By respect to the number of empirical and semi-empirical methods obtainable for predicting
phase in mechanized tunneling, there is a beneficial advantage to using intelligence instrument. This paper aimed to the presented theadvantages of inteligence prediction tool with used artificial neural network(ANN). The ANN crate based on different advancealgorithms and data collected from the real Tunnel project. Carry out networks optimization and advantages of the method on time andhuman resource in projects proposed. The relevant results proved that the capability of this method for prediction and shown good
agreements between prediction results .The main aim of this study is to introduce the capable Artificial Neural Networks (ANNs) as
well as the effectiveness of ANNs in order to predict the TBM performances employed for tunnel excavation.

Keywords: Intelligent system, ANNs, Tunnel Boring Machine, TBMs.

AI2-5

DETERMINATION OF AUTOMATED CONSTRUCTION OPERATIONS FROMSENSOR DATA USING MACHINE LEARNING
Aparna Harichandran1, Benny Raphael2 and Abhijit Mukherjee3
1) Joint Doctoral Candidate, Department of Civil Engineering, Indian Institute of Technology Madras, Chennai, India, and School of
Civil and Mechanical Engineering, Curtin University, Bentley, WA 6102, Australia. Email: aparnaharichandran@gmail.com
2) Professor, Department of Civil Engineering, Indian Institute of Technology Madras, Chennai, India. Email: benny@iitm.ac.in
3) Professor, School of Civil and Mechanical Engineering, Curtin University, Bentley, WA 6102, Australia. Email:abhijit.mukherjee@curtin.edu.au

Abstract: Automated construction creates an intricate working environment involving workers and machines. The
added complexity of automated construction demands a rigorous monitoring system compared to conventional
construction. The first stage of developing such a monitoring system is the identification of construction operations. This
paper discusses a methodology for the identification of construction operations from sensor data. The methodology isillustrated using the case study of a coordinated lifting equipment implemented in a laboratory. The data is collectedfrom a small scale structural frame consisting of steel modules in a controlled laboratory condition. The automatedsystem follows a top-down construction method where the major construction operations are performed at the groundlevel and the structure is lifted upwards in stages. Strain and acceleration measurements were collected from thestructure during construction. Each operation is associated with a unique pattern of measurements at each sensor location.
The measurement data is used for analysis by support vector classification. Parameters like error penalty (C) and widthof Gaussian kernel (σ) were varied to obtain the best prediction results. The results of the analysis show that the linear
classification gives better results compared to the nonlinear classification for all operations except coordinated lifting.
However, coordinated lifting is the best-predicted operation with an accuracy of 96%. Selection of optimal values of C
and σ enhances the accuracy of classification. The features extracted from data seems to highly influence the learning of
the algorithm and the performance of prediction. The results show the potential for using machine learning techniques
for monitoring automated construction operations.
Keywords: Automated Construction, Construction Monitoring, Machine Learning, Support Vector Machines24

Program and Book of Abstracts, ICCBEI 2019

CV-1

STUDY ON AUTOMATIC CHALK MARKS RECOGNITION FOR CONCRETE
TUNNEL INSPECTION USING DEEP LEARNING
Yao Zhang1, Kei Kawamura 2, Cuong Nguyen Kim 3, Koji Oshikiri 4, and Taro Kikuchi 51) Graduate Student. Graduate School of Science & Technology for Innovation, Yamaguchi University, Japan. E-mail:i503vg@yamaguchi-u.ac.jp
2) Ph.D., Assoc. Prof., Graduate School of Science & Technology for Innovation, Yamaguchi University, Japan. Email:kay@yamaguchi-u.ac.jp
3) Dr. Eng., Faculty of Highway & Bridge, Mientrung of Civil Engineering, Vietnam. E-mail: nguyenkimcuong @ muce.edu.vn
4) Ricoh Company, Ltd. Japan.E-mail:kohji.oshikiri@jp.ricoh.com
5) Ricoh Company, Ltd. Japan. E-mail:taroh.kikuchi@jp.ricoh.com

Abstract: Current methods of practice for inspection of concrete tunnel typically involve visual assessments and drawing
notes conducted manually by trained inspectors. The labor intensive and time consuming natures of manual inspection
have engendered research into development of method for automated damage identification using computer vision
techniques. Due to the limitation of the information reflected by the current photography technology, in this study,
compared with other studies that directly detect cracks from images (Eftychios Protopapadakis et al., 2019; F. Panella etal., 2018; Suguru Yokoyama & Takashi Matsumoto, 2017), the author proposed to identify chalk marks that can be
determined to be deformation. In this study, in order to improve the efficiency of tunnel inspection, it verified theautomatic recognition of chalk marks in a concrete tunnel with a reasonable accuracy. As a result, a chalk mark classifier
using a deep convolutional neural network on deep learning has been generated to detect the existence of chalk marks as astage study of recognition. The proposed method is evaluated in terms of accuracy, precision and recall is shown.
Keywords: concrete inspection, deep learning, convolutional neural network, image recognition

CV-2

GA-CNN based automatic crack detection and classification method for concrete
infrastructures
Cuong Nguyen Kim1), Kei Kawamura2), Yao Zhang3), and Amir Tarighat4)

1) Dr. Eng, Faculty of Highway & Bridge, Mientrung of Civil Engineering, Vietnam. E-mail: nguyenkimcuong @ muce.edu.vn
2) Assoc. Prof., Graduate School of Science & Technology for Innovation, Yamaguchi University, Japan. Email: kay@yamaguchiu.ac.jp
3) Graduate Student. Graduate School of Science & Technology for Innovation, Yamaguchi University, Japan.E-mail:i503vg@yamaguchi-u.ac.jp
4) Assoc. prof, Department of Civil Engineering, Shahid Rajaee Teacher Training University, Iran, tarighat@srttu.edu

Abstract: Automatic crack detection is a main task in a crack map generation of the existing concrete infrastructure
inspection. This paper presents an automatic crack detection and classification method based on genetic algorithm (GA)to optimize the parameters of image processing techniques (IPTs). The crack detection results of concrete infrastructuresurface images under various complex photometric conditions still remain noise pixels. Next, a deep convolution neuralnetwork (CNN) method is applied to classify crack candidates and non-crack candidates automatically. Moreover, theproposed method is compared with the state-of-the-art methods for crack detection. The experimental results validate thereasonable accuracy in practical application.
Keywords: Crack detection, genetic algorithm, convolution neural network.

25

Program and Book of Abstracts, ICCBEI 2019

CV-3

AS-BUILT MODELING OF STEEL STRUCURES USING SYMMETRY
Takuya Suzuki 1, Tomohiro Mizoguchi 2
1) Master Student, Department of Computer Science, College of Engineering, Nihon University, Fukushima, Japan.
2) Associate Prof., Department of Computer Science, College of Engineering, Nihon University, Fukushima, Japan. Email:mizoguchi.tomohiro@nihon-u.ac.jp

Abstract: As numerous number of civil infrastructures are aging in Japan, new information technologies are required tosupport efficient and effective maintenance of infrastructures. As-built modeling is one of the techniques that reconstructs
3D model reflecting the current status of the structure from point cloud acquired by laser scanner. Created modes are
effectively used in various stages of inspection, such as prior scheduling before inspection and recording of inspection
results on the 3D model after inspection. We focus on steel structures in bridges in this work. Many steel members areused in bridge and they are arranged in complicated manner. However, from the viewpoint of function and aesthetics ofbridges, steel members are arranged according to the specific rules defined by the designer. For example, steel members
are oriented in the vertical direction and are arranged at regular intervals in the horizontal direction. In addition, they arearranged symmetrically in the front-rear and right-left sides of the bridge. Therefore, detecting such symmetry from point
cloud and utilizing them in modeling process can improve efficiency of as-built modeling, the quality of the 3D
reconstructed model, and robustness to the absence of point cloud, compared with the conventional methods in which
each steel member is modeled individually. In this paper, we propose a new method for reconstructing high-quality 3Dmodel of steel structures of bridges from laser scanned point cloud enhancing symmetry. The method first detects multiple
planar reflection symmetry which dominate the large portion of bridge by shape matching. The next step detects each steel
members efficiently by simplifying point cloud based on voxelization, extracting skeleton structure, and evaluating point
distribution using principal component analysis. Then the members arranged in symmetrical positions and posture aregrouped together, and finally 3D template models are fitted to the group members simultaneously under symmetry
constraints. Experimental results demonstrate good performance of our proposed method.
Keywords: Terrestrial Laser Scanner, As-Built Modeling, Symmetry.
CV-4

A REVIEW OF RESEARCH ON ADVANCED AUTONOMOUS TECHNOLOGIESFOR BRIDGE INSPECTION
Rina Hasuike1, Koji Kinoshita2, Lei Hou3
1) Ph.D. Candidate, Department of Civil Engineering, Gifu University, Gifu, Japan. Email: w3912010@edu.gifu-u.ac.jp
2) Dr. Eng., Associate Professor, Department of Civil Engineering, Gifu University, Gifu, Japan. Email: kinosita@gifu-u.ac.jp
3) Dr. Eng., Senior Lecturer, School of Civil Engineering, RMIT University, Melbourne, Australia. Email: lei.hou@rmit.edu.au

Abstract: Nowadays, many of these infrastructure projects are having serious aging issues, and therefore, timely
inspection and repair works are crucial to ensure these structures are safe to use. So far, bridge inspection has been
conducted primarily based on visual inspection by human inspectors. However, the downside of visual inspection isapparent. Firstly, conducting visual inspections can be quite time-consuming, especially in large and complex bridge
structures; and secondly, this method cannot well address occupational health and safety issues such as working at height.
Under this consideration, applying advanced autonomous technologies such as Unmanned Aer- ial Vehicles (UAVs) andimage processing techniques to support human inspectors has attracted growing interest in the industry. In this study, aliterature review was conducted with a focus placed around identifying the best practice of current technologicalapproaches and proposing the futuristic research directions for technological re- finement and improvement. Methodically,
this study examined the publications over the past 20 years, i.e., from 1999 to 2018, and leveraged the tool of CiteSpace toderive significant review findings on UAV and defect detec- tion research.
Keywords: unmanned aerial vehicles, image processing, bridge inspection

26

Program and Book of Abstracts, ICCBEI 2019

CV-5

A PERFORMANCE EVALUATION OF FEATURE DETECTORS AND
DESCRIPTORS FOR UNMODIFIED INFRASTRUCTURE SITE DIGITAL IMAGES
Natthapol Saovana1, Nobuyoshi Yabuki2, and Tomohiro Fukuda3
1) Ph.D. Candidate, Division of Sustainable Energy and Environmental Engineering, Graduate of School of Engineering, Osaka
University, Osaka, Japan. Email: u089147k@ecs.osaka-u.ac.jp
2) Ph.D., Prof., Division of Sustainable Energy and Environmental Engineering, Graduate of School of Engineering, Osaka
University, Osaka, Japan. Email: yabuki@see.eng.osaka-u.ac.jp
3) Ph.D., Assoc. Prof., Division of Sustainable Energy and Environmental Engineering, Graduate of School of Engineering,Osaka University, Osaka, Japan. Email: fukuda@see.eng.osaka-u.ac.jp

Abstract: Image registration is a process to match and align a group of images. It is the first step of photogrammetrictechniques such as Structure from Motion (SfM) to construct a model. It uses feature detector and descriptor algorithms todetect features inside each image and link these similar feature pairs to solve the unknown variables that is required forfurther processes. Before using feature detector and descriptor algorithm with a specific knowledge, a performance
evaluation of these algorithm is necessary to be conducted because each algorithm has different advantages anddisadvantages over specific expertises. Infrastructure project digital images are unique because the structures have similar
shapes and smooth surfaces, which can complicate the image registration quality. Moreover, the uncontrolled lighting canfurther decrease the clearness and sharpness of images. Therefore, it is very challenging to get satisfied output byprocessing unmodified infrastructure images through photogrammetric techniques. Although these algorithms havevarious types and directly affect the quality of the model, there are no performance evaluations in the domain of
infrastructure images to be seen. This study proposes the performance evaluation of robust feature detector and descriptor
algorithms. The evaluation is separated into two categories, which are the feature coverage inside the region of interest(ROI) and the performance of feature matching. The result shows that Oriented FAST and Rotated BRIEF (ORB) can
detect the highest amount of features with the shortest amount of time. However, Speeded Up Robust Features (SURF) canbetter detect features inside the ROI, which may lead to the better output quality. Finally, SURF128, which is SURF thatwas extended to utilize 128 floats, can finish the entire process at the fastest speed. This study can serve as a suggestion
when feature detector and descriptor algorithms have to be chosen to solve questions inside the infrastructure domain.
Keywords: Image registration; feature detector and descriptor algorithms; feature detection; feature matching;infrastructure digital images
XR-1

