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=Sandbox=
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==Artificial Intelligence for Built Environment (AIfBE)==
[https://en.wikipedia.org/wiki/Artificial_intelligence Artificial intelligence] has tremendous potential to reduce energy, operational costs and carbon emissions, while ensuring occupant comfort, and resilience of buildings and communities. However, there is currently much speculation and lack of understanding about what AI can ''actually'' achieve. The result is a certain mistrust and perceived risk in implementation.
This wiki/paper aims to demystify AI and provide ‘best practice’ examples of ''real-world applications'', so that these may be better understood, and applied with confidence by municipalities, developers, and building owners.
Our environment is increasingly being driven by our use of technology. This explains the interest in smart cities and smart buildings. While '''smart buildings''' are focused on meeting occupants’ needs for wellness, comfort, and productivity, the aim of '''smart cities''' is to link people and businesses to effective and efficient infrastructure such as secure and resilient power and water, multi-modal transportation, land use and waste management.
Cities and buildings generate a vast amount of data, which in-and-of-itself is of little use unless it can provide useful insights. This is where AI can offer a useful tool to achieve a better integration of smart buildings, smart city infrastructure, connected businesses, and people.
[[Image:Fig1.png|center|top]]
<div style="text-align:center;">'''Figure 1. Interfaces within the city fabric'''</div>
Artificial Intelligence (AI) has several subfields such as [https://en.wikipedia.org/wiki/Machine_learning Machine Learning (ML)] , which can make predictions and decisions, and execute operations without being explicitly programmed to do so; and [https://en.wikipedia.org/wiki/Natural_language_processing Natural Language processing], which allows machines to read and understand human language and enable user interface.
These tools can help municipal planners, building owners and occupants to optimize the performance of buildings and interface with city infrastructure. The following table summarizes how different stakeholders can benefit from AI capabilities.</span>
{| style="border-spacing:0;"
|- style="background-color:#7f7f7f;border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;"
| align=center style="color:#ffffff;width:16.5%;"| '''Municipal (policy making at county/city level)'''
| align=center style="color:#ffffff;width:16.5%;"| '''Municipal (operations & purchasing at county/city level)'''
| align=center style="color:#ffffff;width:16.5%;"| '''Large owners and Managers (portfolios)'''
| align=center style="color:#ffffff;width:16.5%;"| '''(Institutional) Asset managers(pension funds/ insurance)'''
| align=center style="color:#ffffff;width:16.5%;"| '''Medium to small building owners (single buildings)'''
| align=center style="color:#ffffff;width:16.5%;"| '''People/ Community'''
|-
! colspan="6" style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.45in;text-align:left;" |BUILDINGS
|-
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" | <span style="color:#000000;">[[Sandbox#Optimizing Performance of Smart Buildings|Optimizing Performance of Smart Buildings]]</span>
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" | <span style="color:#000000;">[[Sandbox#Optimizing Performance of Smart Buildings|Optimizing Performance of Smart Buildings]]</span>
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" | <span style="color:#000000;">[[Sandbox#Optimizing Performance of Smart Buildings|Optimizing Performance of Smart Buildings]]</span>
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |
|-
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |<span style="color:#000000;">Data Analysis and Predictions</span>
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" | 
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" | <span style="color:#000000;">Data Analysis and Predictions</span>
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" | 
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |
|-
! colspan="6" style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.0in;text-align:left;" |URBAN INFRASTRUCTURE AND UTILITIES
|-
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |<span style="color:#000000;">Data Analysis and Predictions</span>
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" | 
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" | <span style="color:#000000;">Data Analysis and Predictions</span>
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" | 
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |
|-
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |<span style="color:#000000;">Smart Grid, Transactive Energy and Renewables</span>
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |<span style="color:#000000;">Smart Grid, Transactive Energy and Renewables</span>
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" | 
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" | 
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |
|-
|-
! colspan="6" style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.0in;text-align:left;" |TRANSPORTATION
