VET4SBO Level 1 module 4 - unit 3 - v0.9 en

ECVET Training for Operatorsof IoT-enabledSmart Buildings (VET4SBO)
2018-1-RS01-KA202-000411
Level 1
Module 4: Basics for the operation of smart building
using IoTs to improve the flexibility and the intelligence
in satisfying human comfort and/or energy efficiency
Unit 4.3: Flexibility and intelligence in smart buildings

Outline
1. Introduction to combining IoTs functions and solutions in
building operation
2. Utilise certain IoT capabilities across functionalities /
modalities of a building
3. Use cases presenting added flexibility for increased building
intelligence
4. Discussion on new creative methods of demonstrating the
flexibility

Intelligent IoT integration in Smart Buildings
Building value is not anymore (only) about location.
New value streams and revenue streams are created by information-based
applications, which have the potential to attract building
customers/occupants by differentiating from competitors in terms of
performance against QoS criteria.
IoT is a key driver of information-based applications, as it can take the
building beyond traditional building automation features and enable
dramatically more efficient building operations, enhanced occupants’
relationships, even new revenue generation opportunities for building
owners.

Building direct relationships with building users is of mutual benefit. For
instance, a shopping mall equipped with sensors and interaction/actuation
facilities helps owners intelligently adapt to the needs of their customers,
thus building trust.
A simple example are the smart devices that regulate temperature, humidity
and light based on occupants’ preferencesand building air condition.
IoT-enabled building management systems (BMS) have great potential to turn
building performance more efficient and enhance occupants’ experience
through heterogeneous measurements,analytics and decision support
features.

IoT objects utilise the internet protocols to communicate data about their
location, condition, provided service, etc.
Building operators (and building owners) first need to understand the
capabilities of various types of sensors to measure properties like motion, air
pressure, light, temperature,water flow, etc. Then, they need to understand
the separate capability to communicate the data to some processing units,
either locally or remotely located, and subsequently process and analyse it to
make sense and generate actions towards human or other devices.

Sensing, as well as data communication and storage costs, are gradually decreasing
and this allows building operators to focus on the added-value applications that
would intelligently analyse and combine the collected information, removing any
hard-integration barriers.
Potentially all physical objects will be able to share information about themselves
and about their function. Therefore, building operators will now be focusing on the
usage/business processes implemented by the building occupants and try to figure
out (with the support of smart algorithms as well) how to use the available data
and information to improve the processes in terms of cost, efficiency, comfort, etc.
Value creation may be hidden within the details of combining existing information.

[Source:Jim Young, “BIoT—BUILDING Internetof Things™,” Realcomm, January 23, 2014; Deloitte Center for Financial
Services analysis.]

[Source:Deloitte Center for Financial Services]
Different types of sensors monitoring
motion, pressure, light, temperature,
and (liquid) flows generate vast
amount of data around building
operations and the environment.
The data are transported through
communication networks available in
the building.
They are then processed and
structured on a real-time basis, so as
to create useful information.

[Source:Deloitte Center for Financial Services]
The aggregatedinformation is
analysed using intelligent machine
learning and data mining algorithms to
generate knowledge and insights for
building operators decision support.
The loop closes with the automated
actionable decision related to
monitoring and control various
building properties.
The whole of the process depends on
the real needs of building services.

IoT capabilities across functionalities/modalities of a
building
Building equipped with a legacy BMS
It usually automates individual functions, such as lighting control
or HVAC monitoring and control. In order to perform any higher
level reasoning, building operators must collect separate data
sets, aggregate manually and analyse separately with different
systems.

building
Building equipped with a BMS, which implementspartial
integration betweenfunctions
More recently developed BMS are able to combine automation
tasks across building functions, to achieve better performance,
e.g. for energy efficiency. This way, data are partially integrated
at system level and decision making becomes more effective.

building
Building equipped with an IoT-enabled BMS, allowing full integration of
functions
It has been discussed that such systems allow building operators to focus on
the customer/occupant needs and avoid any data/services integration
concerns. All building functions are monitored and controlled through a
single low-cost integrated infrastructure, aggregating and analysing all diverse
data sets.
The automatic combination of data, information and knowledge, facilitate
flexible and intelligent decision making and enhance strategic insights.