EFFICIENT ACCESS TO INSPECTION DATA BASED ON AUGMENTEDREALITY USING A “BRIDGE - CARD”
Hisao Emoto1, Hiroki Komuro2, Takehiko Midorikawa3, Hideaki Nakamura4, Kei Kawamura51) Dr. Eng., Assoc. Prof., National Institute of Technology, Fukushima, Japan. Email: emoto@fukushima-nct.ac.jp
2) Student, National Institute of Technology, Fukushima, Japan. Email: komuro-h@city.iwaki.lg.jp
3) Dr. Eng., Prof., National Institute of Technology, Fukushima, Japan. Email: midorikawa@fukushima-nct.ac.jp
4) Dr. Eng., Prof., Yamaguchi University, Yamaguchi, Japan. Email: nakahide@yamaguchi-u.ac.jp
5) Dr. Eng., Assoc. Prof., Yamaguchi University, Yamaguchi, Japan. Email: kay@yamaguchi-u.ac.jp

Abstract: In Japan, the time has come to rapidly rebuild bridges and other civil infrastructure during this period of
economic growth to improve the service life of bridges and to develop long-standing government policy measures tomaintain bridges. Normally, bridge inspections are performed by a close visual inspection on site. However, the numberof professionals have decreased. For this reason, it is important to efficiently access necessary data on site to save labor.
To aid in this, the AR (Augmented Reality) technique has recently been developed.
In order to identify the bridge, a method of accessing data using “marker type” AR technology is employed. As inprevious studies, a marker directly pasted on a bridge near a noted condition, such as a crack etc., has been proposed. Thisis useful for accessing the bridge’s condition data. But the data is not suitable for a bird's- eye viewing of the whole bridge.
Instead, it is easy to access whole bridge data using a “Bridge-Card”, functioning like a business card, on which bridge
specifications are documented. In this way, the Bridge Card is a marker.
This study aims to efficiently save labor for visual inspections using “bridge-cards”, which are the size of abusiness card and developed with a bridge inspection support system for smart phones. This system delivers specification
data, inspection data, repair and reinforcement data, among other information used by AR when the “bridge-cards” is readby the smart phone. This paper discusses the suitability of the use of a marker, while considering the reality that it isuseful to access data off-site, in addition to location-based AR, which requires a bridge site visit.
Keywords: bridge maintenance support system, visual inspection, bridge-card, augmented reality27

Program and Book of Abstracts, ICCBEI 2019

XR-2

Bidirectional linking of 4D-BIM planning with Virtual and Augmented Reality
Felix Dreischerf1 and Habeb Astour2
1) Ph.D. Candidate, Department of Civil Engineering, University of Applied Science Erfurt, Erfurt, Germany.
Email: felix.dreischerf@fh-erfurt.de2) Dr.-Ing., Prof., Department of Civil Engineering, University of Applied Science Erfurt, Erfurt, Germany.
Email: habeb.astour@fh-erfurt.de

Abstract: Building information modeling (BIM) currently provides a significant benefit to digitization in theconstruction industry in and outside of Germany. New techniques such as Augmented Reality (AR) and Virtual
Reality (VR) can contribute to the spread of the BIM methodology in the construction industry and it willcomplement traditional planning and execution methods. Certainly however, these innovative technologies havethe potential to simplify the entire planning and execution process.
The BIM methodology, VR, and AR are not well-known nor well applied in Germany. BIM is used in building
design, but mostly in pilot projects. It needs to be implemented in the daily workflow. By combining it with new
visualization methods, the added value of the BIM methodology will be increased and the process of its implementation
will possibly be accelerated.
Today, the linking of BIM with AR or VR is done only in basic features. BIM combined with computer aided
planning methods and AR or VR enable new approaches and procedures. This leads to a simplification of planning andexecution. That means that the combination of BIM and VR/AR can be one of the most important methodologies in the
future of building design. However, this combination and its use cases need to be developed to increase its practicability.
The following paper explains a concept for linking BIM with AR and VR. Therefore, a short overview of theseelements and the linking methods is given. The focus of the linking is set on the connection between
3D design andconstruction schedule. The combination is known as 4D BIM. The result is a concept of connecting 4D BIM with AR andVR.
Keywords: Building Information Modeling, BIM, Virtual Reality, VR, Augmented Reality, AR, 4D, Planning
XR-3

Verification about work efficiency improvement by using an Augmented Reality andWearable computer
Satoshi Yamanaka1, Shinya Sugiura2, Ryo Tajima3, and Takafumi Yamanaka4
1) Chief Engineer, Obayashi CO., Ltd., Tokyo, Japan. Email: yamanaka.satoshi@obayashi.co.jp
2) Manager, Obayashi, CO., Ltd., Tokyo, Japan, Email: sugiura.shinya@obayashi.co.jp
3) Deputy Manager, Obayashi CO., Ltd., Tokyo, Japan, Email: tajima.ryo@obayashi.co.jp
4) Dr. Eng., Chief Engineer, Obayashi CO., Ltd., Tokyo, Japan, Email: yamanaka.takafumi@obayashi.co.jp

Abstract: Conventionally, in construction site, workers used to imagine a structure to be constructed based on a design
drawing, and executed construction using an explicit thing such as stake or marking on the site. However, whether they
can imagine the finished product accurately depends on the ability of the individual, so work mistakes and rework may
occur. Also, there was a problem that it took a lot of time for preparatory work such as installation work of the stake.
In the construction industry in Japan, the labor shortage is getting worse because the number of employees has
declined and are aging, but construction investment tends to recover. Even under such circumstances, improvement ofwork efficiency is required for the entire industry to ensure quality. The use of Information and Communication
Technology (ICT) is mentioned as a means to improve work efficiency, and among them we focused on Augmented
Reality (AR) technology and Wearable computer and worked to solve the problem.
In this study, we installed the U-shaped drain of berm drainage of 330 meters by using the AR and the wearable
computer omitting the installation work of the stake which we have done so far, and the effect by use was verified. In AR,
we superimposed a three-dimensional model created from Computer-Aided Design (CAD) software using image
recognition method, and adopted “Hololens” it's kind of main display type, among wearable computers which can wear on
the head. In addition, automatic tracking type Total Station was used for fine adjustment and position confirmation of the
U-shaped drain to be installed. As a result of carrying out the actual construction after the test construction and verifying
it, it was possible to shorten the working time by about 48%, and it was confirmed that using this technology contributes
to the improvement of working efficiency.
Keywords: ICT, Augmented Reality, Productivity Improvement28

Program and Book of Abstracts, ICCBEI 2019

XR-4

VISUALIZATION OF CONSTRUCTION PROCESS BY CONSTRUCTION SITESENSING AND DIGITAL TWINS
Atsushi Takao1, Nobuyoshi Yabuki2, Kohei Seto3, and Iwao Miyata 41) Okumura Corporation, Tokyo, Japan. Email: atsushi.takao@okumuragumi.jp
2) Division of Sustainable Energy and Environmental Engineering, Graduate School of Engineering, Osaka University, Osaka,
Japan. Email: yabuki@see.eng.osaka-u.ac.jp
3) Okumura Corporation, Tokyo, Japan. Email: kohei.seto@okumuragumi.jp
4) Okumura Corporation, Tokyo, Japan. Email: iwao.miyata@okumuragumi.jp

Abstract: This paper presents efforts to improve the productivity of construction sites by visualizing construction process.
As a visualization method, we adopted Digital Twins that combine 3D models and sensing data (construction machineryon-board sensor, AI analysis of cloud camera image). Reproducing the situation at the construction site with Digital
Twins made it easier for engineers to understand and analyze the works. Result of the construction site analysis showed
the improved efficiency.
Keywords: Digital Twins, Cloud camera, Sensor, 3D model, Visualization

XR-5

AR VISUALIZATION OF PHYSICAL BARRIER FOR WHEELCHAIR USERSBASED ON REALTIME DEPTH IMAGING
Rio Takahashi1, Hiroshige Dan2, and Yoshihiro Yasumuro3
1) Graduate Student, Graduate School of Science and Engineering, Kansai University, Suita City, Japan. Email:media.englab.tostemkuniv15@gmeil.com
2) Ph.D., Assoc. Prof., Department of Environmental and Urban Engineering, Kansai University, Suita City, Japan. Email:dan@kansai-u.ac.jp
3) Ph.D., Prof., Department of Environmental and Urban Engineering, Kansai University, Suita City, Japan. Email: yasumuro@kansaiu.ac.jp

Abstract: Since Japan is facing the issue of rapid aging society, the number of potential wheelchair users is overgrowing,as more and more seniors need long-term cares. The government has worked on prevailing the barrier-free environment
by establishing a law regarding promotion of smooth transfer for elderly and physically disabled people. Holding the 2020
Olympics is also a vital situation for infrastructure development in Japan. Barrier-free maps, for example, are prepared inmany communities, but they cover only existences of facilities, e.g., lifts, slopes, and handrails, in major public
institutions. Therefore, they miss the details of physical barriers, such as bumps and width clearances on the path, needed
for the independent mobility of the wheelchair users. This paper addresses a method to find out physical barriers by using adepth camera to visualize them efficiently through augmented reality, which may be useful for the facility managers. A
depth camera acquires 3D point cloud in the target space and checks the existence of interference between theenvironment and the volume of an actual wheelchair. The proposed system also performs back-projection of the detectedbarriers onto RGB color video frames for 2D AR representation. The verification of the achieved accuracy of the barrier
check, as well as the implementation scheme, are reported in the paper.
Keywords: Augmented Reality, Wheelchair user, Barrier-free, Depth imaging

29

Program and Book of Abstracts, ICCBEI 2019

FM-1

STEEL BRIDGE INFORMATION DELIVERY MODELFOR EARNED VALUE MANAGEMENT (EVM)
Teruaki Kageyama1, Nobuyoshi Yabuki2
1) Senior Researcher, Research Department, Japan Construction Information Center (JACIC), Tokyo, Japan.
Email: kageyamt@jacic.or.jp
2) Ph.D., Prof., the Division of Sustainable Energy and Environmental Engineering, Graduate School of Engineering,Osaka University, Japan. Email: yabuki@see.eng.osaka-u.ac.jp

Abstract: Building Information Modeling (BIM) has been widely adopted in the building industry, and its establishedmethods and technologies show enormous potential in benefiting the civil engineering industry. Through the rapid growthof BIM in the civil engineering industry, mandatory use in government procurements, and utilization for improving
productivity, the importance of 3D product models in the civil engineering industry is becoming increasingly prominent.
The purpose of this paper is to propose for government organizations to implement Earned Value Management (EVM)
using 3D product models. Firstly, the government contract process in line with the acts, guidelines and standards are
mapped using an Information Delivery Manual (IDM). Next, in order to implement EVM using 3D product models, it isnecessary to organize the relationship between the Work Package (WP), the minimum units of the Work Breakdown
Structure (WBS), and the government contract units. For this reason, 3D product models with government contract units
are defined as Information Delivery Elements (IDE). Finally, by using the Steel Bridge Information Delivery Model (SBIDM), which has been integrated with the IDE of the steel bridge structure, the usability of EVM is evaluated.
Keywords: BIM for infrastructure, product model, information delivery manual, earned value management

FM-2

A PROPOSAL OF DETERIORATION PREDICTION MODEL FOR TUNNEL
LIGHTING FACILITIES USING MARKOV STOCHASTIC PROCESS
Noriaki Maeda1, and Kei Kawamura2
1) Graduate School, Doctor Course, Sciences and Technology for Innovation, University of Yamaguchi, Yamaguchi, Japan.
Email: g005wc@yamaguchi-u.ac.jp
2) Dr Eng., Assoc. Prof., Sciences and Technology for Innovation, University of Yamaguchi, Yamaguchi, Japan. Email:kay@yamaguchi-u.ac.jp

Abstract: Asset management systems (AMS) are powerful tool for maintenance of civil infrastructures. The management
system model consists of the four steps cycle model that is PDCA(Plan-Do-Check-Action) in the total quality
management system. This paper proposes a deterioration prediction model on the management system for tunnel lighting
facilities. The model is a time-based Markov stochastic process for predicting the deterioration of health degree of a tunnel
unit. The tunnel unit is equivalent to all of tunnel lighting facilities in a tunnel.
Firstly, this paper explains a characteristics of the Markov stochastic process model applied to the deterioration
prediction of a tunnel unit. Secondly, the deterioration of health degree of a tunnel unit is formulated by solving themaster-equation of Markov stochastic process. Then, the applicability and validity of the deterioration prediction model isshown by illustrating numerical examples using visual inspection data of existing tunnels. Finally, the paper indicates how
the model functions in AMS.
Keywords: AMS, tunnel lighting facilities, Markov stochastic process, deterioration, prediction, health degree, masterequation, inspection30

