Esitetty Green Building Council Finlandin Vihreä Foorumi -seminaarissa 26.3. Katso videotaltiointi: https://vimeo.com/123925929

1. Rakennusten internet:
mitä on nyt ja mihin ollaan menossa?
Miimu Airaksinen
Tutkimusprofessori
VTT Technical Research Centre of Finland

2. 26/03/2015 2
Drivers for change

3. 26/03/2015 3
Smart Buildings as a part of energy network
 To enable sustainable urban life
through rationalization in the use of
resources while increasing comfort in
urban environments by means of
embedded technology and integration
technologies within residential and
commercial buildings
 To achieve greater efficiency in use of
resources, prioritizing energy, more
flexibility in the provision of resources
and better situation awareness for the
citizen and for service and infrastructure
owners

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Toimivuuskriteerien taso ulkoilmasta ja sisäilmaan
• Ulkoilmaan ei juurikaan voida vaikuttaa
• Sisäilmalle ehdottomat vaatimustasot
• Rakenne ilmatilojen välissä – ulkopinnat altistuvat eniten
kosteusrasituksille
• Monitorointi rakenteessa jo
rakentamisen/kuljetuksen
aikana
• Kiihtyvyys ja T/RH anturit

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Adaptive buildings
self-learning building automation connect to energy networks
VTT innovation program Ingrid+
http://www.vttresearch.com/impact/new-innovations-are-here/innovation-programmes/intelligent-energy-grids
Intelligent energy networks and smart cities http://www.vtt.fi/inf/pdf/researchhighlights/2015/R12.pdf

6. 26/03/2015 6

7. Tuotannon ja kulutuksen eriaikaisuus
missmatch tuntitasolla
Nollaenergiapientalon tuntitason käyttäytyminen. Kokonaiskulutus
8400 kWh/a (laitteet+lämmitys). PV 60 m2
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
1 825 1649 2473 3297 4121 4945 5769 6593 7417 8241
Vuoden tunnit
Sähköteho(W)
Verkosta/akuista (W)
Verkkoon/akkuihin
Kokonaiskulutus (laitteet + lämmitys) 8400 kWh/m2. 10 kW PV (60 m2)Power,W
Hours
Syöttö
verkkoon/akkuihin
Otto
verkosta/akuista
=> Smart management (peak shifting and shaving)

8. 26/03/2015 8
Online forecasting of building energy consumption
• Forecasting is based on
open weather data or
forecast data by Finnish
Meterology Institute
(FMI)
• Web service based
solution (no user
interface is needed, easy
integration with other
applications)

9. 26/03/2015 9
Cooling of the building in the case of power or district
heating system failure
• Online forecasting of the
cooling of the building in
the case of power or district
heating system failure
• Forecasting is based on
open weather / forecast
data by Finnish Meterology
Institute (FMI)
• Web service based solution
(no user interface is
needed, easy integration
with other applications)

10. 26/03/2015 10
By integration of sensors
and wireless connectivity
to lampsEnhancing lighting with new functionalities and
low cost connectivity
VTT program pro-IoT
http://www.vtt.fi/research/spearhead_iot.jsp?lang=en
Productivity leap with IoT http://www.vtt.fi/inf/pdf/visions/2013/V3.pdf

11. 26/03/2015 11
Enriching data to information and
supporting decision making
Data from different sources creating new
business and services opportunities

12. 1226/03/2015 12
Data from different sources creating new
business and services opportunities
E.g. Quicker to track
and locate problems in
power lines by
combining sensor and
social media data. Also
end-user satisfaction
higher due to quicker
response and
information flow (people
know that problems
solving has started)

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Progress monitoring
Smart City key performance indicators

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Performance measurements and visualisations

15. Building Level Performance Measurements & Visualisations

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Indoor environment quality (IEQ) index

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Building Maintenance
Project DigiSpaces
 Mobile AR visualization and interaction with Building
Information Models (BIM) & service book
 Applications: building's life cycle services, e.g.
maintenance & repair
 Partners: Skanska, Granlund, Pöyry, Tekla, Solibri
Functionality
 Navigation to service targets
 Highlighting targets in camera view
 Opening targets by clicking in camera view
 “X-ray vision”, seeing targets behing walls etc.
Generalizations
 Public places, consumers, PoIs, IoT
 Interactions between physical and digital
See video

18. 26/03/2015 18
Understanding user preferences
• Human thermal model to estimate better thermal comfort and to crease
demand based control of temperatures
• Human behavior patters to forecast building energy demand

19. HTS – Fusion Sensor
Proof-of-Concept Application – Simple HTM Calculation, version 1.70
• Case configuration (space and occupant data)
• IoT sensor data (input)
• On-line Human Thermal Model (HTM) calculation
• HTM controller output
Demand-controlled thermal
indoor environment

20. 26/03/2015 20

21. 26/03/2015 21
People flow, VTT FlowRadar

22. 26/03/2015 22
People behaviour monitoring and classification

23. Combining data from various sources

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BIM-based interfaces
Monitoring
District E. management services
BIM based energy management services
• Smart meters: peak energy demand can be reduced by
different tariffs
• Building automation: Building automation is controlling the
indoor environment based on weather, user occupancy and
user preferences, self-learning systems

25. 26/03/2015 25
World Browsing
Location based information in mobile AR view
 Points of interest, social media, mobile advertising
VTT solutions
 Accurate 3D tracking solution based on 3D point clouds,
developed for Nokia (Navteq True data, CityLense)
 Also, Mobile CityGuide, developed for Sanoma News
(local events, Metro newspaper content)

26. 26/03/2015 26
Responsive eco-efficient environment
Embedded
sensors are
warning mother:
Little Raipe is
moving towards
busy road
Integrated energy
production and
weather forecast
system informs
father:
Put the washing
machine on, since
non polluting solar
energy is available
now.
Enabling technology IoT, internet of things

27. 26/03/2015 27
Cities transformation
Given urbanisation trends, on-going transformations towards
increasingly knowledge-intensive economies as well as their growing
share of resource consumption and emissions, cities are becoming even
more of a focal point for our economies and societies at large.
To meet public policy objectives under these circumstances, cities need to
change but in times of tight budgets this change needs to be achieved in
a smart way: cities need to transform themselves into 'smart cities'.

28. 26/03/2015 28
A city has many systems and sub systems which are interlinked and
interconnected
A change in one place will affect on the whole system
→System dynamic model for a city
Population
District
Attractiveness
Available services
and jobs
Available dwellings
- -
Buildings
construction
+
+
Demolition
Buildings age
-
+
+
Births Deaths
+
+
+
-
+
+
-
Travelled distance
-
-+
- +/-
-
Congestion
+
-
-
-
Roads
construction
+
-
- +
Energy use
Materialuse
Environmental
impacts
CityPlan
Weight factors
Materialrecovery
strategies
Localenergy
production
Public transport
policies

29. 26/03/2015 29
Smartness requires an integrated approach
VTT’s research programs for smart cities:
Tackling challenges in a systemic way
Intelligent Energy Systems and smart cities
Productivity Leap with Internet of Things
Smart Mobility integrated with Low Carbon Energy

30. 26/03/2015 30http://www.vtt.fi/inf/pdf/researchhighlights/2015/R12.pdf
http://www.vttresearch.com/impact/new-innovations-are-here/innovation-
programmes/intelligent-energy-grids

31. TECHNOLOGY FOR BUSINESS