how DATA CAN Accelerate the adoption of SDG’S in the AEC industry?

DATA U N I T

VISUALIZATION & ANALYTICS

DATA MINING ANALYTICS & VISUALISATION

PROGRAMMING

AUTOMATION

PARAMETRIC MODELING

DATA UNIT |Columbia University 2019.11.13

LARGE SCALE

SUSTAINABILITY

DATA ANALYTICS

PROGRAMMING

DATA MINING ANALYTICS & VISUALISATION

ENVIRONMENTAL SCRIPTING

LARGE SCALE

PARAMETRIC SUSTAINABILITY AUTOMATION MODELING

DIGITAL FABRICATION

PREDICTIVE ANALYTICS

HOW DATA CAN ACCELERATE THE ADOPTION OF SDG’S IN THE AEC INDUSTRY? DATA UNIT |Columbia University 2019.11.13

2

WHAT IS DATA? FACTS AND STATISTICS COLLECTED TOGETHER FOR REFERENCE OR ANALYSIS. DATA UNIT | Columbia University 2019.11.13

WHY DATA IS SO IMPORTANT?

DATA U N I

2000 TOOL CAD/CAM

VISUALIZATION & ANALYTICS

DATA MINING

NOW BIM AUTOMATION SIMULATION SCRIPTING FABRICATION DATA ANALYTICS MACHINE LEARNING IOT

PROGRAMMING

AUTOMATION

PREDICTIVE ANALYTICS

2040 AI PARTNER OR AGENT

THE GROWTH OF COMPUTER POWER 4

DATA UNIT |Columbia University 2019.11.13

PROJECT DATA LIFE CYCLE

LIFE CYCLE OF DATA IN AEC DATA MINING IDENTIFY AND UNDERSTAND DATA

INTEGRATE AND ENRICH DATA

TEST OPTIONS & MODELS

Data

USER NEEDS

LEGACY DATA

WORKSPACE TRENDS

BENCHMARKS

PROPOSAL / FEASIBILITY

FINAL PROJECT

Data

SUSTAINABILITY WEATHER DATA

BIM

FINAL PROJECT

CONSTRUCTION

ENVIRONMENTAL MODELING

SUSTAINABILITY CERTIFICATIONS

MANAGEMENT

AUTOMATION & MACHINE LEARNING

SITE DATA

PROGRAM AND VIEW SCENARIOS CONCEPTUAL DESIGN

DATA UNIT |Columbia University 2019.11.13

Data

BIM ITERATIVE

PREDICTIVE ANALYTICS

PARAMETRIC MODELING SCHEMATIC DESIGN

DESIGN DEVELOPMENT

MONITORING

FINAL PROJECT

DETAILLING & SPACE PARAMETERS

BUDGET & BIDDING

CONSTRUCTION DOCUMENTS

SITE COORDINATION

POST OCCUPANCY DATA

APPS FOR DAILY USE

DIGITAL FABRICATION CONSTUCTION BIDDING

CONSTUCTION ADMINISTRATION

POST OCCUPANCY

5

DATA ANALYTICS

PROGRAMMING

DATA MINING ANALYTICS & VISUALISATION

PREDICTIVE ANALYTICS

DATA UNIT | Columbia University 2019.11.13

ENVIRONMENTAL SCRIPTING

LARGE SCALE

DATA ANALYTICS FOR SUSTAINABLE CITIES AND COMMUNITIES PARAMETRIC SUSTAINABILITY AUTOMATION MODELING

DIGITAL FABRICATION

Survivorship Bias

SURVIVORSHIP BIAS THE TENDENCY TO FOCUS ON SURVIVORS INSTEAD OF A NON-SURVIVOR

GDP PER CAPITA,PPP

GINI INDEX ( DISTRIBUTION OF INCOME)

DENMARK 29

US 45

CHILE 52

SOUTH AFRICA 62.5

Survivor

“CHILE IS MORE UNEQUAL NOWADAYS THAT IT WAS BEFORE THE DICTATORSHIP”

*ABRAHAM WALD, HUNGARIAN MATHEMATICIAN

TOP INCOMES IN CHILE: A HISTORICAL PERSPECTIVE OF INCOME INEQUALITY (1964-2015), JORGE ATRIA ET. AL, WORLD INEQUALITY DATABASE