|-
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |<span style="color:#000000;">Data Analysis and Predictions</span>
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |<span style="color:#000000;">Shared Mobility</span>
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" | 
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" | 
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |<span style="color:#000000;">Shared Mobility</span>
|-
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |<span style="color:#000000;">Autonomous Vehicles/Drones</span>
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |<span style="color:#000000;">Autonomous Vehicles/Drones</span> 
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" | 
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |
|-
! colspan="6" style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.0in;text-align:left;" |RESILIENCY
|-
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |<span style="color:#000000;">Data Analysis and Predictions</span>
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |<span style="color:#000000;">Operational Awareness</span>
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" | 
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" | 
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |<span style="color:#000000;">Notification/Awareness</span>
|-
! colspan="6" style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.0in;text-align:left;" |BEHAVIOUR CHANGE AND INDIVIDUAL ACTION
|-
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" | 
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" | 
| style="border:0.5pt solid #000000;padding-top:0in;padding-bottom:0in;padding-left:0.075in;padding-right:0.075in;" |<span style="color:#000000;">Behaviour Change and Individual Action</span>
|-
|}
==Optimizing Performance of Smart Buildings==
{|| class="wikitable" style="width: 25%; float:right; margin-left: 20px;" cellpadding="10"
|style="background-color:#4472c4; text-align:center;" |'''Raiffeisen Tower'''
|-
|[https://passivehouseplus.ie/blogs/world-s-first-passive-house-office-tower-certified Raiffeisen Tower]’s energy concept is compelling: Energy is provided by a photovoltaic system and a combined heat, cooling and power plant.
Even the waste heat from the data center is re-used, with cooling partly coming from the Danube canal.
The decisive factors in reducing energy consumption is the radically increased efficiency of the facade, building component connections, and the mechanical systems in combination with optimized shading equipment.
|}
Buildings can improve energy performance and decrease operation cost and their carbon footprint through energy-efficient design and smart control systems capable of monitoring, analytics, and diagnostic of the building’s operations.
Many examples, such as the [http://www.plparchitecture.com/the-edge.html EDGE] in Amsterdam, [http://www.plparchitecture.com/22-bishopsgate.html 22 Bishopsgate] in London, and [https://passivehouseplus.ie/blogs/world-s-first-passive-house-office-tower-certified Raiffeisen Tower] in Vienna, demonstrate that new high-rise buildings can achieve as much as 80% of energy savings compared to conventional high-rise buildings through the heating and cooling demand reduction.
However, the bulk of the building stock is existing. Retrofitting them with energy conservation measures such as autonomous optimization of existing Heating, Ventilation, and Air Conditioning (HVAC) control systems for maximum impact on energy consumption could reduce emissions by about 30–60% <ref name="ftn1">[https://www.researchgate.net/publication/223028526_European_residential_buildings_and_empirical_assessment_of_the_Hellenic_building_stock_energy_consumption_emissions_and_potential_energy_savings European residential buildings and empirical assessment of the Hellenic building stock, energy consumption, emissions and potential energy savings]<span style="color:#000000;">) </span></ref>.  The greatest challenge is not the technology but how to persuade the owners to install the smart technology and retrofit the buildings. Can AI help to reduce emissions of those buildings?
{|| class="wikitable" style="width: 25%; float:right; margin-left: 20px;" cellpadding="10"
|style="background-color:#4472c4; text-align:center;" |'''Sidewalk Quayside'''
|-
|[https://www.sidewalktoronto.ca/Sidewalk Quayside]is a Toronto project that proposed to cut GHG emissions by 89% through energy and mobility initiatives, starting with energy-efficient building design and digital management tools. Sidewalk believed in pushing the smart building systems management beyond simple analytics and diagnostics to a self-managed system, based on the ‘DeepMind’ [https://deepmind.com/blog/article/deepmind-ai-reduces-google-data-centre-cooling-bill-40 AI technology used to reduce Google’s Data Centre] cooling bill by 40%. 
|}
Smart buildings use analytic and diagnostic systems that send data from the Building Automation System (BAS) to an analytical engine in the cloud, which process the data according to certain set rules, displays performance data, and even provides instructions and work-orders to building operators to help them optimize the building performance. Such systems are typically capable of reducing carbon emissions by 16-25%.