Program and Book of Abstracts, ICCBEI 2019

FM-3

VRP-BASED MODEL FOR LANE MARKING ASSESSMENT WITH MRU
VEHICLE1
Yu-Chun Lin1, Si-Ting Liao2, Chieh (Ross) Wang3, and Albert Y. Chen4
1) Master Student, Department of Civil Engineering, National Taiwan University, Taipei, Taiwan. Email: r06521515@ntu.edu.tw
2) Master Student, Department of Civil Engineering, National Taiwan University, Taipei, Taiwan. Email: r07521501@ntu.edu.tw3) R&D Staff, Energy and Transportation Science Division, Oak Ridge National Laboratory, Knoxville, TN, USA. Email:cwang@ornl.gov
4) Associate Professor, Department of Civil Engineering, National Taiwan University, Taipei, Taiwan. Email: albertchen@ntu.edu.tw

Abstract: Evaluation of lane marking conditions has advanced from visual and/or manual inspections, which can beunsafe and time-consuming, to mobile assessments using vehicle-mounted devices that allow transportation agencies tocollect retroreflectivity data at a large scale in a safer and efficient manner. However, cost-effectively routing andoperating these mobile retroreflectivity units (MRUs) at a large scale can be a unique challenge. This study proposes avehicle routing problem (VRP) based model to optimize the routing of MRUs. The model takes into account theadditional costs of daily and weekly operations of MRUs, such as remounting the device and traveling between tasks.
Keywords: vehicle routing problem (VRP); pavement markings; mobile retroreflectivity unit (MRU)

FM-4

THE GATEWAY TO INTEGRATING USER BEHAVIOR DATA IN “COGNITIVEFACILITY MANAGEMENT”
Jinying Xu1, Weisheng Lu2, and Jing Wang3
1) Ph.D. Candidate, Department of Real Estate and Construction, The University of Hong Kong, Hong Kong. Email:jinyingxu@connect.hku.hk
2) Ph.D., Assoc. Prof., Department of Real Estate and Construction, The University of Hong Kong, Hong Kong. Email:wilsonlu@hku.hk3) Ph.D. Candidate, Department of Real Estate and Construction, The University of Hong Kong, Hong Kong. Email:jingww@connect.hku.hk

Abstract: In the face of current predicaments of facility management (FM), the concept of cognitive FM is proposed witha view to providing active intelligent management of a facility. In order to achieve such cognitive FM, how to integrateuser behavior data into a cognitive FM system has to be solved. This paper serves as method guidance for it by putting
forward the idea that location can serve as a gateway for the integration. Ultra-wideband (UWB) is recommended as thedevice layer to construct the 3D local positioning system for the cognitive FM system after comparison between different
local positioning technologies from the accuracy, scalability, and cost dimensions. The way to bridge the user behavior
data with facilities through coordinate transformation and location/distance computation is briefly introduced. Such of a
uniform 3D coordinate system with high accuracy and scalability for FM situation can provide a common language forcommunication and computational applications. Finally, application scenarios for various facilities such as commercial
building, office building, hospitals, warehouses, airports, and transportation stations are discussed.
Keywords: Facility management, cognitive system, data integration, user behavior, local positioning system, UWB.

31

Program and Book of Abstracts, ICCBEI 2019

BM1-1

RESEARCH ON BIM-BASED INFRASTRUCTURE PLATFORMS WITH
INTERNATIONAL STANDARDS
Katsunori Miyamoto1
1) Senior Researcher, Construction Information Research Institute, Japan Construction Information Center General Incorporated
Foundation (JACIC), Tokyo, Japan. Email: miyamotk@jacic.or.jp

Abstract: The Ministry of Land, Infrastructure, Transport, and Tourism (MLIT) released the “action plan for the overseas
development of infrastructure systems” in 2016. In consideration of this plan, we support the acquisition of theinternational standards in addition to the Japanese domestic design standards originating in global activity to promote
original Japanese construction technologies and knowhow to minimize risks for differences in design concepts between
the standards.
Therefore it is becoming increasingly important to participate in international BIM standards meetings to share
information and study the major benefits of initiating the international standards related to BIM for infrastructure. Thesebenefits enables 3D collaborative design to improve the efficiency of the construction production system throughmanaged infrastructure lifecycle innovation and facilitates communication by using a standardized format for 3D data
modeling, adding the attribute shape and materials information to enable data interoperability between each phase of the
production processes of the infrastructure systems.
In this paper, we considered a new method for solutions for civil infrastructure platforms based on theinternational standards that will maximize efficiency and productivity of public works. While watching the trends of ISO
and other international standards, we tried this new method to save time, costs, and human resources, and to improvesafety and the production process while working on its standardization. The purpose of this paper is to provide
information to introduce a BIM-based framework using the Industry Foundation Classes (IFC) model in considerationof a use case and tools from various Information and Communication Technology (ICT) at construction sites. In order
to confirm the amendment results, we applied BIM to a complex, model-related geography and geological 3D model at
the time of disaster restoration by utilizing JACIC’s complimentary Photog- CAD® and performing case studies ofinvestigations on small-scale areas and short-term lifecycles in a conceptual model.
Keywords: BIM, InfraBIM, International Standards, Product Model, Model-Based Design, Cooperative Design
BM1-2

A BIM-based AR Application for Construction Quality Inspection
Nai-Wen Chi1, Yi-Wen Chen2, Shang-Hsien Hsieh3, Jen-Yu Han4, and Lung-Mao Huang5
1) Project Assistant Professor, Department of Civil and Construction Engineering, National Taiwan University of Science andTechnology, R.O.C. Email: nwchi@mail.ntust.edu.tw2) Research and Development Engineer, Moldex3D Co., Ltd., R.O.C. Email: owen0407@gmail.com
3) Professor, Department of Civil Engineering, National Taiwan University, R.O.C. Email: shhsieh@ntu.edu.tw
4) Professor, Department of Civil Engineering, National Taiwan University, R.O.C. Email: jyhan@ntu.edu.tw
5) Assistant Vice President, Reiju Construction Co., Ltd., R.O.C. Email: ko0957@mstc.reiju.com.tw

Abstract: Quality inspection is always an important stage during construction projects. Effective quality control can help
construction projects avoid schedule delay and budget overrun. However, effective and efficient construction quality
control is always a challenging task. It not only requires experienced inspectors but also various tools such as design
drawings, tape measures and cameras to support the on-site quality inspections. In recent years, with the popularity of
portable devices, and also the maturity of Building Information Modeling (BIM) and Augmented Reality (AR), it has
become possible to integrate the two techniques on portable devices for developing an innovative construction quality
control platform. In this paper, a prototype BIM-based AR quality inspection system is proposed. It can assist inspectors
to discover the construction errors in the early stage of a construction project by comparing the on-site construction
objects (especially for the falseworks) with their corresponding elements in the BIM model. The framework and the userinterface of the prototype system are discussed and the application scenarios for improving the current quality inspection
procedure are demonstrated.
Keywords: Building Information Modeling (BIM), Augmented Reality (AR), Quality Inspection, Site Inspection

32

Program and Book of Abstracts, ICCBEI 2019

BM1-3

APPLICATION OF BIM TECHNOLOGY ON VIRTUAL MOCK-UP AND
IMPLEMENTATION FOR GENERAL CONTRACTOR IN CONSTRUCTION
Rodrigo Samuel Ortiz Chaparro *1, Yu-Cheng Lin 2
1) Master graduate student, Department of Civil Engineering, National Taipei University of Technology, No.1. Chung-Hsiao
E. Rd., Sec.3, Taipei, Taiwan. Email: rodrigo.ortizchap@gmail.com
2) Professor, Department of Civil Engineering, National Taipei University of Technology, No.1. Chung-Hsiao E. Rd., Sec.3, Taipei
Taiwan. Email: yclin@ntut.edu.tw* To whom correspondence should be addressed. E-mail: rodrigo.ortizchap@gmail.com

Abstract: Building information modeling (BIM), the visual technology that has been constantly used in architectural,engineering and construction (AEC) industry. Some of the major benefits of applying BIM includes presenting andsimulating construction operations through 3D illustration, as well as providing an advanced review for construction
management. Two dimensional CAD drawings are still widely used for construction projects. However, to avoid
misunderstanding of the design concept in projects of larger complexity, construction project teams will require morereliable and detailed information. This study proposes a BIM-based virtual mockup approach for general contractors, toenhance the performance of analysis review for construction management in construction phase of projects. The proposed
approach is then applied in the construction phase of a selected project case study to discuss the effectiveness of BIMbased virtual mockup implementation approach in practice. Finally, this study identifies and summaries the benefits,
limitations, conclusion, and suggestions for further applications.
Keywords: Building information modeling; BIM; virtual mock-up; general contractor; construction management.

BM1-4

DEEP LEARNING-BASED SCAN-TO-BIM FRAMEWORK FOR
COMPLEX MEP SCENES USING LASER SCAN DATA
Chao YIN1 & Boyu Wang1, and Jack C.P. Cheng1
1) Ph.D. Student, Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong
Kong, China. Email: cyinac@connect.ust.hk

2) Ph.D. Student, Department of Civil and Environmental Engineering, The Hong Kong University of Science andTechnology, Hong Kong, China. Email: bwangbb@connect.ust.hk
3) Ph.D., Assoc. Prof., Department of Civil and Environmental Engineering, The Hong Kong University of Science andTechnology, Hong Kong, China. Email: cejcheng@ust.hk

Abstract: Mechanical, electrical and plumbing (MEP) systems play an important role in buildings and civil infrastructure.
As laser scanning technology can capture geometric information with a high accuracy, point clouds have been widely used
to reconstruct the as-built models of MEP systems. However, due to the complexity of point clouds collected fromindustrial scenes, processing point cloud data is mostly conducted manually over a long period. In order to speed up themodeling work, this paper proposes an automated BIM model generation framework based on deep learning technique forcomplex MEP scenes, with noise and heavy occlusion. There are four main procedures in our framework: (1) semantic
segmentation: a state-of-the-art deep learning model named PointNet is adapted and leveraged to segment point clouds
into four categories; (2) instance segmentation: retrieved point clouds of different classes are further segmented into
instances with clustering methods; (3) geometrical information extraction and alignment: for pipes, an algorithm isdeveloped to extract geometric information for pipes; and (4) BIM generation: a BIM model is generated parametricallyusing Dynamo based on geometric information and alignment parameters. The proposed approach was validated using areal MEP scene. The results show that our proposed framework can satisfactorily provide an automated and robust solution
to BIM model generation for MEP scenes using laser scanning data.
Keywords: As-built BIM, SCAN-to-BIM, Point Cloud Processing, Deep Learning, MEP, Laser Scanning

33

Program and Book of Abstracts, ICCBEI 2019

BM2-1

Conversation-based Building Information Delivery System for Facility Management
Kuan-Lin Chen1, Meng-Han Tsai2
1) Graduate Student, Department of Civil and Construction Engineering, National Taiwan University of Science and Technology,
Taiwan. Email: m10705504@mail.ntust.edu.tw
2) Assistant Professor, Department of Civil and Construction Engineering, National Taiwan University of Science and Technology,
Taiwan. Email: menghan@mail.ntust.edu.tw

Abstract: This research aims to develop a conversation-based building information delivery system as a bridge between
equipment maintenance engineers and facility information management platform. At present, most of the new buildings
using BIM technology are handed over the managing system to the property management companies. On-site equipment
maintenance engineers obtain building model information through these management platforms or emails. However, for anengineer who is on site to repair a particular piece of equipment, there is too much unnecessary model information in thesystem and it may cause their work to be inefficient. With the development of IT technology, the conversation-based
system is more flexible and has been gradually applied in various engineering fields. We developed a conversation-based
system through natural language processing (NLP). By collecting and training the query keywords that equipment
maintenance engineers often use, this conversation- based system can quickly understand the user's query intent. At thesame time, this method integrates various tools for transmitting building information, and equipment maintenanceengineers can complete the receiving and querying equipment models in the same interface. In order to verify theeffectiveness of this method, we tested several devices in a residential building to analyze the benefits of importing
conversation-based system during the FM phase. The results demonstrated that the conversation-based system cancorrectly identify statements for different sentences but with the same intent and this method can improve the efficiency ofequipment maintenance engineers to retrieve building model information.
Keywords: Building Information Modeling, Facility management, Conversation-based system, Natural language
processing
BM2-2

DEVELOPMENT OF A NEW DISTRICT IN THE STATE OF HESSEN “FLEXQUARTIER”
PROJECT
Jose Alberto Lagunes Ronzon1, Moritz Hofmann2, Milena Potpara3, Dirk Metzger4 and Joaquin Diaz5
1) Master student, Department of Architecture and Civil Engineering, Technische Hochschule Mittelhessen, Giessen, Germany. Email:jose.lagunes.ronzon@bau.thm.de2) Master student, Department of Architecture and Civil Engineering, Technische Hochschule Mittelhessen, Giessen, Germany. Email:moritz.fabio.hofmann@bau.thm.de3) Ph. D. student, Department of Architecture and Civil Engineering, Technische Hochschule Mittelhessen, Giessen, Germany. Email:milena.potpara@bau.thm.de4) Professor, Department of Architecture and Civil Engineering, Technische Hochschule Mittelhessen, Giessen, Germany. Email:dirk.jens.dieter.metzger@bau.thm.de5) Ph. D. Professor, Department of Architecture and Civil Engineering, Technische Hochschule Mittelhessen, Giessen, Germany.
Email: joaquin.diaz@bau.thm.de

Abstract: A new district is planned to be built in Hessen, a state in Germany. This new district is called “FlexQuartier”
and it is intended to include residential units and other kinds of floor uses. It is a goal of the Government of Germany todevelop new districts with characteristics based on smart city and sustainability principles. The main technology in thisproject is an innovative High-Temperature Storage System in combination with a battery storage and a water tank storing
hot water, this combined with the use of a Quartier Information Model (QIM). This papers explains the steps that are
being followed in the beginning of the project (conception phase) and also the steps that will be followed in order tocreate a model that builds upon itself and can store not only information about the district, but also can help in the design,
construction, commissioning and management phases of the project.
Keywords: FlexQuartier, Smart Cities, BIM, QIM, High-Temperature Storage, Interoperability, Sensors, Energy, Facility
management.

