이 슬라이드는 한국 퍼실리티 매니지먼트 학회 컨퍼런스(2017년 11월) 발표자료입니다. 시설물 관리를 위한 BIM 활용 시 Smart BIM의 개념을 발표하고, 관련 연구 및 사례를 공유하였습니다.

1. Acknowledge
This research was supported by a grant (17AUDP-B127891-01) from the Architecture & Urban Development
Research Program funded by the Ministry of Land, Infrastructure and Transport of the Korean government.
Korea Institute of Civil engineering and building Technology
강태욱 공학박사
laputa99999@gmail.com
sites.google.com/site/bimprinciple
Smart BIM for FM

2. 소개 Ph.D. KICT senior researcher
ISO/TC211 committee member. 9 books publishing

3. KICT
1 BIM connection

4. BIM Role in digital transformation
FM-CPS
CPS
Structural
health
monitoring
Track and
trace
Remote
diagnosis
Remote
services
Remote
control
Condition
monitoring
Systems
health
monitoring
BIM
as i-DB
IoT…
AI
Sensor device
ICBM
MRFM
Scan-Vision

5. Smart BIM
BIM
Big data
Processing Data
Mining / Analysis
Smart FM
Dashboard
IoT Big Data processing considering reliability
KPI matrix data ming / analysis
IoT / BAS nodes
PCI Operation
Effectiveness Maximization
KPI management using dashboard
f(x)
bxayxf :)(
Association
analysis
Basic statistics
analysis
Prediction
Analysis
…
Effective decision making support
In the future, when PCI will be over
the criteria?
Expected energy usage in next year?
KICT

6. IoT BIM
Packing
Wireless
Sensor
Gateway
IoT
Control
Big data
analysis
Protocol
IoT
connection
service
http://daddynkidsmakers.blogspot.kr/
A BIM ANALYSIS OF HVAC AND RADIANT COOLING SOLUTIONS, ROBERT CUBICK, 2016
KICT

7. IoT BIM
Packing
Wireless
Sensor
Gateway
IoT
Control
Big data
analysis
Protocol
IoT
connection
service
http://daddynkidsmakers.blogspot.kr/
A BIM ANALYSIS OF HVAC AND RADIANT COOLING SOLUTIONS, ROBERT CUBICK, 2016
KICT

8. IoT-BIM connection
BIM
W1
D2
F3
R4
Geo-information
W1
= {LOD1, LOD2, LOD3, LOD4}
D2
= {LOD1, LOD2, LOD3, LOD4}
F3
= {LOD1, LOD2, LOD3, LOD4}
R4
= {LOD1, LOD2, LOD3, LOD4}
B2G LM
B2G EM
IoT
+External
Data Set
• In example, W1 = Wall#1, D2 = Door#2, F3 = Floor#3, R4 = Roof#4.
• External Data Set – External data set related to the specific use-cases such as the facility
management
E1
E2
E3
E4
B2G PDElement Mapping
LOD Mapping
Property Mapping
from External Data
Set using PD
ISO N19166 - B2GM Data Mapping Flow
Data
= {Maker,
Code, Serial
No, Date,
Manual Links,
Drawing
Links,
Historical
Record…}
Object =
Geometry + Data
1
2
3
KICT

9. Geospatial information modeling – 3D scan & reverse engineering
Trimble
GPS
카메라
카메라
스캐너
IMU
DMI
KICT

10. Geospatial information modeling – 3D scan & reverse engineering

11. Geospatial information modeling – 3D scan & reverse engineering
KICT

12. 3D data set for deep learning
KICT
ShapeNet Part (Princeton, Stanford, TTIC)
51,300 unique 3D models
CIFAR (Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton)
60,000
10 classes
ImageNet (Fei-Fei Li)
Matterport 3D
90 buildings
194,400 RGB+D
10,800 3D (RGB+D)

