impulse 1: technology skills for real estate professionals · impulse 1: technology skills for real...

Impulse 1:

Technology Skills for Real Estate Professionals

Source: fotolia.de; ERES.

Mario Bodenbender M.Sc.

PhD Candidate

TU Kaiserslautern, Real Estate Studies

Source: ADBE/ST. 2

Digital InstrumentsSoftware – Technology – Methods

3Source top: shutterstock; ADBE/ST, DHL, WinSun, TU Kaiserslautern.Source bottom: ADBE/ST, ADBE/ST, G. Schroth/TUM, Wearable Intelligence in Energy, HRP-3 by Kawada Industry.

Technological Transformation

Big Data/Business Intelligence

AI (Machine Learning/ Deep Learning)

Drones 3D Concrete Printing BIM

Blockchain IoT/Smart City Indoor Mapping VR/AR Robots

4Sources: D&S; Wassermann, Uwe (2014).

Digital Planning, Construction and Operation

5

DigitalisationAcceleration of processes

6Source: Wassermann, Uwe (2014).

BIM

7Source: Wassermann, Uwe (2014) (left); https://www.curbed.com/2016/6/28/12053256/3d-printer-concrete-construction-netherlands (right).

3D Concrete Printing

https://www.curbed.com/2016/6/28/12053256/3d-printer-concrete-construction-netherlands

8Sources: TechXplore, thejapantimes, robots.net.

Robots

9Sources: http://www.aerial9.com/2017/10/07/drones-construction-companies/; https://www.geospatialworld.net/blogs/drones-to-propel-new-technological-innovations-in-the-construction-industry/.

Drones

http://www.aerial9.com/2017/10/07/drones-construction-companies/

10Source: Drogemuller, Robin (2014).

3D-Scan/ Indoor Mapping

Reality

3D-Scan

Pointcloud

3D-Model

11Source: Wassermann, Uwe (2014).

Scan to BIM – Reality Capture

12Sources: Drogemuller, Robin (2014), ADBE/ST (top right).

Virtual Reality and Augmented Reality

13Source: Bitkom (2014).

IoT/Smart CityGrowth curve of networked devices

Desktop-PC Mobile Computing Internet of Things Internet of Everything

Bil.

Bil.

14

Blockchain

15Sources: Lets talk Payments (2015).

BlockchainFields of application

Certificates of authenticity

Supply chain control

Smart-Contracts

Land register entry

16Sources: Architrave (left); Weber, Rainer (2012).

Digital Real Estate Management

17

Digital Real Estate Management

CAFM/IWMS, CMMS, Energy-Management-Systems, Building-Automation-Systems

CAD, GIS, BIM

ERP, CRM, Business Intelligence, Collaboration Tools

Portfolio-Management-Systems, Systems for Rental Contract

Document-Management-Systems, Project/ Data Rooms

18Source: Shiller, Robert J. (2005).

The power of creative destruction/ disruption

Source: ADBE/ST. 19

Artificial Intelligence in Real Estate

Big Data – Smart Data – Data Analysis

20

Big Data/Business Intelligence

1999 2018• 1 Byte = 8 Bit = 23 Bit (1 alphanumerisches Zeichen 0, 1,…A, B,…)

• 1 Kilobyte = 1024 Byte = 210 Byte = 213 Bit ~ eine Viertel Druckseite

• 1 Megabyte = 1024 x 1024 Byte = 220 Byte ~ 106 Byte = 1.000.000 Byte (500 Textseiten)

• 1 Gigabyte = 1024 Megabyte = ~109 Byte (selbst als USB-Stick kein großzügiges Geschenk mehr)

• 1 Terabyte = 1024 Gigabyte = ~1012 Byte (10 TByte lassen sich 2016 mit dem PMR-Aufzeichnungsverfahren auf Festplatten speichern)

• 1 Petabyte = 1024 Terabyte = ~1015 Byte (immer noch ein hoch kapazitives Speichersystem, erste Objektspeichersysteme mit 4,7 PByte Fassungsvermögen passen in ein 19-Zoll Rack; dank 15 TByteKapazität reichen nun 66 SSDs im 2,5-Zoll Format aus, um 1 Petabyte Daten zu speichern.)