34

Program and Book of Abstracts, ICCBEI 2019

BM2-3

PROCESS RE-ENGINEERING IN OWNER ORGANIZATIONS TO IMPROVE BIMBASED PROJECT DELIVERY USING REQUIREMENTS MANAGEMENT PLATFORM
Ali Motamedi1, Sylvain Vaudou2, Romain Leygonie3, Daniel Forgues4
1) Ph.D., Assoc. Prof., Department of Construction Engineering, École de technologie supérieure, Montreal, Canada. Email:ali.motamedi@etsmtl.ca2) BIM Director, CAP INGELEC., Bordeaux, France. Email: sylvainvaudou@hotmail.com
3) M.A.Sc. Candidate, Department of Construction Engineering, École de technologie supérieure, Montreal, Canada. Email:romain.leygonie.1@ens.etsmtl.ca4) Ph.D., Prof., Department of Construction Engineering, École de technologie supérieure, Montreal, Canada. Email:daniel.forgues@etsmtl.ca

Abstract: BIM-assisted project execution methods are being increasingly adopted by designers and contractors due toclient demand and the efficiency gains they provide. However, many owner organizations do not take full advantage of
BIM in assessing the quality of deliverables, and do not use digital deliverables during the operation phase. Additionally,
although many owner organizations have BIM implementation plans, their design review and data handover processes still
follow conventional methods due to a lack of BIM knowledge related to facilities management. Requirements related to
Facility Management (FM) operations are usually transferred using traditional methods, and requirement elicitation andmanagement processes often do not consider the BIM potential (such as information provision, automatic data transfer,data quality assurance and control). In this research, the operation of a major provincial government owner organization in
Canada, which is one of the pioneers in adopting BIM-based project execution, is analyzed in an observational study toidentify process gaps when it comes to benefiting from BIM during the lifecycle. The study showed that although many
BIM-based processes are adopted for projects, many core processes on the owner side (such as gathering andcommunication of FM requirement, data quality control and non-geometric data handover) still follow traditional methods.
Using extensive data gathering and use case analysis, process gaps were identified and process re-engineering
recommendations prepared. Additionally, the use of a requirements management system is proposed and verified to tackle
issues related to requirement documentation and tracing, knowledge preservation, data handover, and data quality
assurance and control.
Keywords: BIM, Requirements management, Quality assurance, Facilities management, Process re-engineering
BM2-4

A Framework for Visual BIM-based Maintenance Management in MRT Stations
Yi-Shian Huang 1, Yu-Cheng Lin2
1) Master graduate student, Department of Civil Engineering, National Taipei University of Technology, No.1. Chung-Hsiao
E. Rd., Sec.3, Taipei, Taiwan. Email: mh70804@gmail.com
2) Professor, Department of Civil Engineering, National Taipei University of Technology, No.1. Chung-Hsiao E. Rd., Sec.3, Taipei
Taiwan. Email: yclinntut@gmail.com

Abstract: The long-term operation of MRT station facilities will cause wear and tear. How to improve the maintenanceand management is an important issue in MRT station facilities management. In order to improve the efficiency of MRT
station facility maintenance and management, this study use the building information model (BIM) visualization
technology to discuss the facility management. Although there are many previous studies focused on applications of BIMbased MM works, few studies are focus on the implementation models for BIM-based visual BIM-based maintenancemanagement in MRT Stations. Therefore, the study proposes the framework for visual BIM-based maintenancemanagement special for MRT station in Taiwan. The proposed framework was applied in a selected MRT station in
Taiwan for case study to verify our proposed framework and to demonstrate the effectiveness. Finally, the study identifies
the benefits, limitations, and suggestions for further applications.
Keywords: Building Information Modeling (BIM), Maintenance Management, MRT Station, Operation Phase

35

Program and Book of Abstracts, ICCBEI 2019

BM2-5

MODELING THE LAST-MILE PROBLEM OF BIM ADOPTION
Jing Wang1, Weisheng Lu2, and Jinying Xu3
1) Ph.D. Candidate, Department of Real Estate and Construction, the University of Hong Kong, Hong Kong. Email:jingww@connect.hku.hk
2) Associate Professor, Department of Real Estate and Construction, the University of Hong Kong, Hong Kong. Email:wilsonlu@connect.hku.hk3) Ph.D. Candidate, Department of Real Estate and Construction, the University of Hong Kong, Hong Kong. Email:jinyingxu@connect.hku.hk

Abstract: In recent years, the high expectation of Building Information Modeling (BIM) has increasingly attracted theattention of organizations in developing countries. To catch up with the leading BIM practice, those ‘late mover’
organizations tend to benchmark and adopt BIM practices that have been proven effective by global leaders. However, theuptake of BIM use is largely stuck by the “last-mile problem”. While developers diffusing their standardized or
generalized solutions to global users, organizations often find it difficult to adopt such solutions due to the contextual
difference between such standardized and generalized BIM solutions and their use environments. This paper aims tofirstly define the “last-mile” problem in BIM adoption and then, propose a conceptual model of such problem. In thispaper, the last-mile BIM adoption is defined as “a decentralized process involving the linear diffusion of BIM solutions
from its source developers to destination users”. Synchronizing literature on BIM and last-mile problems in various
domains, a last-mile BIM adoption model is proposed by identifying the model components and developing a design
framework. This study has both academic and practical implications. It offers a set of formal language to systematicallydescribe the last-mile problem of BIM adoption, leading to an improved understanding of the last-mile process andproblems therein. For practitioners, the study facilitates them to analyze last-mile problems and develop strategies
accordingly.
Keywords: Building Information Modeling (BIM), last mile, model, adoption, diffusion
BM3-1

BIM-BASED WALL FRAMING CALCULATION ALGORITHMS FOR DETAILEDQUANTITY TAKEOFF
Chavanont Khosakitchalert1, Nobuyoshi Yabuki2, and Tomohiro Fukuda3
1) Ph.D. Candidate, Division of Sustainable Energy and Environmental Engineering, Graduate School of Engineering, Osaka
University, Japan. Email: khosakitchalert@it.see.eng.osaka-u.ac.jp
2) Ph.D., Prof., Division of Sustainable Energy and Environmental Engineering, Graduate School of Engineering, Osaka University,
Japan. Email: yabuki@see.eng.osaka-u.ac.jp
3) Ph.D., Assoc. Prof., Division of Sustainable Energy and Environmental Engineering, Graduate School of Engineering, Osaka
University, Japan. Email: fukuda@see.eng.osaka-u.ac.jp

Abstract: Although an automated quantity takeoff using building information modeling (BIM) is proved to be faster andmore reliable than the traditional quantity takeoff method, the information and geometries in a BIM model must be input
correctly. Drywall is a wall type that consists of wall framings as a core structure layer and drywall sheets as finish layers.
During a tendering phase, the area of each layer of drywall is used for cost estimation. However, during a construction
phase, the material quantity of wall framings must be calculated in length in order to purchase the materials effectively. If
the wall framings do not exist in the BIM model, construction practitioners have to create them or calculate their lengthmanually. Creating wall framing elements in a BIM model is a time-consuming and error-prone task, especially in a large
scale project. The increased geometries in a BIM model also affect the working performance of the software. This research
proposes a method that automatically calculates the lengths of vertical and horizontal members of wall framings from theextracted wall surfaces and the input spacing values. The method also eliminates the region of walls that overlap withstructural elements such as columns and beams. The validation is done by using an interior construction project as a casestudy. It showed that the proposed method provides an accurate wall framing quantity when compared with the quantity
results from the BIM model that has wall framings and the quantity results from the manual calculation methods. With thismethod, the wall framing elements do not need to be created in a BIM model for quantity takeoff. The modeling time canbe saved while construction practitioners can get an accurate wall framing quantity for purchasing material during a
construction phase.
Keywords: Building Information Modeling (BIM), Quantity takeoff, BIM-based quantity takeoff, Wall framing36

Program and Book of Abstracts, ICCBEI 2019

BM3-2

BIM-SUPPORTED COMPLIANCE VERIFICATION OF PERFORMANCE-BASEDCAR-PARK VENTILATION DESIGN
Johannes Dimyadi1, Robert Amor2
1) PhD, CEO, Compliance Audit Systems Limited, Auckland, New Zealand. Email: jdimyadi@complianceauditsystems.com
2) PhD, Prof., School of Computer Science, University of Auckland, Auckland, New Zealand. Email: trebor@cs.auckland.ac.nz

Abstract: Modern regulatory frameworks, such as those enforceable in the UK, Australia, and New Zealand, allow car-parkventilation systems to be designed to comply with performance-based objectives. This has provided designers with theopportunity to propose an alternative solution when prescriptive requirements are either too restrictive or costly to
implement. The input data required for computations or numerical simulations to support the performance-based design isoften complex and may include the geometry, building usage or activities and building system characteristics, as well as
normative compliant-design parameters. Conventionally, this input data is gathered manually from paper-based drawings
and other written documentation including normative standards, which is an inefficient and error-prone process. In thispaper, we investigate to what extent can simulation input data be generated from the available information shared throughthe Building Information Modelling (BIM) collaborative process. Additionally, we explore an open standard computable
representation of normative requirements that can be used to automate some of the preparatory computations to further
complement the simulation input data. An exemplary use case is also described to illustrate the approach.
Keywords: BIM, CO, CFD, car-park ventilation, performance-based design.

BM3-3

The Study of Automatic CIM Models Development for Infrastructure Projects
Tzu-Tin Huang1 and Yu-Cheng Lin2
1) Graduate Student, Department of Civil Engineering, National Taipei University of Technology, Taipei, Taiwan. Email:wchwch8899@gmail.com
2) Professor, Department of Civil Engineering, National Taipei University of Technology, Taipei, Taiwan. Email:yclinntut@gmail.com

Abstract: Building Information Modeling (BIM) has been widely used in civil engineering and construction industry. Its
technology has effectively reduced many mistakes of this huge industry and reduced the cost of construction projects. It
has established industrial trends for countries all over the world. However, Civil Information Modeling (CIM), is thelatest concept in the construction engineering, its application in the is slowly becoming more present in the constructionindustry. The field of civil engineering construction is relatively large, and the work content in the design and planningstage is highly variable, especially when the model is being constantly updated on the constrcution phase of the project. In
this stage CIM engineer encounters many complicated and cumbersome operations and integration of information
problem are detected. If complicated projects are built with the limitations of the software itself, improving work efficiency
will become a more difficult task. Recently, visualization program design for the application of engineering has gradually
become a trend. Visual programming tools can assist the CIM model designs by providing improvement in the solutionsof problems encountered in the original construction method. Therefore, this study uses the Autodesk Revit platform
combined with Dynamo as a research tool to write programs, import into case application, and study how these two
softwares simplify the repetitive work when designing projects. Finally, the research demonstrates the application of the
proposed tool into a case of the North Road model guardrail for the design and development of a model with support ofautomatic generation of elements. With the successful development and implementation of the automation program, thisproject was able effectively shorten designing and construction time even thought the complexity of the project, reduce
human errors and omission. Lastly, this paper will present the discussion of the main benefits, difficulties and limitations
by case study as a reference for follow-up research and application will be introduced.
Keywords: Civil Information Modeling, CIM, Automation, Visual Programming, Dynamo.