13. AI Machine Learning (ML) for space scan
VoxNet: A 3D Convolutional Neural Network for real-time object recognition
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation, 2017

14. GeoIoT-BIM connection
f(x)
bxayxf :)(
SELECT * FROM Alignment, Building WHERE
Buffer(Alignment, Building, ‘1km’) AND
Building.Pset(‘FM’).PCI < ‘50%’
ORDERBY Building.Pset(‘FM’).PCI
BIMGIS
SELECT * FROM Building, Pipe WHERE Overlap(Pipe, Building, ‘1m’)
AND Building.Pset(‘FM’).Owner = ‘LH’ …
Fig. IFC (http://www.iai-tech.org/)
IfcProject – Activity to make product
IfcProcess – Process and activity in project
IfcResource – Used resource object definition in process
IfcActor – Human resource definition in process
IfcProduct – Physical representation object
IfcControl – Control object
IfcGroup – Object set
Kernel
3개기본 확장 패키지
5개AEC/FM공통 패키지
AEC/FM도메인별9개의패키지
26개의 리소스패키지
IFC2x3
Building
Oriented
Format
IFC4
GIS CRS
NURBS
…
but
Heavy
Complex
Ambiguous
•Developed by OGC
•Open 3D urban object model for interoperability(ISO TC211)
•Shape, material, feature information support
•Focusing city Infrastructure object model
•Model abstraction support(LOD)Version 2.0
CityGML
GIS Oriented
Format
LOD
Features
But
Detailed
Building
Information?
Parameter set
Civil engineering
object
Detailed object
information
related to civil
engineering
ex- superelevation
LandXML
Civil
Engineering
Oriented
Format
But
Detailed
Building
Information?
GIS Topology
Element?
GIS BIM
외부
이기종
데이터
External
Dataset
I-DB
도시
시설물
사용자
KPI
(Key
Performanc
e Indicator)
BIM-GIS
연계기술
데이터
분석
IoT nodes
Geospatial BIM External
data object
KICT

15. MR-BIM for Digital Twin
KICT
visualive3d
Ioannis Brilakis(2017.5)
Infrastructure sensing
(Kenichi Soga)

16. KICT
2 Smart BIM
for intelligent FM
BIM-based Data-Mining Method
considering Data Integration and
Function Extension, KSCE

17. Scan-BIM-FM-Field(SBF) R&D overview
용도구분 복합도
(complexity)
규모 (scale)
플랜트
복합건물
병원
대형 쇼핑몰
주거 단지(아파트 단지)
공공건물(학교, 관공서)
근린생활시설(상가, 오피스, 동사무소)
소형주거
5층 이하 정형 건물 6~12층 13층~고층 고층~초고층
소형(연면적 3,000 이하) 중형(3,000~10,000 ) 대형(10,000 이상)
한국건설기술
연구원 본관동
S사 반도체 공장
대형 캠퍼스
대학 병원
코엑스
S사 래미안
세종시 청사
오피스
상가
다세대
주민센터

18. Scan-BIM-FM-Field(SBF) R&D overview
KICT
1.56

19. Scan-BIM-FM-Field(SBF) R&D overview
FM BIM 현장
경영정보
시스템(MIS)
1. 하자 확인
2. 유지보수 요청
3. 하자 현장 확인
4. 공사/유지보수 이력확인
5. 공사/유지보수
위치 및 구조/이력 확인 (도면 등)
6. 작업계획작성
시설물 관리
업체
7. 업체작업견적요청
11. 업체견적제출
12. 업체견적검토
13. 작업진행
결재 요청
14. 작업진행승인
15. 업체계약/
작업요청
8. 업체 현장확인
16. 유지보수작업
18. 유지보수작업
전후 결과 및 산출물 제출
17. 유지보수작업
전후 결과 확인
22. 작업비용
결재 요청
19. 유지보수작업 결과 현장 확인
23. 작업비용 결재
및 이력 등록
20. 도면/문서/이력 갱신
DB
24. 유지보수작업 결과 통보
21. 작업비용요청
9. 현장작업
관련자료 요청
10. 현장작업
관련자료 전달
25. 비용결재
요청개체 / 시스템
정보 수집
반복 작업
작업자시설물
관리자
경영관리자
Actor
자체
수행
시설물 관리 BIM DB
C. IoT / Tag
Mobile
VR / AR
B. Big data / Data analysis
Machine Learning
Knowledge model / LCC
A. Scan-BIM
Drawing-BIM
역설계
활용 기술
ICBM
ICBM=IoT, Cloud, Big Data, Mobile
Scan-BIM Field FM
Intelligent
FM
Smart
FM