• 1 Exabyte = 1024 Petabyte =~1018 Byte (1350 Petabyte waren 1998 die Größenordnung „menschlichen Wissens“, heute sind es geschätzt mehrere Hundert Exabyte)

• 1 Zettabyte = 1024 Exabyte =~1021 Byte (angeblich speichert die NSA Datenmengen von mehreren Zettabyte)

• 1 Yottabyte = 1024 Zettabyte =~1024 Byte (100 Milliarden Festplatten zu 10 TByte)

Sources: Cisco Systems, Inc. (1999), CCNA Semester 1; Graefen, Rainer (2017).

21

• Many data are not necessarily Big Data…

Big Data

Source: Bitkom (2015), https://www.iflscience.com/technology/how-much-data-does-the-world-generate-every-minute/, last checked 27th November 2018.

https://www.iflscience.com/technology/how-much-data-does-the-world-generate-every-minute/

22

• … and neither automatically Smart Data.

Smart Data

23Source: quora.com/How-are-AI-and-ML-different-and-what-could-be-a-possible-Venn-diagram-of-how-AI-and-machine-learning-overlap, last checked 27th November 2018.

AI and Data Analysis

24Source: http://www.hansonrobotics.com/robot/sophia/

Do you know Sophia?

http://www.hansonrobotics.com/robot/sophia/

25Source: Google I/O 2018 (Google Duplex Restaurant Call)

Do you know Google Duplex?

Source: ADBE/ST. 26

PartneringAI – RE Professionals

27

Can AI also develop …• Curiosity, creativity? Yes, for sure.• Sensations (feelings, emotions)?

Already more difficult ...• Conscience? • Consciousness?

AI can take over duties. But (ultimately) noresponsibility (e.g. in real estate management).

“Download“ of leadership skills?

Sources: DHL (center), 3x ADBE/ST.

The Limits of AI

28

What skills will be required to perform against machines?

• Programming/ Coding

• Machine Learning

• Data Visualization

• Information (Cyber) Security

• UI/UX Design

Real Estate Professionals: Demand for Technology Skills

Source: Pexels.

29

Real Estate Professionals: Extent of Technology Skills

Source (right): https://www.quora.com/.

To what extent will skills be required toperform against machines?

• Programming/ Coding (348 programming languages)

Computer science (curriculum):• Mathematics

• Analysis• Stochastic• Linear algebra

• Basics of computer science• Algorithms• Data structures• Formal languages• Object orientation

• Computer Engineering

30

To what extent will skills be required toperform against machines?

• Programming/ Coding (348 programming languages)

Things to know for non programmers:• Knowing concepts about programming• Quick, specific and efficient communication is important• Providing context about why things are important is relevant• Programming is time consuming• Things can appear to be easier to implement than they are• Developing customized software must be the last choice• Code should be as simple as possible• Best programmers use off the shelf libraries and frameworks• Securing software is difficult and expensive


Sources: Stack Overflow, GitHub, TIOBE, Stack Overflow.

31

To what extent will skills be required to performagainst machines?


• Machine Learning (39 software suits; 32 methods for supervised learning)

Relevant for Real Estate Professionals:• Requirements for the application of ML?• Limits of algorithms?• Reasons for failure (bias)?• Possibilities for optimization?• Relevance and context of data?


Source: Pexels, Twitter.

32




• Data Visualization(common mistakes)


Source: http://viz.wtf.

33





• Information (Cyber) Security (Data Privacy, IT Security, Corporate Governance)


Source: Pexels.

34





• Information (Cyber) Security

• UI/UX Design(Decision-makers for the selection and implementation of a RE software system)


Source: Pexels.

35Source top: shutterstock; ADBE/ST, DHL, WinSun, TU Kaiserslautern.Source bottom: ADBE/ST, ADBE/ST, G. Schroth/TUM, Wearable Intelligence in Energy, HRP-3 by Kawada Industry.

Real Estate Professionals: Technology Skills

Data Quality (consistency and integrity)

Avoidance of Data Loss

Data Persistence

36Source: Data rooms.

Real Estate Professionals: Quality Assurance and Avoidance of Data Loss

Source: Christoph Sickinger.

Thank you!

impulse 1: technology skills for real estate professionals · impulse 1: technology skills for real...

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