Data-Driven Analysis of Building Use

Manuel Weber, Eshref Januzaj, Peter Mandl

Munich University of Applied Sciences,Department of Computer Science and Mathematics

Data-Driven Analysis of Building Use

IEECB & SC 2020, December 1-2

Agenda

IEECB&SC‘20 / Weber, Januzaj, Mandl


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• NuData Campus Project

• Idea: Data Mining for Building Analysis

• Knowledge Generation from…

‒ Static Data

‒ Dynamic Data

NuData Campus Project

• 3-year research project

• Analysis of energy demand in complex building structures

• Case study in a German university building

IEECB&SC‘20 / Weber, Januzaj, MandlData-Driven Analysis of Building Use

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Faculty building of the department of Mathematics and Computer Science in Munich, Germany

Idea: Data Mining for Building Analysis



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(x1, x2, x3, x4, x5) Parametrisation Data Mining

Knowledge




5

Data

Inte

gra

tion




6

Data

Inte

gra

tion




7

Data

Inte

gra

tion




8

Data

Inte

gra

tion




9

Pa

tte

rn S

ea

rch

(Clu

ste

rin

g)

Data

Inte

gra

tion

Static Data – Clustering of Office Rooms by Area and Perimeter



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Area

Pe

rim

ete

r

Static Data – Clustering of Office Rooms by Area and Perimeter



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Area

Pe

rim

ete

r

Static Data – Room Types

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Offices

Classrooms

Bathrooms

Labs

Ro

om

usa

ge

acco

rdin

gto

DIN

27

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Number of rooms

Live and Stay

Storage Rooms



Static Data – Classification of Rooms by Area and Perimeter

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Offices

Classrooms

Bathrooms

Labs

Ro

om

usa

ge

acco

rdin

gto

DIN

27

7

Number of rooms

Classifier Accuracy

SupportVectorClassifier 0.7578

KNeighborsClassifier 0.8323

DecisionTreeClassifier 0.8323

RandomForestClassifier 0.8447

Live and Stay

Storage Rooms



Static Data – Classification of Rooms by Area and Perimeter

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NF2 Office

NF5 Classroom NF1 Live and Stay

NF3 Laboratory

NF7 Bathroom



Dynamic Data – Wifi Access Data



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Contact Fair Lectures Not in use

eduroam public WiFi

Dynamic Data – Room Types



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Number of rooms

Ro

om

usage

accord

ing

toD

IN277

Dynamic Data – Example: Convolutional Neural Network (CNN) Classification



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Co

nv1

D

Co

nv1D

MaxP

oo

lin

g1D

Fla

tten

Fu

lly

Co

nn

ecte

dL

ayer

Fu

lly

Co

nn

ecte

dL

ayer

Ou

tpu

t L

ayer

Convolutional Neural Network

0 Teaching Room

1 Study Room

Dynamic Data – Example: Convolutional Neural Network (CNN) Classification



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Co

nv1

D

Co

nv1D

MaxP

oo

lin

g1D

Fla

tten

Fu

lly

Co

nn

ecte

dL

ayer

Fu

lly

Co

nn

ecte

dL

ayer

Ou

tpu

t L

ayer

Convolutional Neural Network

0 Teaching Room

1 Study Room

Accuracy 0.7257 (std. 0.0229)

ROC AUC 0.6455 (std. 0.0126)

PR AUC 0.2898 (std. 0.0166)



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Thank you for your attention!

Backup: DIN 277 - Categorization of the Net Floor Area in Buildings

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Net Floor Area (NF)

Effective Area (NF 1-7) Functional Area (NF 8) Common Area (NF 9)

NF 1 Live & Stay

NF 2 Office Work

NF 3Production etc.

NF 4 Storage

NF 5 Education &

Culture

NF 6 Health & Care

NF 7Other

711 Bathroom719 Cleaning Room

…

513 Lecture Hall521 Classroom523 Practice Room533 Media Room535 Technical Practice Room

…

322 Metal Workshop323 Electrical Workshop353 Chem./Techn. Laboratory382 Kitchen

…

211 Office Room231 Meeting Room

…

120 Common Room123 Children‘s

Playroom135 Quiet Room152 Dining Hall

…



411 Storage Room…

612 First Aid Room

Backup: Classifier

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Support Vector Machine K-Nearest Neighbors

Decision Tree Random Forest

k=3

perimeter > 20 ?

area > 25 ?

area < 100 ?

…

…

…

Voting

Dataset



Backup: Area Under the Curve (AUC)

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ROC AUCReceiver-Operating-Characteristic

PR AUCPrecision-Recall



1

10False Positive Rate

Tru

e P

ositiv

e R

ate

1

10Recall

Pre

cis

ion

AUC=1 AUC=1

𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛 =Σ True positives

Σ Predicted positives

𝑅𝑒𝑐𝑎𝑙𝑙 =Σ True positives

Σ Total positivesFalse Positive Rate =

Σ False positives

Σ Total negatives

True Positive Rate =Σ True positives

Σ Total positives

Backup: Building Data Integration

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Dynamic Data

CAFM System Wifi Access Points

Building Plans (CAD)Sensor Data

Integrated

Building

Data

Static Data

Data Mining



Data-Driven Analysis of Building Use

Documents

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