DATA UNIT |Columbia University 2019.11.13

7

MMING

DATA MODELING FOR FUTURE SCENARIOS PATIENT dIscharge days Long space deficit

10/23/2019

The Space Deficit

180,000 200,000

183,600

167,535 540 Bed 85%

160,000 157,680 540 Bed 80%

150,000

140,000

DATA ANALYTICS

ENVIRONMENTAL SCRIPTING

100,000

85,355

100,000

4.4%

50,400

50,000

77,003 249 Bed 30,000 85% 81,789 24,000

32,500

SDG

80,000

28,223

DATA MINING ANALYTICS & VISUALISATION

70,573

ery

S… rg d/ e65,889 Su tM

In

25,238

67,090

0

n 60,000 tie pa

2014

2015

cy

en

rg me

E

ry

to

a 2017 or ab

L

90%

AEC

15,095

r&

bo

La

2019

ery

liv

De

ity

rn

ate

ion

t

tra

s ini

m

Ad

20,000

13,200

16,227

12,703

tM

en

ati

Inp 2020

21,000

18,000

ing

ag

Im

6,278

2023

nt

e ati

Inp

U

3,897

IC

eiv

& ing

c Re

M

M

2025

ath

C

9,600

8,400

7,979

7,875

8,322

8,467

7,979

7,875

/IR

b

La

SP

CS

E

Value

64,393 (19.55%) 78%

2014

74%

2015

111,610 (33.89%)

ing

3,963

t

s Te iac

rd

Ca

Value

85%

72%

o

sc

o nd

py

8,400 e tP

en ati

Inp

ds

2030

Bed Scenarios 94% PARAMETRIC SUSTAINABILITY AUTOMATION 93% Current 318 Beds DGSF 400 Beds DGSF ICU, MODELING 90% 329,294 549,247 Total

22,417 (6.81%)

85%

70%

n

Di

/ ice

erv

dS

o 2018 Fo

95%

80%

PREDICTIVE ANALYTICS

rm

ha

P T/ /R

ing

23,800

21,600

11,567

108,588 350 Bed 85%

102,200 350 Bed 80%

85 ,187

84,328

16,495

72,708 s 249 Bed ce rvi Se 80% t or

pp

Su

2016

28,000

23,967

Current 318Occupancy Beds R ate LARGE SCALE

75%

130,232 446 Bed 80%

Percentage Growth 2014 - 2020

120,000

2016

292

249 Bed 130,874 (39.74%) 85% 2017 249 Bed 80% 2016 Q2 2017

DIGITAL FABRICATION 2018

Type

138,372 446 Bed 85%

Med/Surg Peds 249

6,000

6,400

4,800

5,600

4,800

5,418

4,304

3,311

4,800

3,828

1,886

ter

en

C ep

Sle

5,418

Diagnostic & Treatment

a

Inp

u

vo

ha

Be

ral

a

He

Fa

ly mi

lth

a

He

itt

m Ad

2035

ing

era

h cT

Oc

al/

sic

y Ph

2037

2,128 2,128 are

dC

n ou W

1,200 598

547 547

C AT

sis

aly

Di

2039

2040

85%

400 Bed Scenario Estimated year Patient

2016

Discharge Days Estimated year Patient Discharge Days

28,800 (5.24%)

110,400 (20.1%)

72,708

2017

77,252

102,200

2025

108,588

400

350

2023

500

446

2030

130,232

2032

600

540

2037

157,680

2039

Average Daily Census

py

2015

2016

138,372

243,200 (44.28%)

167,535

2017

2018

2019

2020

180.52

183.81

193.35

210.97

224.08

231.04

233.39

Total Adult & Pediatric 65,889 Disch. Days Occupancy R ate 72% 249 Bed Support Services Public & Administration

67,090

70,573

77,003

81,789

84,328

85,187

85%

90%

93%

94%

2020

Nursing Units

2032

U

IC

tN

n tie

lth

80%

2014

2019

C

n

ere

f on

ce

4,000 1,704

74% 166,847 (30.38%) 78%

1/1

DATA UNIT |Columbia University 2019.11.13

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DATA MODELING FOR PLANING DATA ANALYTICS