20. Data Mining Framework for Smart FM
Diversity management perspective
Data
diversity
Service
diversity
Flexible and simple forms of Integrated Data Model (IDB)
Data model transformation (DMT)
Data model validation rule (DVR)
Data binding method considering BIM object (DBM)
Service extensibility (SEB)
Service management method considering reusability (SRU)
Problem description method for implementing services
(PDM)
Before developing BIM-based DM, to identify considerations for ensuring the
support functions such as data transform, binding, integrity, extensibility is
needed.

21. Identification of the framework structure
The B-DM4SEM framework structure is identified based on the consi
derations
B-
DM4SEM
IDB
DMT
DBM
DVRPDM
SEB
SRU
Integrated Data Model
Data model transfo
rmation
Data model validation rule
Data binding method c
onsidering BIM object
Problem description met
hod for implementing ser
vices
Service extensibility
Service managem
ent method consi
dering reusability

22. Identification of the framework structure
Block diagram of B-DM4SEM framework
The B-DM4SEM framework structure is identified based on the considerations
BIM-based Integrated
Database
BIM-based Data Mining
Operator
BIM-based Data Mining
Script
BIM-based Service
Container
Service #1
Service #2
Service #n
BIM Server
BIM-based ETL
BIM Object
Data Binder
Service Plug-ins
BIM-based Data Model
Validation Rule set
Data Mining
Function Library
IFC, Revit …
Excel, Xml …
Xml, Text …
Plug in
B-DM4SEM
manage energy
of building space
Actors
Decision
making support
Energy
usage data
BIM data
Sensor data

