impulse 1: technology skills for real estate professionals · impulse 1: technology skills for real...
TRANSCRIPT
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
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
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.
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?
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
Real Estate Professionals: Extent of Technology Skills
Sources: Stack Overflow, GitHub, TIOBE, Stack Overflow.
31
To what extent will skills be required to performagainst machines?
• Programming/ Coding
• 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?
Real Estate Professionals: Extent of Technology Skills
Source: Pexels, Twitter.
32
To what extent will skills be required to performagainst machines?
• Programming/ Coding
• Machine Learning
• Data Visualization(common mistakes)
Real Estate Professionals: Extent of Technology Skills
Source: http://viz.wtf.
33
To what extent will skills be required to performagainst machines?
• Programming/ Coding
• Machine Learning
• Data Visualization
• Information (Cyber) Security (Data Privacy, IT Security, Corporate Governance)
Real Estate Professionals: Extent of Technology Skills
Source: Pexels.
34
To what extent will skills be required to performagainst machines?
• Programming/ Coding
• Machine Learning
• Data Visualization
• Information (Cyber) Security
• UI/UX Design(Decision-makers for the selection and implementation of a RE software system)
Real Estate Professionals: Extent of Technology Skills
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!