ENVIRONMENTAL SCRIPTING REGIONAL LEVEL

AL SCRIPTING

EXCEL DATABASE

SDG

LYTICS

ENVIRONMENTAL SCRIPTING PROGRAMMING

NABILITY AUTOMATION

NING GITAL CS & CATION ATION

LARGE SCALE

AEC

DATA MINING ANALYTICS & VISUALISATION

ROOM LEVEL

PARAMETRIC SUSTAINABILITY AUTOMATION MODELING

LARGE SCALE

DIGITAL FABRICATION

PREDICTIVE ANALYTICS

PARAMETRIC SUSTAINABILITY AUTOMATION MODELING

DIGITAL FABRICATION

VE CS

DATA UNIT |Columbia University 2019.11.13

* Script by Hung Kit and Carlos Sarmiento

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GEOGRAPHIC DATA FOR HAZARD VISUALIZATION DATA ANALYTICS

AL SCRIPTING

ENVIRONMENTAL SCRIPTING

SDG

YTICS

ENVIRONMENTAL SCRIPTING PROGRAMMING

NABILITY AUTOMATION

ING TAL CS & CATION TION

LARGE SCALE

DATA MINING ANALYTICS & VISUALISATION

PARAMETRIC SUSTAINABILITY AUTOMATION MODELING

LARGE SCALE

DIGITAL FABRICATION

PREDICTIVE ANALYTICS

PARAMETRIC SUSTAINABILITY AUTOMATION MODELING

AEC DIGITAL FABRICATION

E S

DATA UNIT |Columbia University 2019.11.13

* Tool by

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DATA ANALYTICS

ENVIRONMENTAL SCRIPTING

ENVIRONMENTAL SCRIPTING EMBODYING CLIMATE ACTION PROGRAMMING

DATA MINING ANALYTICS & VISUALISATION

PREDICTIVE ANALYTICS

DATA UNIT | Columbia University 2019.11.13

LARGE SCALE

PARAMETRIC SUSTAINABILITY AUTOMATION MODELING

DIGITAL FABRICATION

DATA & SCRIPTING 6/7/2019

Duplicate of Duplicate of Page 1 Duplicate of Duplicate of Page 1

6/7/2019 SCRIPTING HOURS, RUN AND IMPLEMENTED SCRIPTING HOURS, RUN AND IMPLEMENTED

1,400 1,400

1,200 1,200

1,000 1,000

800 800

1280 1280 1200 1200

600 600

800 800

400 400

200 200

0 0

1200 1200

85 85

160 160

160 160

70 70

65 65 s

200 200 65 65 s

80 80

50 g50

320 320

240 240 39 39 on

60 60 36

35 t vi35

400 400

480 480

50 50

90 90

48 48

100 100

40 40 vit

40 40 ds

80 80

80 80

36 t r r r s s s s s Id er n si sis rks or ets ms u… ti… ata ke i ion ion ion ion in all ea en low rte ize int iews nt d amer eg … rica i… lations nalysis anel ng ulat on Ma er o/Revit nalysis diat on omf rt She ts er D ta l Ma ks ivis on erat on erat on Ar as ir F w In Revit cre ns po ter Clouds agra s tab lls Po ts om er V e n I R w g e r o e m u d n S e o t z a ia a b si A ly P li A ly a ti g ti m ak in e C f ta e n ti em t n re A Fl el Re r ree Im or on lou Di ra M ba ate oin nd mi lig ie t R am n ti h e g ab a cu io o e i r on Re e F ric Cal lat iew na de ane rian ula gra M Rh o/R ow na ar R dia al om Da a Sh heat er D ent al M Su divi y Genera e Genera El men assi g A eta ul P Ra o A ign V evi Ren Ai Excel In n F r Sc efil Imp evis n C r 2D Diag t W ath qu nti Site ub Cit Ge ap Ge idzone cad Fab rea alcu V w A aça e P nt T iang Dia ram l To hin had w A Sol r Ra hermal C M Pop late ree and R it a Ele n Massin m xc atio Fo hap file e R isio Fo D e e F ad ie Tr S M z Fa de A C Al o R e c D S v i a g e o T e S m l s y a e 2 h d n r E pu T ee R v e a r l n V ç r a id l F m eliz tio is S ape lat Re ion or Re P nM qu Pla Sit W So ha Di ; Excel To Cit andscap Po s r he e r M gita Faca owe Are Fa Gradient t S t o F T o T n S a e h r a G L e s at ula n e Fr Pa liz n y t l c I S i e r r d a e l d s x T P t l t n l p io a s a D ita E Sh ets nd ane as P we M ster Gi La Gr me y; g Iso Po ulat M ster To a Di eo etr ate She s A d P e p a e e G M r n m r n e t M C at tio A T e Po or Geo s a e e p r r n r C rfo tio T Ex rt ea po Pe fora Ar a Ex r m e e sto P Ar Cu tom s u C TOTAL TIME USED TOTAL USED WITHOUT SCRIPT TOTAL TIME USED TOTAL USED WITHOUT SCRIPT

DATA UNIT |Columbia University 2019.11.13

1/1 1/1

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DATA DRIVEN ENVIRONMENT DESIGN ENVIRONMENTAL SCRIPTING Modelación virtual del contexto de la Torre Santa María, la escala comunal y geográfica.