37

Program and Book of Abstracts, ICCBEI 2019

BM3-4

AN AUTOMATED BIM-INTEGRATED SYSTEM FOR CHANGE ORDER COST
IMPACT EVALUATION
Veerasak Likhitruangsilp1, Tantri N. Handayani2, Nobuyoshi Yabuki3, Photios G. Ioannou4
1) Ph.D., Assoc. Prof., Department of Civil Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand.
Email: Veerasak.L@chula.ac.th2) Ph.D., Department of Civil and Environmental Engineering, Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta,
Indonesia. Email: tantri.n.h@ugm.ac.id3) Ph.D., Prof., Division of Sustainable Energy and Environmental Engineering, Osaka University, Osaka, Japan. Email:yabuki@see.eng.osaka-u.ac.jp
4) Ph.D., Prof., Department of Civil and Environmental Engineering, University of Michgian, Ann Arbor, USA. Email:photios@umich.edu

Abstract: Change orders are inevitable in construction projects and usually have a major impact on project costs.
Evaluating change order impacts by using conventional 2D drawings often leads to the inaccurate estimated quantity ofmodified works, which subsequently yields unreliable impact costs. Building information modeling (BIM) can address
such challenges because it facilitates automated quantity takeoff and cost estimating, integrating relevant information, andvisualization. Yet, implementing BIM for this purpose requires a well-defined methodology and a well-organized
information structure. This paper develops an automated system for evaluating the cost impact of a construction changeorder. The system analyzes the modified building elements using the model checker and estimates direct and indirect
costs of such change order (e.g., demolition and relocation costs). Since the proposed system performs a thorough cost
impact analysis with minimal subjectivity, the results are accurate and reliable for all project participants. In addition, thesystem is equipped with a recording system for tracking the dynamic changing of project costs throughout theconstruction phase. The system is applied to an actual high-rise building project to illustrate its capability and practicality.
Keywords: Building information modeling (BIM), change order, variation order, automated cost evaluation, cost impact,
claim management
BM4-1

SIMULATION AND OPTIMIZATION OF UTILITY TUNNELS CONSTRUCTION AS
LINEAR PROJECTS
Mohamed A. Sherif 1, Abdelhamid Abdallah 2, and Khaled Nasser 3
1) MSc Candidate, Department of Construction Engineering, The American University in Cairo, Fifth Settlement, Egypt. Email:mohamed_ayman_sherif@aucegypt.edu
2) Teaching Assistant, Department of Architectural Engineering, Helwan University, Cairo, Egypt. Email:abdelhamid.abdullah@aucegypt.edu
3) Ph.D., Assoc. Prof., Department of Construction Engineering, The American University in Cairo, Fifth Settlement, Egypt. Email:knassar@aucegypt.edu

Abstract: The utility tunnels are major features in several projects on different scales ranges from different sizes ofcampuses like university and hospital campuses to large scale utility tunnels used in mega residential projects and airports.
They are usually the housing space for different utilities required for the projects that are on multi- building scale. The
simulation of the construction of utility tunneling hasn’t received enough attention in research while tunneling in general
has been studied significantly. The scheduling and planning of utility tunnels as an example of linear projects are facing
big challenges of optimizing the project duration, work balance and utilization of the available resources. Linear Projects
consist of several similar elements with repeated activities from one element to the other. This paper will propose adiscrete event simulation model to plan the construction sequence of utility tunnels with optimum duration and resources.
It also represents a case study as an example for a utility tunnel construction in Egypt.
Keywords: Utility, tunnels, Scheduling, Planning, Linear Projects, Simulation, Modeling, Optimization, Construction,
Management.

38

Program and Book of Abstracts, ICCBEI 2019

BM4-2

INTEGRATING BIM INTO GREEN RESIDENTIAL BUILDING ASSESSMENT: A CASE
STUDY
Fatma Abdelaal1, Brian Guo2, Yang Zou3, and Mazharuddin Syed Ahmed41) Ph.D. Candidate, University of Canterbury, Christchurch, New Zealand. fatma.abdelaal@pg.canterbury.ac.nz
2) Ph.D., Lecturer, University of Canterbury, Christchurch, New Zealand. brian.guo@canterbury.ac.nz
3) Ph.D., Lecturer, University of Auckland, Auckland, New Zealand. yang.zou@auckland.ac.nz
4) Ph.D., Ara Institute of Canterbury, Christchurch, Canterbury, New Zealand. mazharuddin.syedahmed@ara.ac.nz

Abstract: Building Information Modeling (BIM) technology provides numerous benefits for green building design andassessment. Recent years have seen attempts to integrate BIM into the commercial and industrial building assessment
process. However, research on BIM applications to green residential buildings is limited. Thus, this research aims atinvestigating the potential of integrating BIM into green residential building rating systems such as Homestar, the green
residential assessment system in New Zealand. First, the required data and information to calculate Homestar points has
been identified by reviewing the Homestar v4 technical manual, in order to determine the proportion of the design rating
points that can be calculated based on BIM functions. Second, the required data were matched against the data available ina BIM model of a case study of a residential building, the building is the first 10 Homestar rating house in Christchurch,
New Zealand. The results reveal that 76 of 120 points of Homestar rating credits can be achieved with BIM software, with
100% computable for Density and Resources Efficiency, 67% for Energy, 21% for Water, %17 for Waste, 33% forManagement, 100% for Materials, and 67% for Site. Future efforts can be made to develop a fully automated BIM-based
green residential buildings assessment framework that can help designers optimize the design and assist the assessors withthe rating process. Such a BIM-based assessment framework has a significant potential to simplify the rating process andreduce assessment costs.
Keywords: Building Information Modeling (BIM), Green Building Assessment, Residential Buildings, Homestar, New
Zealand, Sustainability.
BM4-3

ENHANCED UNDERGROUND UTILITIES MANAGEMENT INTEGRATED CIM
TECHNOLOGIES
Sheng-Lun Zhuo*1, Yu-Cheng Lin2
1) Master graduate student, Department of Civil Engineering, National Taipei University of Technology, No.1. Chung-Hsiao
E. Rd., Sec.3, Taipei, Taiwan. Email: z0933957902@gmail.com
2) Professor, Department of Civil Engineering, National Taipei University of Technology, No.1. Chung-Hsiao E. Rd., Sec.3, Taipei
Taiwan. Email: yclinntut@gmail.com

Abstract: Civil Information Modeling (CIM) is commonly used in civil engineering projects, such as tunnels, bridges,
roads, underground pipelines. CIM can provide a better understanding of engineering problems and onsite status throughthe visual advantages. The CIM model can present a parameter-based visual effect that once established can effectively
achieve communication and coordination. Over the years many adjustments have been made in the existing infrastructureof the pipelines in addition to the new pipelines systems that have been switched. Sometimes, due to an error in theunderground pipeline drawings or specifications, unnecessary disasters may occur this would occur because there is not aperiodic update in the 2D drawings. In some cases, after the pipeline location is excavated, underground utilities in service
could be affected since they were traditionally designed with 2D drawings. If the original pipeline is found during
construction or maintenance, 2D drawings will probably show a change or addition, therefore, it will be a difficult task forthe construction company to update or verify the precision of the available maps according to the actual situation on site.
There are also cases where the current or new pipeline location is not shown or specified in the as-built drawings, making
more difficult dinging or other related operations, miscalculation in the construction site for excavation can cause
thousands of dollars of over cost and would affect thousands if the drinking water or electricity distribution is affected.
This study will use CIM in underground pipeline management applications by building, planning and researching about
the processes and standards taken for the underground pipeline models. It is expected that CIM will enable field personnel
and construction personnel to keep clear visualization of the underground soil conditions. And explore the benefits,difficulties and restrictions of building a CIM model for underground utilities. Finally, through the 3D model forcommunication coordination and inspection, and using 3D models and virtual space, through 3D visualization to present
pipeline conflicts, review the spatial and spatial needs of facilities and buildings, and analyze the models, and achievecommunication between members. Coordinate and integrate the effectiveness of collaboration.
Keywords: Building Information Modeling (BIM), Civil Information Modeling (CIM), Underground Utilities,
Underground Pipeline Maintenance.
39

Program and Book of Abstracts, ICCBEI 2019

BM4-4

DEVELOPING EFFICIENT MECHANISMS FOR BIM MODEL SIMPLIFICATIONJack C. P. CHENG1, Keyu CHEN2, Weiwei CHEN3,
1) Associate Professor, Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology,
Hong Kong. E-mail: cejcheng@ust.hk
2) Ph.D. Student, Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, HongKong. E-mail: kchenal@connect.ust.hk
3) Ph.D. Student, Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, HongKong. E-mail: wchenau@connect.ust.hk

Abstract: Building information modeling (BIM), which can provide both geometric and semantic information for users tovisualize and interact with each building component, is attracting increasing attention in the architecture, engineering,
construction and operations (AECO) industry nowadays. However, complicated and huge BIM models can increase thetime for model transfer, increase the computation work load while rendering, and reduce the fluency during visualizationand interaction. Therefore, this paper aims to develop efficient mechanisms for BIM model simplification to better utilize
large BIM models. This paper mainly focuses on two types of components: walls and cylindrical components. Walls thatare connected to each other have a large number of redundant polygons, thus an algorithm is proposed to minimize thenumber of polygons without altering the walls. Cylindrical components, which have a large amount of redundant polygons
on the side surfaces, can be simplified by removing all redundant polygons. Illustrative examples that evaluates theperformance of these developed mechanisms are also provided.
Keywords: AR/VR; BIM; Model simplification; Polygon reduction
CME-1

EVALUATION OF PILE PERFORMANCE IN DIFFERENT LAYERS OF SOIL
INVESTIGATING PILE BEHAVIOR BY OPENSEESPL
Orod Zarrin1, Mohsen Ramezanshirazi2
1) Centre for Infrastructure Performance and Reliability, The University of Newcastle, Callaghan, NSW 2308 (Australia)
2) PhD Candidate, Sapienza University of Rome, Italy, Mohsen Ramezanshirazi, mohsen.ramezanshirazi@uniroma1.it

Abstract: Pile foundations technique is developed to support structures and buildings on soft soil. The mostimportant dynamic load that can affect the pile structure is earthquake excitation. From the 1960s, the comprehensive
investigation of pile foundations during earthquake excitation indicate that piles are subject to damage by affecting thesuperstructure integrity and serviceability.
The main part of researches has been focused on the behavior of liquefiable soil and lateral spreading load on piles.
During an earthquake, two types of stresses can damage the pile head. Inertial load that is due to superstructure anddeformation that is caused by surrounding soil. Inertial load and soil deformation are associated with the acceleration
developed in an earthquake. The acceleration amplitude at the ground surface depends on the magnitude of earthquakes,
soil properties and seismic source distance. According to the investigation, the damage is between the liquefiable andnon-liquefiable layers and also soft and stiff layers. This damage crushes the pile head by increasing the inertial load,
which is applied by the superstructure. On the other hand, the cracks on the piles due to the surrounding soil are directly
related to the soil profile.
In this study, the performance and behavior of pile foundations during different earthquakes are investigated. This
investigation has done by OpeenSeesPL in three different layers of soil that contain liquefiable and non-liquefiable layers.
Keywords: Pile, Earthquake, Liquefaction, Non-Liquefiable, Damage.

40

Program and Book of Abstracts, ICCBEI 2019

CME-2

DEVELOPMENT OF STATIC AND DYNAMIC MODELING APPROACHES USINGFRAME MODELS FOR CITY SEISMIC RESPONSE ANALYSIS
Pher Errol B. Quinay1, Aileen Rachelle Fader2, Franz Marius Carangan3
1) Dr. Eng., Assoc. Prof., Institute of Civil Engineering, University of the Philippines Diliman, Quezon City, Philippines. Email:pbquinay2@up.edu.ph2) Quantity Surveyor-Technical TeaAM, Wallcrete Company, Inc., Quezon City, Philippines, Email: aileenrachellef.wci@gmail.com
3) Junior Structural Engineer, Al Abbar Aluminum Philippines, Inc., Pasig City, Philippines, Email: FranzC@alabbargroup.com

Abstract: Methods that can estimate the city response to seismic events are valuable tools that can assist in disaster risk
reduction efforts. With the increasing availability of large computing resources, physics-based approaches that can be used
for this purpose are becoming more practicable. This study aims to develop static and dynamic modeling approaches forcity seismic response analysis. For both modeling approaches, tools were developed to generate and analyze models thatare suitable to the available GIS and BIM data. To check the accuracy of the developed tools, validation tests wereconducted by comparing with commercial software that is commonly used in structural analysis and design in thePhilippines. Validations for static and dynamic analysis show that the results of the developed tools are within 6% and 8%of the results that were computed using a commercial software, respectively. These results are considered acceptable given
the low computation cost per building in the developed approaches. As a demonstrative example, two cities in Metro
Manila were considered for scenario earthquake analysis. Low to midrise reinforced concrete structures were analyzed
and floor displacements were computed. From these results, maximum responses were obtained and visualized in citylevel. Another example was conducted with the aim to compare the computed period of vibration with that of a previous
study that performed experiment on a three-story building in Metro Manila. Results show that for the considered standard
model of the building, the periods of vibration can be closely estimated by the developed tool.
Keywords: City seismic response analysis, finite element method, static and dynamic analysis
CME-3

Structural Shape Grammars used in Intelligent Generation Design of Discrete Structures
Xianzhong Zhao1, Ruifeng Luo 2
1) Ph.D., Prof., College of Civil Engineering, Tongji University, Shanghai 200092, China. Email: x.zhao@tongji.edu.cn.
2) Ph.D. Candidate, College of Civil Engineering, Tongji University, Shanghai 200092, China. Email: lrf@tongji.edu.cn

Abstract: The intelligent construction industry involves three aspects: intelligent generation design, intelligent
fabrication, and intelligent operation and service. A conceptual and intelligent generation design method of discrete
structures was introduced. The method, based on the computational synthesis, is capable of generating an optimal
structure from all alternative ones at the concept design stage to meet the optimization objectives and constraints. This
generation method contains three parts: structural shape grammars, structural evaluation, and structural optimization
algorithm. Structural shape grammars in this method can generate, optimize and transform discrete structural shapes
using geometric topology within the design domain. The characters of structural shape grammars were obtained throughexisting shape grammars. An innovational tetrahedral shape grammar was presented aiming to improve the adaptability ofstructural shape grammar in spatial issues. Through classifying the topological relations of five points in space, thetetrahedral shape grammar determines not only the topological transformation rules but also the nodes adding anddeletion rules of discrete structure. Besides the topological transformation method, this tetrahedral shape grammar also
takes the shape transformation and size transformation into comprehensive consideration. Besides, prospective
applications of intelligent generation design method were put forward.
Keywords: intelligent generation design method, spatial shape grammar, tetrahedron topology.