23. Method definition of BIM-based energy management data
integration
DMT, DBM, and RM, which define how to ensure reliability and BIM object integration along wit
h an external data transformation for energy management, consist of B-ETL, B-ODB, and B-DVR,
and thereby integrate and verify the external data
B-DATA-EXTRACTOR
B-DATA-
TRANSFORMER
B-DATA-LOADER
B-DATA-BIND-RuleSET
B-DATA-BIND-MAPPING
B-DATA-BIND-LOGGER
BIM-based
Data set
BIM Object
Database
Energy
usage data
Sensor data
B-ETLB-ODB B-DVR
B-DATAMODEL-RuleSET
B-DATAMODEL-VALIDATOR
B-DATAMODEL-LOGGER
<B_ODB>
<Rule name=‘Space object binding’>
<Object name=‘Space’ PK=‘GUID’>
<Dataset name=‘E#1.Space’ PK=‘GUID’
Pset=‘Identity’ />
</Object>
</Rule>
</B_ODB>
<B_ETL>
<Module>
<Element type=‘extract’ name=‘E#1 Dataset’ datasource=‘...’/>
<Element type=‘transform’ name=‘T#1’ program=‘…’/>
<Element type=‘load’ name=‘L#1’ datasource=‘…’/>
</Module>
<Workflow name=‘Space Energy Usage ETL’>
<Step name=‘S#1’ input=‘E#1, E#2, E#3…’
execute=‘T#1’ output=‘L#1’/>
<Step name=‘Validate data model’
execute=‘B_DVR.B_IDM schema Rule’ />
</Workflow>
</B_ETL>
<B_DVR>
<Rule name=‘B_IDM schema Rule’
method=‘schema’ option=‘all’ />
</Rule>
<Rule name=‘GUID check Rule’
method=‘sql’>
WHERE Object.Pset.Property.GUID
IS NOT NULL
</Rule>
</B_DVR>
WORK
FLOW
Object
<<PK>>+OB_ID
<<FK>>+OT_ID
<<FK>>+OC_ID
+Name: string
PSet
<<PK>>+PS_ID
<<FK>>+PARENT_PS_ID
<<FK>>+OB_ID
+Name: string
Property
<<PK>>+P_ID
<<FK>>+PS_ID
+Name: string
+Value: string
PSetDictionary
<<PK>>+PD_ID
<<FK>>+PARENT_PD_ID
<<FK>>+OT_ID
+Name: string
+Validate(PSet): bool
+Create(): PSet
**
DomainSchema
<<PK>>+DM_ID
<<FK>>+PARENT_DM_ID
+Name: string
+Description: string
*
ObjectType
<<PK>>+OT_ID
<<FK>>+DM_ID
+Name: string
+Description: string
+Validate(Object): bool
+Create(): Object
*
PropertyType
<<PK>>+PT_ID
<<FK>>+PD_ID
+Name: string
+Description: string
+Type: PT_ENUM_TYPE
+Formating: string
+Validate(Property): bool
+Create(): Property
*
ObjectContainer
<<PK>>+OC_ID
+Name: string
*
Relationship
<<PK>>+RS_ID
<<FK>>+RT_ID
<<FK>>+OT_ID_LEFT
<<FK>>+OT_ID_RIGHT
+Name: string
RelationshipType
<<PK>>+RT_ID
+Name: string
+Description: string
+Type: RT_ENUM_TYPE
+CustomType: string
<<FK>>+OT_ID_LEFT
<<FK>>+OT_ID_RIGHT
+Validate(Relationship): bool
+Create(): Object
*
2
*
*
RT_ENUM_TYPE
<<enumeration>>
+Generalization
+Aggregate
+Contain
+Association
+Custom
PT_ENUM_TYPE
<<enumeration>>
+Integer
+Real
+List
+Table
+BineryData
+Custom
Object
<<PK>>+OB_ID
<<FK>>+OT_ID
<<FK>>+OC_ID
+Name: string
PSet
<<PK>>+PS_ID
<<FK>>+PARENT_PS_ID
<<FK>>+OB_ID
+Name: string
Property
<<PK>>+P_ID
<<FK>>+PS_ID
+Name: string
+Value: string
PSetDictionary
<<PK>>+PD_ID
<<FK>>+PARENT_PD_ID
<<FK>>+OT_ID
+Name: string
+Validate(PSet): bool
+Create(): PSet
**
DomainSchema
<<PK>>+DM_ID
<<FK>>+PARENT_DM_ID
+Name: string
+Description: string
*
ObjectType
<<PK>>+OT_ID
<<FK>>+DM_ID
+Name: string
+Description: string
+Validate(Object): bool
+Create(): Object
*
PropertyType
<<PK>>+PT_ID
<<FK>>+PD_ID
+Name: string
+Description: string
+Type: PT_ENUM_TYPE
+Formating: string
+Validate(Property): bool
+Create(): Property
*
ObjectContainer
<<PK>>+OC_ID
+Name: string
*
Relationship
<<PK>>+RS_ID
<<FK>>+RT_ID
RelationshipType
<<PK>>+RT_ID
+Name: string
+Description: string
+Type: RT_ENUM_TYPE
+CustomType: string
<<FK>>+OT_ID_LEFT
<<FK>>+OT_ID_RIGHT
+Validate(Relationship): bool
+Create(): Object
*
2
*
*
RT_ENUM_TYPE
<<enumeration>>
+Generalization
+Aggregate
+Contain
+Association
+Custom
PT_ENUM_TYPE
<<enumeration>>
+Integer
+Real
+List
+Table
+BineryData
+Custom
B-IDM
Operational concepts and correlations of DMT, DBM, and DVR in B-