A significant reduction of carbon emissions can be achieved by regulating the ventilation air and temperature based on the occupancy. For example, there is no point heating and cooling the building where the is no one inside. The occupant density monitoring is being highlighted in the time of COVID, when it is important to know that a “social distancing” can be maintained. The AI programs <ref name="ftn2">[https://www.spacent.com/ Spacent is a Finnish prop-tech company specialised in enabling more effective space resource use of corporate and institutional clients]<span style="color:#000000;">) </span></ref> can monitor the building occupancy density and inform the BAS which spaces are being occupied, at what density so that the appropriate amount of air, heat, and cooling can be delivered to that space. This increases efficiency, flexibility, sustainability, and resilience, optimize services and enhance the human experience.
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Revision as of 18:07, January 10, 2022

 Has author
Active TransitWilfred Pinfold
Age-Inclusive CommunitiesWilfred Pinfold
AgroforestryWilfred Pinfold
Artificial IntelligenceWilfred Pinfold
Autonomous VehiclesWilfred Pinfold
Skip Newberry
Jeff Allen
Ken Montler
Joe Cortright
Greta Knappenberger
Jill Sorensen
John Feo
Jose Gonzalez
Geoffrey Urbach
Corey Marshall
Timothy Smith
Benefit, Value and Return on Investment (ROI) ConsiderationsBenson Chan
Renil Paramel
Benefits and Cybersecurity and Privacy RisksLan Jenson
David Balenson
Adnan Baykal
Gary Dennis
Wayne Dennis
Damon Kachur
Benny Lee
Carmen Marsh
Aleta Nye
Carmen Parada
Renil Paramel
Bill Pugh
Maryam Rahmani
Carter Schoenberg
Sushmita Senmajumdar
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Dean Skidmore
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Paul Wertz
Peter Wong
Edward Walker
Business ContinuityWilfred Pinfold
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Skip Newberry
Jeff Allen
Ken Montler
Joe Cortright
Greta Knappenberger
Jill Sorensen
John Feo
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Geoffrey Urbach
Corey Marshall
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Case StudiesDavid Witkowski
Anton Batalla
Essam El-Beik
Benny Lee
Bill Pugh
Steve Wimsatt
Case Study Summary Findings & DiscussionDavid Witkowski
Anton Batalla
Essam El-Beik
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Bill Pugh
Steve Wimsatt
City ResilienceJiri Skopek
Communications NetworksWilfred Pinfold
Communications and BroadbandBill Pugh
Wilfred Pinfold
Community DevelopmentWilfred Pinfold
Community EngagementWilfred Pinfold
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Considerations for Deploying Municipal IoTDavid Witkowski
Anton Batalla
Essam El-Beik
Benny Lee
Bill Pugh
Steve Wimsatt
Cybersecurity and Privacy Risk ManagementColin Dunn
François Bégin
Cybersecurity for Smart BuildingsColin Dunn
François Bégin
Data SovereigntyWilfred Pinfold
Designing and Implementing a Resilient Smart Public Safety ProgramBrenda Bannan
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Michael Dunaway
Dean Skidmore
Digital TwinsWilfred Pinfold
Disaster RecoveryBrenda Bannan
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Stan Curtis
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Geoffrey Urbach
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Anton Batalla
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GlossaryBrenda Bannan
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History of Public WiFiDavid Witkowski
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Steve Wimsatt
HyperloopWilfred Pinfold
Impacts to Municipal Governments of IoT NetworksDavid Witkowski
Anton Batalla
Essam El-Beik
Benny Lee
Bill Pugh
Steve Wimsatt
InfrastructureWilfred Pinfold
Intelligence AugmentationWilfred Pinfold
Intelligent BuildingWilfred Pinfold
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