41

Program and Book of Abstracts, ICCBEI 2019

CME-4

Numerical Evaluation of Seismic Response of Anchorage Foundation installed in
Switchboard Cabinet
Sang-Moon Lee1, Ga-Ram Kim2, Woo-Young Jung3
1) Ph.D. Candidate, Department of Civil Engineering, Gangneung-Wonju University, Gangneung-si, Gangwon-do, South Korea.
Email: idealmoon@naver.com
2) Master Student, Department of Civil Engineering, Gangneung-Wonju University, Gangneung-si, Gangwon-do, South Korea. Email:kgr3288@naver.com
3) Professor, Department of Civil Engineering, Gangneung-Wonju University, Gangneung-si, Gangwon-do, South Korea. Email:woojung@gwnu.ac.kr

Abstract: In this study, the seismic response of anchor bolt for freestanding equipment, such as switchboard cabinets, atthe hydroelectric power plant was presented based on the results of numerical simulations. From the experimental study,
shaking table tests were performed to investigate the overall structural behavior of switchboard cabinets and seismicinduced damages including a rocking problem that leads to the deformation occurred at the cabinet bottom were observed
during the test. The FE modeling was conducted by using the ABAQUS similar to an actual cabinet panel and 3D dynamic
nonlinear analysis was performed using seismic loadings like long-period earthquakes. For validating the proposed FE
model, the maximum displacement and the mode shapes were used in the comparison of numerical analysis results and areasonable agreement was made when seeing in the maximum displacement of the switchboard cabinets. From the analysis,a slight difference was found in the analysis due to the rocking problem which causes cup-like deformation at the bottom of
the cabinet during the tests. Finally, using the validated numerical model, the effects of long period earthquake wave on
cabinet behavior was analyzed. The Von-Mises stress at the anchor bolt embedded in concrete foundation occurred 1.068
MPa and the horizontal maximum displacement of the cabinet was 24.8 cm. From the basis of this research, there isneeded to compare interrelation between nonstructural components such as a cabinet and the seismic waves which havevarious period in the future research.
Keywords: Switchboard Cabinet, Shaking Table Test, Seismic Waves, Nonstructural Components
IOT-1

FRAMEWORK FOR A BIM-BASED REAL-TIME EVACUATION GUIDANCESYSTEM IN SMART BUILDINGS
Kayla Manuel1, Nobuyoshi Yabuki2, and Tomohiro Fukuda3
1) Master Course Student, Division of Sustainable Energy and Environmental Engineering, Osaka University, Japan. E-mail:manuel@it.see.eng.osaka-u.ac.jp
2) Ph.D., Prof., Division of Sustainable Energy and Environmental Engineering, Osaka University, Japan. E-mail:yabuki@see.eng.osaka-u.ac.jp
3) Ph.D., Assoc. Prof., Division of Sustainable Energy and Environmental Engineering, Osaka University, Japan.
E-mail: fukuda@see.eng.osaka-u.ac.jp
Abstract: In emergency situations, such as a fire, mass panic can result in many unnecessary deaths. Some deaths are caused not
as a result of the fire, but due to the herds of people seeking egress. If alternative exits were made known to those seeking
egress, congestion at prominent exits could be alleviated and unnecessary deaths prevented. Current two-dimensional
evacuation signs in buildings show a single means of escape and are insufficient because they are static and relying on them for
information is inconvenient in a time-sensitive situation. A Building Information Modeling (BIM) model is a semantically richthree-dimensional representation of a building with geometric and semantic data. Integration of this built environment
information and Internet of Things (IoT), termed SMART buildings, are commonly used for operation and maintenancepurposes. The proposed system integrates BIM and IoT to create an evacuation guidance system to assist users in building egress.
The proposed system continuously monitors the current fire situation, the building and its’ occupant in order to provide realtime customized instruction from each user’s respective location/s to safety. Moreover, should their initial path of escape be
obstructed by dynamic events, such as obstructions caused by an escalated fire or inoperative doors, the pre-simulated paths
would suggest an alternative route that an egress-seeker should take. Because visibility is low, due to smoke density, egress
instruction is given as voice commands to customized wireless earphones so that users can be hands-free to crawl, should theneed arise. The system goes through a database of evacuation paths and based on proximity and other factors the evacuation
instruction is relayed. The proposed system relies heavily upon knowing where occupants are in the building at all times inorder to immediately instruct them from their respective initial positions to a designated exit.
Keywords: Building Information Modeling (BIM), Egress, Dynamic Real-time navigation, Indoor Localization, Smart
Buildings, Internet of Things (IoT).

42

Program and Book of Abstracts, ICCBEI 2019

IOT-2

DEVELOPMENT OF A METHOD TO DETECT EARTHQUAKE-RELATED CHANGESIN IMAGES TAKEN BY CCTV CAMERAS SURVEYING CIVIL INFRASTRUCTURE
Arata Konno1, Hirotaka Sekiya2, and Hideyuki Ashiya3
1) Head, Disaster Prevention and Relief Division, Okayama River Management Office, Chugoku Regional Development Bureau,
Ministry of Land, Infrastructure, Transport and Tourism, Japan. Email: konno-a85aa@mlit.go.jp
2) Ph.D., Head, Information Platform Division, Research Center for Infrastructure Management, National Institute for Land andInfrastructure Management, Ministry of Land, Infrastructure, Transport and Tourism, Japan. Email: sekiya-h92tb@mlit.go.jp
3) Director for Information Engineering Affairs, Electricity and Telecommunication Office, Engineering Affairs Division, Minister’s
Secretariat, Ministry of Land, Infrastructure, Transport and Tourism, Japan. Email: ashiya-h82ac@mlit.go.jp

Abstract: Following an earthquake, the government’s disaster management bureau immediately seeks to clarify the
degree of damage to infrastructure. Closed Circuit Television (CCTV) cameras have been deployed and utilized to survey
infrastructure on roads and rivers. Use of an automated system to select CCTV cameras in municipal areas where seismic
activity has exceeded a preset level (set by the Japan Meteorological Agency) was studied. This system is equipped toobtain images taken by some testing CCTV cameras at regular times to compare images pre- and post-earthquake.
In this paper, we validated a method of detecting regions of change caused by earthquakes using three steps. First,
we rendered non-photorealistic images as anomalous by drawing artificial damage after the earthquake. For example,
falling objects can be captured by CCTV cameras surveying roads. Second, we validated an optimal number of images so
as to remove moving objects such as cars and waving trees. We used the median value of each pixel in the images. Third,
we validated algorithms containing parameters to adjust image sensitivity. Accounting for daylight changes, we used ajoint intensity histogram of an anomalous image and a normal image. The joint intensity histogram was a twodimensional combined intensity for the same pixel between anomalous and normal images. We regarded changes outside
the constant multiple of the standard deviation of the joint intensity histogram as legitimate.
Using several filters, we removed moving objects with five images for four camera images. Under this condition,
it was optimal to regard 10 times the standard deviation as artificial damage for 18 CCTV cameras. We are trying todetect a variety of changes more robustly for more CCTV cameras.
Keywords: support of the early stage after earthquake, Closed Circuit Television, image change detection
IOT-3

A HUMAN-FOLLOWING ROBOT FOR ASSISTING TUNNEL INSPECTORS
Chia-Hsing Ho1 and Yo-Ming Hsieh2
1) Engineer, Turing Drive Inc., Taipei City, Taiwan, Email: chiahsing@turing-drive.com
2) Associate Professor, Department of Civil and Construction Engineering, National Taiwan University of Science and Technology,
Taipei City, Taiwan, Email: ymhsieh@mail.ntust.edu.tw

Abstract: Tunnels require regular inspections to maintain their safety. Tunnel inspectors have modern tools such as
smartphones and tablets to help them record observations via picture-taking, voice-recording, hand-writing, and text-typing.
However, there is a lack of automated ways to obtain localization information inside tunnels. In this work, a personfollowing robot is developed for assisting tunnel inspectors by providing localization information inside tunnels. The
robot contains four essential ingredients: person-detection, self-driving, localization, and communication with smart
devices. This paper presents these ingredients and their integration. The developed robot was field tested inside buildings
and pedestrian tunnels with success and issues. These results and issues are also presented in this paper.
Keywords: localization, person following, robot, tunnel inspection

43

Program and Book of Abstracts, ICCBEI 2019

IOT-4

A BUILDING STRUCTURAL HEALTH MANAGEMENT SYSTEM BY BIM AND IoT
COLLABORATION
Narito Kurata1, Kenro Aihara2, Takahiro Konishi3, Hirofumi Yamaoka4, and Shinichi Kondo5
1) Ph.D., Prof., Faculty of Industrial Technology, Tsukuba University of Technology, Tsukuba-City, Ibaraki, Japan. Email:kurata@home.email.ne.jp
2) Ph.D., Assoc. Prof., Digital Content and Media Sciences Research Division, National Institute of Informatics, Chiyoda-ku, Tokyo,
Japan. Email: kenro.aihara@nii.ac.jp
3) Corporate Officer, General Manager, Business Strategy Division, Applied Technology Co., Ltd., Kita-ku, Osaka, Japan. Email: takonishi@apptec.co.jp
4) IT Consultant, Business Strategy Division, Applied Technology Co., Ltd., Kita-ku, Osaka, Japan. Email: yamaoka@apptec.co.jp
5) BIM Consultant, Business Strategy Division, Applied Technology Co., Ltd., Kita-ku, Osaka, Japan. Email: shkondo@apptec.co.jp

Abstract: The authors have developed an autonomous time-synchronization sensing system that holds high- precisionabsolute time information by using a Chip-Scale Atomic Clock (CSAC) (Kurata, 2016; Kurata, 2018). Even if the CSACmounted sensor module/data logger is installed over a wide area and at high density, it is possible to acquire measurement
data with time synchronization without relying on a network or a global positioning system (GPS) signal. The CSACmounted sensor module as an Internet of Things (IoT) device was installed in an actual building, and a structural healthevaluation was performed for each subsequent earthquake (Kurata et al., 2008). A building structural health management
system was constructed wherein acceleration data on each floor during an earthquake as measured by the CSAC-mounted
sensor module is transmitted to a cloud server by 3G/LTE, and the acceleration, the inter-story drift angle and a structural
health evaluation of the building are displayed in 3D model by a Building Information Modeling (BIM). Forge (Applied
Technology, 2019; Autodesk, 2019) is employed as a development platform to realize this. This paper gives an outline of
the CSAC- mounted sensor module as an IoT device and the building where it was installed, along with case results ofseismic observations and inter-story deformation, a proposal for a building structural health management system, and its
envisaged future. As a demonstration, an autonomous time-synchronization sensing system as an IoT device was linked
with Forge, the BIM cloud expansion support development platform, and the results of a structural health evaluation
during an earthquake were shown on a BIM model.
Keywords: Building Management System, Building Information Modeling (BIM), Internet of Things (IoT), Structural
Health Monitoring, Earthquake Observation, Time Synchronization, Chip-Scale Atomic Clock.
IOT-5

DEVELOPMENT OF AN ANOMALY DETECTION SYSTEM OF ROAD SIGNSUSING MEMS ACCELEROMETERS
Naomasa Haibara1, Masayuki Saeki2
1) Master’s Student, Tokyo University of Science, Chiba, Japan. Email: 7618527@ed.tus.ac.jp
2) Dr. Eng., Prof., Tokyo University of Science, Chiba, Japan. Email: saeki@rs.noda.tus.ac.jp