24. Definition of operators for BIM-based data mining
The operator definition is divided into CRUDE in consideration of MECE. Here, CRUDE
and the "*" mark have the following definitions.
C, create; R, read query; U, update query; D, delete; E, execute; and *, plural indicator of an
object
Operator Namespace Operator-Supported Object
CRUDE B-DET-OP Data Extractor (TDE), Data Transformer (TDT), Data Loader (TDL)
B-ODB-OP Data Binding Rule (BRU), Data Binding Logger (BLG)
B-DVR-OP
Data Model Validation Rule (MRU), Data Model Validator (MVA), Data Model Va
lidation Logger (MVL)
B-DM-OP
Classification Model (DMCF), Prediction Model (DMPD), Clustering Model (DM
CL), Association Model (DMAS)
CRUD
B-DMS- OP
DomainSchema (BDS), ObjectType (BOT), RelationshipType (BRT), PSetDictio
nary (BPD), PropertyType (BPT), ObjectContainer (BOC), Object (BOJ), Relati
onship (BRS), PSet (BPS), Property (BPR)
CD B-DET-OP Data Source (TDS)
B-ODB-OP Binding Data Source (BDS)

25. Case study
Use cases for the defined building-space energy management applied in this study
are as follows.
1. Which spaces and users of those spaces exceed the specific
reference amount of annual energy usage?
2. When was the first time this reference amount was exceeded, and
for which space, based on the trend of annual energy consumption?
The reference usage value for use case 1 was 1,000 kWh, and that for use case 2 was
5,000 kWh.
f(x)
Regression equation model
bxayxf :)(x and y vector Slope and intercept

26. Case study: use-case #1
B-DM4SEM
1.Executing use case-1
2.Searching
& executing
a service
3.Executing data
miningmodelfor
service
4.Obtaininginformation forservice
5.Rendering data
miningresults with
spatialinformation

27. Case study: use-case #2
B-DM4SEM
1.Executing use case-2
2.Searching
& executing
a service
3.Executing data
miningmodelfor
service
4.Obtaininginformation forservice
5.Rendering data
miningresults with
spatialinformation
Identifying space object in
BIM with data mining results.

28. BIM R&D
KICT

29. BIM R&D
KICT

30. Experiment result
Test method division and phase
Work performance time
A B C D E
Existing work m
ethod
Related data proc
essing time
Search 827.7 620.1 578.6 537.1 495.5
Collect 185.6 167.4 160.2 161.3 154.1
Integration 1200.8 996.0 955.1 914.1 873.2
Work performance/Report generatio
n
405.0 336.3 322.5 308.8 295.0
Total work time A 2619.0 2119.7 2016.3 1921.2 1817.8
B-DM4SEM met
hod
Work performance/Report generatio
n B
12.0 10.5 11.0 11.5 11.0
Work time difference D = A – (B + C) 2491.5 1993.7 1889.8 1794.2 1691.3
Improved performance ratio R = A / (B + C) 20.5 16.8 15.9 15.1 14.4
Results of the work performance time (min) for each case (
manual)

31. Experiment result
Related data integratio
n rule development tim
e
DB extraction 3.0
BIM integration time 65.0
B-DM script develop
ment time
47.5
Total work time C 115.5
B-DM4SEM data integration rule development time
0.0
500.0
1000.0
1500.0
2000.0
2500.0
3000.0
A B C D E
Existing work
B-DM4SEM
min
Use case
Comparison of work performance time for each case
The maximum annual energy reference usage was divided into the
following phases:
A (5000 kWh), B (6000 kWh), C (7000 kWh), D (8000 kWh), and E (9000
kWh)