ENVIRONMENTAL SCRIPTING

SDG

PARAMETRIC SUSTAINABILITY MODELING

AMETRIC SUSTAINABILITY AUTOMATION DIGITAL ODELING FABRICATION

AEC DIGITAL FABRICATION

1. Con los resultados se obtiene el índice de oclusión urbana, el cual indica la AUTOMATION profundidad (metros) y la dirección

2. Este índice muestra las zonas donde se tiene menos oclusión urbana, es decir, una mayor profundidad (en metros) de los vectores principales.

URBAN OCCLUSION

SOLAR RADIATION

INDEX

STRATEGY

3. Con esto se distorciona el patrón hexagonal base para que las zonas de menos índice de oclusión urbana sean las de mayor apertura a la ciudad.

DATA UNIT |Columbia University 2019.11.13

STRUCTURAL TOPOLOGICAL OPTIMIZATION

* Thesis Structural Skin by JM Armijo

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DATA DRIVEN FACADE AND DIRECT SOLAR GAIN 68%

REDUCTION

ENVIRONMENTAL SCRIPTING

ENVIRONMENTAL SCRIPTING

SDG

+

=

+

=

PARAMETRIC SUSTAINABILITY AUTOMATION MODELING

AMETRIC SUSTAINABILITY AUTOMATION DIGITAL ODELING FABRICATION

AEC TYPE A

TYPE B

TYPE C

TYPE D

TYPE E

25% GLAZING

50% GLAZING

75% GLAZING

85% GLAZING

100% GLAZING

1028 UNITS

1164 UNITS

707 UNITS

1212 UNITS

341 UNITS

DIGITAL FABRICATION

DATA UNIT |Columbia University 2019.11.13

01 SOLAR EXPOSURE ANALYZING SOLAR EXPOSURE GENERATES A HEAT MAP

14

ENVIRONMENTAL SCRIPTING

YTICS

PERFORMANCE BASED ANALYSIS ENVIRONMENTAL SCRIPTING

SDG

AMETRIC SUSTAINABILITY AUTOMATION DELING

NING CS & ATION

MULTIPLE MICRO CLIMATE MAPS WITHIN ONE PROJECT

DIGITAL LARGE SCALE FABRICATION

PARAMETRIC SUSTAINABILITY AUTOMATION MODELING

AEC DIGITAL FABRICATION

VE S

3D UTCI (UNIVERSAL THERMAL COMFORT INDEX) DIAGRAM

THERMAL COMFORT URBAN MICRO CLIMATE MAP

80.75째F/26.76째C MICRO CLIMATE MAPS WITHIN DIFFERENT GEOMETRIES

DATA UNIT |Columbia University 2019.11.13

81.69째F/27.60째C

* Analysis by Juan Guarin

15

DIGITAL FABRICATION WITH ON-SITE MATERIALS ENVIRONMENTAL SCRIPTING ENVIRONMENTAL SCRIPTING

NASA'S 3D-PRINTED MARS HABITAT CHALLENGE PHASE 1

3D MODEL SDG

RAMETRIC SUSTAINABILITY AUTOMATION AUTOMATION PARAMETRIC SUSTAINABILITY ODELING MODELING

DIGITAL DIGITAL FABRICATION FABRICATION

AEC

DATA UNIT |Columbia University 2019.11.13

16 * N3ST Proposal by Up team and JMA

DATA ANALYTICS

ENVIRONMENTAL SCRIPTING

DATA PROGRAMMING

DATA MINING ANALYTICS & VISUALISATION

PREDICTIVE ANALYTICS

LARGE SCALE

PARAMETRIC SUSTAINABILITY AUTOMATION MODELING

DIGITAL FABRICATION

HOW DATA CAN ACCELERATE THE ADOPTION OF SDG’S IN THE AEC INDUSTRY?

DATA UNIT |Columbia University 2019.11.13

17

DATA ANALYTICS

ENVIRONMENTAL SCRIPTING

DATA PROGRAMMING

DATA MINING ANALYTICS & VISUALISATION

PREDICTIVE ANALYTICS

LARGE SCALE

PARAMETRIC SUSTAINABILITY AUTOMATION MODELING

DIGITAL FABRICATION

AS A CONSEQUENCE OF RIGOROUS DATA MODELING AND SCRIPTING WORKFLOWS

DATA UNIT |Columbia University 2019.11.13

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ISHOULD I AUTOMATE THIS?

IHOW COULD WE IMPROVE DESIGN

RY

ALSO, PROMOTING A SCRIPTINGPECOMMUNITY AWARE OF THE SDGS DU AMBASSADOR

DATA UNIT |Columbia University 2019.11.13

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