Abstract: It is recognized as an important issue how to efficiently maintain an enormous number of social infrastructures.
For example, it is said that there are approximately 10 million road signs in Japan, and they are visually inspected once
every five years. The visual inspections take a lot of time and cost. Therefore, we have been trying to develop an anomaly
detection system for infrastructures. In this research, as a basic experiment, a road sign was constructed in our university.
Then, MEMS (Micro Electronic Mechanical Systems) accelerometers was fixed on the back of the signboard, and theacceleration responses were automatically observed every 4 hours for about 18 months to investigate the daily variation. A
single measurement was performed at 100 Hz sampling rate and 3 minutes data length. As a result, it was found that the
eigenfrequency of the first mode varied by about
0.01 Hz. We also simulated the damage of the boundary condition which was often seen in damage cases of road signs andexamined the change in responses. As reducing the thickness of the root part by about 0.5 mm which corresponded to
12 % decrement of bending rigidity, the eigenfrequency decreased by about 0.016 Hz. Since the change in eigenfrequency
was larger than the temporal variation, the anomaly was successfully detected. On the other hand, in the case of 0.1 mm
which corresponded to 5 % decrement, the change in eigenfrequency could not be detected because of the small variation.
In addition, we also examined the direct density ratio estimation method based on KLIEP (Kullback-Leibler Importance
Estimation Procedure) to detect the change point and abnormal value of the anomaly detection index.
Keywords: eigenfrequency, MEMS accelerometer, anomaly detection, road signs, density-ratio estimation, KLIEP

44

Program and Book of Abstracts, ICCBEI 2019

LIS-1

AUTOMATIC INDOOR ENVIRONMENT MODELING FROM LASER-SCANNED POINT
CLOUDS USING GRAPH-BASED REGULAR ARRANGEMENT RECOGNITION
Hayato Takahashi1, Hiroaki Date2, and Satoshi Kanai 31) Master Course Student, Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan. Email:h_takahashi@sdm.ssi.ist.hokudai.ac.jp
2) Ph.D., Assoc. Prof., Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan. Email:hdate@ssi.ist.hokudai.ac.jp
3) Ph.D., Prof., Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan. Email:kanai@ssi.ist.hokudai.ac.jp

Abstract: In this paper, an automatic regularized 3D modeling method of indoor environments from laser- scanned point
clouds is proposed. The method can efficiently create 3D indoor environment models which consist of a floor, a ceiling,
and walls with regular arrangements of orthogonal, parallel, coplanar, and regular intervals. In the method, first, a floor
and ceiling are extracted by plane fitting and parallelized by the least-square fitting. Then, wall line segments on theceiling plane are estimated from boundary points on the ceiling. Next, graphs for the wall line segments are successively
constructed to recognize the regular arrangements of the walls. In the graph, a node corresponds to one or more wall line
segments, and an edge represents regular arrangement relationships between the walls. The resulting graph expresses thesimplest regular arrangement relationships of the walls, and modified wall line segments are obtained by the least square
fitting of lines to corresponding points under the constraints of the regular arrangements. Finally, a 3D model is created bysweeping the wall line segments along a vertical direction. Experimental results using point clouds from the laser scansimulation of a 3D model and laser scanning of a real indoor environment show the effectiveness of the proposed method.
Keywords: Laser scan, point clouds, 3D indoor environment modeling, regular arrangement.

LIS-2

Detecting Building Façade Deteriorations: Evaluation of 3D Laser Scanning andImage-based Reconstruction Approaches to Determine Feasible Settings in Data
Collection
Zhuoya Shi1, Semiha Ergan2
1) Ph.D. Candidate, Department of Civil and Environmental Engineering, NYU Tandon School of Engineering, Brooklyn, NY, USA.
Email: zhuoyash@nyu.edu
2) Ph.D., Assist. Prof., Department of Civil and Environmental Engineering, NYU Tandon School of Engineering, Brooklyn, NY,
USA. Email: semiha@nyu.edu

Abstract: To identify façade conditions that may cause public injury, many cities mandate façade inspection programs.
With around one million aging buildings, New York City (NYC) requires buildings more than six stories to be inspected
every five years. Thus, a safe, comprehensive, and objective inspection method is important. Laser scanners can capture asis conditions rapidly and safely, while terrestrial laser scanners are influenced by the high incidence-angle in capturing
detailed crack information at required heights. Images captured through drones or stationary equipment at elevatedheights can aid with the height problem by generating point clouds via 3D reconstruction technology; however, isinfluenced by the accuracy of reconstruction algorithms. The objective of this study is to compare the point clouds
obtained from these two modalities of technologies for the visibility and measurement accuracy of cracks and define thesettings of equipment in capturing the right quality of point clouds at all floors including six levels and up. The experiments
use a series of simulated cracks with different widths and orientations. These cracks were generated at sizes and thresholds
indicated in building inspection programs (e.g., Local Law 11/98 in NYC) to understand the capability of two technologies
in detecting such thresholds. The root- mean-square error in the measurement of crack lengths as compared to the groundtruth data was utilized to evaluate the accuracy of crack detection using point clouds obtained with these two modalities.
Findings are influential for choosing and utilizing technologies at the right settings for effective periodical evaluations ofbuilding façades.
Keywords: building façade inspection, 3D laser scanning, 3D reconstruction.

45

Program and Book of Abstracts, ICCBEI 2019

LIS-3

AUTOMATED UAV ROUTE PLANNING FOR BRIDGE INSPECTION USING BIM-GIS
DATAYang Zou1, Molood Barati2, Enrique del Rey Castillo3, Robert Amor4, Brian H.W. Guo5, Jiamou Liu6
1) Lecturer, Department of Civil and Environmental Engineering, University of Auckland, Auckland, New Zealand.
yang.zou@auckland.ac.nz
2) Research Assistant, Department of Civil and Environmental Engineering, University of Auckland, Auckland, New Zealand.
mbar468@aucklanduni.ac.nz
3) Lecturer, Department of Civil and Environmental Engineering, University of Auckland, Auckland, New Zealand.
e.delrey@auckland.ac.nz
4) Professor, Department of Computer Science, University of Auckland, Auckland, New Zealand. trebor@cs.auckland.ac.nz
5) Lecturer, Department of Civil and Natural Resources Engineering, University of Canterbury, Christchurch, New Zealand.
brian.guo@canterbury.ac.nz
6) Senior Lecturer, Department of Computer Science, University of Auckland, Auckland, New Zealand. jiamou.liu@auckland.ac.nz

Abstract: Unmanned Aerial Vehicle (UAV) has been increasingly used for bridge inspection in the past few years and therecent development of 3D bridge models generated by UAV photogrammetry is highly promising for inspection purposes.
However, the current practices of UAV-enabled bridge inspection require human control, during which process the UAV
is flying close to the bridge location to take high-resolution images according to human commands. To overcome this gap,a novel method to automate the UAV route planning for bridge inspections is proposed, which uses Building Information
Modelling (BIM) and Geographic Information System (GIS) data as input to drive the automated UAV flying andoperations. The underlying assumptions include, 1) the integrated BIM-GIS system can represent the physical world, and2) the 3D bridge model generated by UAV photogrammetry can provide highly reliable and accurate data for bridge
inspection. Under such route planning, the BIM-GIS system provides the bridge’s geospatial and surrounding
environment information (e.g. bridge’s geometry, elevation, orientation) to guide the UAV flying the shortest path togather all required information for the bridge inspection according to a novel algorithm. The next stage of this project willvalidate and test the proposed method for real bridges.
Keywords: Unmanned Aerial Vehicle (UAV), Bridge inspection, BIM-GIS integration, Route planning, Photogrammetry.
LIS-4

MEASURING RAILWAY FACILITIES BY USING TWO MOBILE LASER SCANNERS
DIRECTLY ABOVE THE RAILS
Kohei Yamamoto1 and Nobuyoshi Yabuki2
1) PASCO Corp., Japan. Email: kootho1810@pasco.co.jp
2) Ph.D., Prof., Division of Sustainable Energy and Environmental Engineering, Graduate School of Engineering, Osaka University,
Suita, Japan. Email: yabuki@see.eng.osaka-u.ac.jp

Abstract: To measure three-dimensional shape of the rail is important for the safe operation of trains. Conventional rail
track measuring methods tend to be time-consuming, labor-intensive, and error prone. To grasp positions and shapes ofrailway facilities which are close to the clearance gauge, rapidly, efficiently and precisely, this research proposes a newmeasurement method by using two mobile laser scanners directly above the rails. In this method, two Mobile Laser
Scanners (MLSs) are installed directly above rails so that high-precision point cloud data can be obtained more rapidly
than the single MLS method. The point cloud data obtained by two MLSs directly above the rails can be accurately
coincided using the position of rail track center lines. The point cloud data of MLSs are compared with the point cloudcollected by Terrestrial Laser Scanner (TLS). Finally, this method was applied to the test rail line where two electric poles
are installed and it was identified within 0.01m of relative accuracy compared with TLS. The applicability of this method
has been verified to both curve and straight tracks.
Keywords: Mobile Laser Scanning, 3D Point Clouds, Registration, Facility Management, Monitoring.

46

Program and Book of Abstracts, ICCBEI 2019

IPM-1

A FEASIBILITY STUDY FOR LDAP CERTIFICATION IN COLLABORATION WITH
EXISTING ACCOUNTS IN RDBMS
Yoshiyuki Yokoyama1
1) Project Manager, Department of Systems Engineering, Japan Construction Information Center, Minato, Tokyo, Japan. Email:yokoyamy@jacic.or.jp

Abstract: For the purpose of improving productivity, we, JACIC, have been trying to apply a cloud storage product on ouralready existing application. This idea will have our users use a new login account instead of their existing account to becertified by a cloud storage product. However, since this would put a burden on users by requiring them to keep track ofmultiple accounts, we have focused on finding a single sign-on solution with LDAP. OpenLDAP, a product that implements
LDAP, as well as BerkeleyDB and HierarchicalDB, are used as a back- end system for storing login accounts. However,
RDBMS also could have been used at least from its documents. If the RDBMS is attached as the back-end for OpenLDAP,
the cloud will be able to access the existing login accounts through an LDAP interface. Thus, users will be certified by thecloud without having to register multiple accounts. However, there are a few OpenLDAP + RDBMS test cases online whichhave made us hesitate to choose LDAP as our single sign-on solution. This feasibility study shows some points of attention
for creating and operating an OpenLDAP + RDBMS environment.
Keywords: single sign-on, OpenLDAP, back-sql, slapd-sql, RDBMS

IPM-2

SEMANTIC MODELING OF BUILDING CONSTRUCTION EMISSION KNOWLEDGE
Wenkai Luo1, Guomin Zhang2, Lei Hou3, Malindu Sandanayake4
1) Ph.D. Candidate, School of Engineering, RMIT University, Melbourne, VIC, Australia. Email: s3691927@student.rmit. edu.au
2) Ph.D., Prof., School of Engineering, RMIT University, Melbourne, VIC, Australia. Email: kevin.zhang@rmit.edu.au
3) Ph.D., School of Engineering, RMIT University, Melbourne, VIC, Australia. Email: lei.hou@rmit.edu.au
4) Ph.D., School of Engineering and Science, Victoria University, Melbourne, VIC, Australia. Email: Malindu.Sandanayake@ vu. edu.au

Abstract: Previous works on estimating construction carbon emissions from energy consumption were primarily
capitalizing on the quantity of construction materials, equipment and an emission inventory. It is envisaged thatwith the aid of Building Information Modeling (BIM) technologies that are featured by semantic-rich data andinformation, the present-day practice of energy and emission estimation can be well improved. Despite an ideal
BIM model typically encompasses information that ranges across building design, construction and operation
details, a rationale around how to leverage semantic-rich BIM to address building energy consumption and carbon
emission topics is still unclear. Under this backdrop, this study is centered on formulating a semantic-rich building
energy consumption ontological model that is capable of accurately calibrating the energy consumption andemissions of a building. The formulated model will consider various factors that can affect the calibration andestimation such as materials, fabrication, logistics, processing, and the like.
Keywords: Construction Phase, Ontology, Emission Estimation

47

Program and Book of Abstracts, ICCBEI 2019

IPM-3

APPLICATION AND ANALYSIS OF SYSTEM ARCHITECTURE MODEL FORCONSTRUCTION PROJECT
Tatsuru Tomii1, Koji Makanae2, Raj Kapur Shah3
1) Software developer, Kokusai Kogyo Co., Ltd., Tokyo, Japan. Email: tatsuru_tomii@kk-grp.jp
2) Ph.D., Prof., School of Project Design, Miyagi University, Miyagi, Japan. Email: makanae@myu.ac.jp
3) Ph.D., Senior Lecturer, Faculty of Engineering and Technology, Liverpool John Moores University, Liverpool, United Kingdom.
Email: r.shah@ljmu.ac.uk