32. AEC-IoT use cases
AEC-
IoT
장비
모니터링
장비
검사/
수리
재고
관리/
주문
에너지
관리
물류
모니터링
인력
이력
추적
웨어
러블
안전
whitelight group, 2014)
KICT

33. Smart FM use cases
Watson IoT is connecting the workplace of the future (1:36, IBM)
KICT

34. Smart FM use cases
Watson IoT is connecting the workplace of the future, IBM
KICT

35. Smart FM with BIM
https://www.i-
scoop.eu/industry-4-0/
IoT + BIM
Big data
AI / ML
MR
Smart FM
Usecase
Data
Connection

36. 1. 강태욱, 임지순 역, 2015.2, 스마트 홈 오토메이션, 씨아이알
2. 강태욱, 현소영 역, 2014.12, 스마트 빌딩 시스템, 씨아이알
3. 강태욱, 김호중, 2014.1, BIM기반 건축 협업 디자인, SpaceTime
4. 강태욱, 2011.6, BIM의 원리, SpaceTime
5. Alan Safe, 2016.2.12, How the Internet of Things is Impacting the Construction Industry, For Construction Pros.com
6. Rachel Burger, 2015.7.28, Three Ways the Internet of Things Can Benefit Your Construction Project, Construction
Management
7. Jacqi Levy, 2016.4.28, 4 BIG ways the IoT is impacting design and construction, Internet of Things blog, IBM
8. whitelight group, 2014.8.18, How the Internet of Things is transforming the construction industry
9. Rachel Burger, 2016.8.5, How "The Internet of Things" is Affecting the Construction Industry, the balance.com
10. AIG, Human Condition Safety: Using Sensors to Improve Worker Safety
11. Niina Gromov, 2015.11.23, Offering Value through Internet of Things Case: Construction Companies in Finland, School of
Science, Aalto University
12. Wipro Digital, 2016.4.1, CASE STUDY: INCREASING CUSTOMER VALUE THROUGH IOT FOR JCB INDIA
13. Monitor Deloitte, 2015.7, Every. Thing. Connected.
14. Laura Black, 2015.8.12, An Inside Look at Autodesk’s Project Aquila, ConstructionTech
15. Jeff Walsh, 2015.10.1, Human Condition Aims to Transform Construction-Site Safety With Wearables, Line shape space.com
16. Insights, IoT Logistics Are Transforming the Trucking Industry
17. Chris Topham, 2015.9.10, Case Study: Northumbria Specialist Care Hospital Pushes KNX into the IoT, Abtec Building
Technologies
18. Mike Chino, 2015.11.6, Intel’s Smart Tiny House packs futuristic technology into 264 square feet, inhabitat
19. Wanda Lau, 2016.5.9, KieranTimberlake Offers a New Tool for Architects Wanting an In on IoT
20. CADDIGEST, 2016.7.7, IBM Watson IoT Platform to Add Intelligence to Buildings Worldwide
Reference
KICT
Acknowledge
This research was supported by a grant (17AUDP-B127891-01) from the Architecture & Urban Development
Research Program funded by the Ministry of Land, Infrastructure and Transport of the Korean government.

37. http://daddynkidsmakers.blogspot.kr/AEC IoT ?
Packing
Wireless
Sensor
Gateway
IoT
Control
Big data
analysis
Protocol
IoT
connection
service
극한 환경
습도/온도
충격/전파
설치 대상
위치 공간
센서 신뢰성
정확도/해상도
캘리브레이션/진단
유지보수/관리
전력 문제
쉐도우 영역
전파 방해
전력 문제
빅데이터
노이즈 필터링
보안 문제
응용 별 데이터
트래픽 문제
실시간성 데이터
수집/분석 빈도
응용 별 데이터
분석 방법
응용 별 모니터링
/제어 방법 표준
문제
IoT 서비스 / DB
연결 표준 문제
KICT