Abstract: In a smart society where physical space and cyber space are integrated. Similarly, the construction project life
cycle is being considered to be mutually related on both physical and cyber spaces. The project life cycle becomescomplicate when integrating the relationship between physical and cyber space. This paper presents the design of a systemarchitecture model in which the project life cycle is hierarchized, which is based on the scope of each process in the
project. Additionally, an analysis of the information technology that supports each process from the scope of this model isalso presented. The paper concludes that the proposed model is a useful tool to the construction project life cycle, and it
helps to organize the process and system of the project components.
Keywords: System architecture model, V-model, Construction project life cycle, Cyber-Physical systems

IPM-4

SMART CONSTRUCTION OBJECTS (SCOS): A NEW THEORY OF SMARTCONSTRUCTION IS BORN
Weisheng Lu1, Yuhan Niu2, and Chimay Anumba3
1) Associate Professor, Department of Real Estate and Construction, Faculty of Architecture, The University of Hong Kong,
Pokfulam, Hong Kong
2) Construction Industry Council (CIC), Hong Kong
3) Dean and Professor College of Design, Construction and Planning, University of Florida, USA

Abstract: Despite of the prolific development of smart systems in the construction industry, the theorizing work of ‘smart
construction’ is rather stagnant. The fundamental concepts, definitions, and models of smart construction are yet to be fully
explored. It is against this backdrop that this study seeks to advocate smart construction objects (SCOs) as an innovative
concept and the basic elements to define, understand, and achieve a new theory of smart construction. It does so byadopting a mixed-method strategy at the kernel. It establishes the conceptual and deployment elements of SCOs and tests
them in two case studies. This study reveals that the concept of SCOs can steer the field of smart construction towards a
new theory by (a) enhancing the theoretical lucidity on smart construction, and (b) providing a generalizable framework
for realizing it. One elegance of SCOs lies in that they can be adopted and implemented without radically changing theprevailing construction practice and process. Advancing smart construction through this direction can be expected to go
more promisingly than existing directions.
Keywords: Smart construction, smart construction objects, theory.

48

Program and Book of Abstracts, ICCBEI 2019

IS-1

COLLECTION DATA USING NEW TOOL TO
SATISFY SPECIFICATIONS
Yasushi Kawanai1
1) Registered Perfect Engineer (Civil), Director of E-bidding Support Center, Japan Construction Information Center, Akasaka, Tokyo,
Japan. Email: kawanaiy@jacic.or.jp

Abstract: As part of E-Bidding Support Center’s work with the Japanese Ministry of Land, Infrastructure,
Transportation and Tourism (MLIT), our help desk business for e-bidding is partially controlled by the ‘‘performance
regulations’’ on contract specifications, not amount regulations. The specifications say that the necessary facilities andstaff should be prepared for dealing with daily telephone inquiries. This does not involve amount regulations. And thespecifications also say that we should avoid making people wait when they call. Instead, immediate responses arerequested.
In order to prove that people are not waiting when they call, we need a new data. Therefore, I found a tool to obtain
this data and prove that we met this requirement. By using a type of Interactive Voice Response (IVR) system, we canget the data to prove people is not waiting when they call. As a result, we were able to prove that we satisfied the MLIT
specifications by the introduction of this system.
Keywords: Interactive Voice Response (IVR), data analysis, MLIT, specifications, performance regulations

IS-2

EDUCATIONAL ACTIVITIES AIMED AT IMPROVING PRODUCTIVITY IN
JAPANESE CONSTRUCTION INDUSTRIES THROUGH 3D-CAD
Yasuyuki Kikyo1
1) Senior Researcher, Construction Information Research Institute, Japan Construction Information Center, Tokyo Japan. Email:kikyoy@jacic.or.jp

Abstract: In 2014, the Japan Construction Information Center Foundation (JACIC), began a technical and institutional
plan about applying CIM. At the same time, the Ministry of Land, Infrastructure, Transport and Tourism (MLIT)
announced its policy for CIM, but there is no educational organization that provides instruction for 3D-CAD software in
the civil engineering field.
We believe it is urgent to develop human resources who can use 3D-CAD software in the construction field. Therefore,
we started holding educational activities in Japan called "CIM Challenging Education and Training" as a non-profit
service. We developed a special curriculum for 3D-CAD in the construction field with the cooperation of organizations
such as buildingSMART Japan. To date, we have held this program eight times from 2015 to 2018.
Keywords: BIM/CIM, develop human resources, 3D-CAD.

49

Program and Book of Abstracts, ICCBEI 2019

IS-3

IMPROVEMENT OF ELECTRONIC BIDDING CORE SYSTEM
Hiroyuki Ishiwata1
1) Manager, Systems Engineering Department, Japan Construction Information Center Foundation (JACIC), Tokyo, Japan. Email:ishiwath@jacic.or.jp

Abstract: Most Japanese public procurements were made through paper-based procedures before the year 2000. However,there were some problems with these paper-based processes such as inefficiency, non-competitiveness, and nontransparency. Furthermore, there was a serious issue involving unfairness in transportation costs and time between theparticipating companies.
The Japanese government officially announced the “e-Japan Strategy” in 2001 and active application of“information, communication, and technology.” For public procurement, an electronic procurement method using theinternet was planned. According to the policy, JACIC had developed package software for an electronic bidding system(Electronic Bidding Core System) in 2002. Afterwards, we launched some updates and are now on our latest version,
Version 6, released in March 2016. Currently, 800 public organizations have adopted our software.
For 15 years, we worked with several types of IT technology and launched update modules for this software. Then,a serious problem occurred in December 2016 that Java plugin technology will be abolished starting from the futureversion, Next Java SE Version 9. However, in September 2017, when Version 9 was released, it was announced that theabolition schedule of the Java plugin had been pushed ahead. The majority of Japanese public systems depend on Javaplugin technology, and our Electronic Bidding Core System was no exception, so we immediately got to work on an
emergency project for our system.
This paper describes that project.
Keywords: procurement, electronic bidding, JACIC

IS-4

INTEGRATION OF 3D MODELS OF STRUCTURES AND GEOLOGICALCOMPOSITION AS AN UNDERGROUND INFRASTRUCTURE MODEL
Toshiaki Hakoda1, Syoichi Nishiyama 2, Takaki Omori3, Isao Shiozaki4, Mamoru Narusawa5, andNobuyoshi Yabuki61) Assistant General Manager, Overseas Infrastructure Project Division, JGC Corporation, Yokohama, Japan. Email:hakoda.toshiaki@jgc.com
2) P.E., JP (Applied Science), General Manager, Social System Business Division, OYO Corporation, Tokyo, Japan. Email: nisiyamasyoichi@oyonet.oyo.co.jp
3) P.E., JP (Applied Science), General Manager, Engineering Division, Nikken Sekkei Civil Engineering Ltd., Email:oomorita@nikken.jp
4) Dr. Eng., General Manager, Geo-space Engineering Center (GEC), Engineering Advancement Association of Japan (ENAA) Email:shiozaki@enaa.or.jp
5) Deputy Manager, Facility Management Department, ESCA-SC, Email: narusawa@esca-sc.com
Ph.D., Prof., Division of Sustainable Energy and Environmental Engineering, Graduate School of Engineering, Osaka University.
Email: yabuki@see.eng.osaka-u.ac.jp

Abstract: To develop three-dimensional (3D) models as examples of the infrastructure model concept which would be
useful for the operation and maintenance or design and construction of underground facilities, we integrated 3D models of
the geological composition, the structure and the lifeline facilities (water supply and sewerage system, city gas line,
electrical power and communication lines) for the underground mall named ESCA in Nagoya City, Japan. After the
integration of the above 3D models, we were able to show the owner, ESCA-SC, that the soil layers were suitable toensure the stability of the structure. They also checked the 3D models by utilizing the Mixed Reality (MR) system andfound the integrated 3D models would be very useful for making a plan for the modification and renovation of theirfacilities.
Keywords: 3D geological model, underground mall and lifeline, Mixed Reality (MR)50

WINNER

V i rt ua l re a lity d esi gn stu d io

Ver.14Ultimate： US$19,200
Driving Sim： US$12,800
Advanced： US$9,700
Standard ： US$6,300
Presentation：
US$660

64bit
32bit

3D real time/virtual reality software UC-win/Road awarded Software Product of the Year, 2002.
Advanced software that enables the creation of large scale 3D spaces for all sorts of projects by
PC operations and with which you can give variety of presentations in real-time. It can be used as
an ideal software in a flexible development environment and for advanced system development.
地形

線形

道路土工処理FUNCTION
Large-scale VR support

CIM support
Utilization of standard data Simple and precise creation Thousands of 3D
and CAD dataof complex road structure models available for by DWG tooleasy and efficientVR modeling64 bit native support realizes the dynamic display of LOD and thesmooth processing of vast terrain and many fine models.
Visual Options Tool can change andcontrol various environmental effects.

Terrain data and map are included on the database. A 50m
topographic mesh(of New Zealand and Japan) and 2500 spatial
infrastructure data is included.
Other useful features include a custom terrain feature, a worldgeographic coordinate system conversion feature,DXF-XML
conversion as well as a 3D and 2D terrain editing feature.

VR space can be manipulated at will in
real-time by simple PC operations.
Before/After, scripting, and manual drivingfeatures all assist presenters.

Makes drawings of VR space model in
3D and supports CIM.

DESIGNSIMULATION
TRAFFIC SIMULATION

Terrain surface input/Road generation

Driving SIMULATION
Steering rotation

Digital maps available

Rivers, road cross sections

Cutting, embankment, berm

Signal control

Set cockpit

Traffic Floworbit of understeer
slip angle

Visualizing analysis results
Vehicle Motion Simulator
Plan view

Cross-section editor

orbit in case ofnon-slip driving tofront wheel direction

High grip roadsurface

Railway

Slippery roadsurface

Noise simulation

Crowd flow

Road attribute

Refuge simulation

Fluid analysis

Intersection editor

Off-road driving

Illumination andmeteorological effectModeling / Data linkage
Tunami simulation

Debris-Avalanche
simulation

FBX

Point cloud data

DWG/CAD

Setting of sound/vibration

IFC

Traffic AP

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Audio systemvibration

Lighting function Weather effect

System integration

6K digital signage

8DOF Traffic
safety simulator

4K 3D Driving
simulator

Ve r . 1 4 NEW FUNCTIONSCreation of 360-degree video

Linkage with Eye Tracking Devices

Real-time Linkage with Traffic Simulation
Model in VISSIMVISSIM

VISSIM
Data of driven
vehicleVR simulation videos created as 3D video can be displayedon VR Head Mounted Display and be published in VR video
formatCustomization of Rendering Process

Post process
Calculation of wheel andsuspension

Linkage of eye tracking devices with UC-win/Road allows inspection ofdriver's gaze-point, and exporting of logs recorded in real-time whilst
driving

Object Sensor

Sends UC-win/Road's vehicle data in real-time to VISSIM, which then calculates dataof surrounding vehicles and feeds the calculation result to UC-win/Road.

Direction
vector

Detect objects
contained in a
conevertexThis pixel color processing is able to be freely customized byusing OpenGL shader language GLSL. For example, it can beused for the space analysis function by object segmentation,
the deep learning and AI training, and the test data creation.

Data of other vehicles
and signals

Right angle

This function detects
objects within a sensor's measurement
range and visual field.
Version 14 supports
the detection of static
3D models, traffic flow
models, characters,
movable models, roadsigns, road markings,
and cockpit objects.

Enhancement of Simulation Real-time Linkage Option

Seamless interoperability with more devices●HTC VIVE Plug-in Ver.3
・Supports newest version of OpenVR API
・Device Model Display function updated
・Linkage with scenario events ・Ability set scenario triggers
・Linkage with VIVE Tracker ・Interface for developers available●UAV Plug-in Ver.5

・Supports newest model of DJI Drone

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Conference Venue:
Sendai Mediatheque

Subway: Kotodai-Koen Station

Sendai Station

Dinner Venue:
Sendai Castle Honmaru Kaikan

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Scenic Point

Statue of Date Masamune

Dinner Venue:
Sendai Castle Honmaru Kaikan

FLOOR MAP -Ground(1st) Floor of Sendai MediathequeStage[Crepuscule Café]

Presentation Area

Ceremony and Keynote
LectureReception Party[Open Square]Power Supply

Coffee and Lunch Area
Sponsor’s
Exhibition

Reception

Shop

Elevator (Lift)
To Parallel Session (7F)

Entrance

FLOOR MAP - 7th Floor of Sendai Mediatheque

Entrance to Theater

Session-A
StudioTheater(Cinema)

Session-B
Meeting
Room
A/B

Elevator (Lift)
To Ground Floor

Proceeding of the 4th Interenational Conference on Civil and Building Engineering Informatics
ISBN978-4-600-00276-3
can be downloaded from https://www.iccbei2019.com

Photos are provided by SenTIA

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