building
Leveraging IoT data
For example, a shopping mall can track the movement patterns of shoppers through
signals from their cell-phones, combine this information with shopping preferences
and profile of the person and use advance analytics to create tailored services and
subsequentlyincrease revenue and profit margins.
Building operators can use collected motion and occupancymeasurements to regulate
the condition of the air and the lights in real-time; we have seen that this reduces
overall energy costsand retains good (if not increasing) occupants’comfort. Savings in
large building sites, such as industrial zones, office parks, shopping malls, airports, can
reach up to 30%.

building
Leveraging IoT data
Beyond the obvious bills’ reduction, IoT-enabled cross-function monitoring and
control, facilitates the early detection of problems in the operation of individual
componentsof the BMS or on the overall performance with respect to some functions.
Even hidden faults/deviations can be detecteddue to the massive data that is
collected. Such hidden deviations act as predictions for maintenance purposes and the
early detection potentially reduces maintenance and replacement costs considerably.
Prediction analytics are very useful also in the case of security systems, where
combining weather and building environment/infrastructure data, systems can predict
emergency weather conditions, water leaks, etc.

building
Services provided to occupants
Combining environmental data (temperatureand air quality) with movement
data from motion sensors and other sources, could also allow building
operators to understand the optimal ventilation and temperaturelevels for a
specific day and give instructions to the HVAC and lighting systems to adjust
their operation.
Data about the movement of occupants can also help building operators and
owners to make more intelligent decision regarding the function of each
room/building-zone.

building
Services provided to occupants
Aggregated anonymous data about movement in the building, combined with
socio-demographic information, would result in better-informed decision
making.
It is expected that in the near future, the information about the level at which
the building is IoT-enabled will comprise an important decision factor for
companies and individuals to buy or rent it.

building
Commercial office/shops buildings
Identify buyers and general customers using camera face recognition technologies and
combine with personalised discount offers, information on parking availability,
recommendationof products, indoor navigation, contactless payment, etc.
Increase convenience of working personnel by monitoring interaction and movement;
improve efficiency and productivity by providing a healthier work environment; air
quality sensors can be embedded on the lights.

building
Residential buildings
Make better decisions on the design of the space and the experience of occupants
by collecting information on personal habits, such as consumption, health status,
movement, etc.
Enable predictive maintenance and remote control of IoT-enabled appliances.

building
Industrial buildings
Enable faster asset transportation using warehouse pick-up automation with the
help of IoT-enabled robots. Then, details about the asset while in transport, its
condition, etc. are tracked through sensors, by a centralised remote monitoring
unit.

building
Ecosystem-level contribution
IoT-enabled BMS create the ground for interconnection between buildings of
various types in a city and undertaking of higher level analytics. This helps
promote collective sustainability actions related to energy, water and waste
management.
For instance, the knowledge extracted from high-level analytics can be
combined and help make decisions on how to better connect each device on
the electricity grid.

building
Ecosystem-level contribution
In the case of water, the lack of rainfall, compared with data about flood
helps make decision on potential water leaks instead of rain-based water.
In the case of waste management, data about amount of wastes in the bins
can help optimise the collection times/types.
Finally, higher-level analytics can create very useful knowledge, which can be
useful to higher-level decision makers (e.g. city council, government) and
even create new resources and products for marketing, construction industry,
etc.

building
Technology challenges related to integration and interoperability
Despite the huge technological advancements and the existence of certain open protocols like
BACnet, Lonworks, ModBus, etc., there is still lack of widely adopted industry standards, which
acts as a barrier to wide adoption of IoT-enabled buildings.
The challenges are summarised as:
• Competing and legacy IT systems. Many legacy BMS use their own data representation and
communication standards, leading to inability to achieve vendor- and technology-
independent integration. The result is to have multiple protocols enabled in a single building
simultaneously, creating unnecessary installation, configuration and maintenance costs.
• Integration of devices across building functions has not been the industry priority in building
construction period.
• Lack of scalability beyond the physical boundaries of the building to enable remote
controlling and monitoring over the internet and cloud.

building
Responding to the challenges:
• Use new software systems that are built specifically in the IoT era and provide
already all required features for complete IoT integration across building
functions. Owners of new buildings need to consider deploying such open
solutions instead of the legacy BMS.
• Use common and open standards and protocols. For instance, the OASIS Open
Building Information Exchange is an industry-wide effort aiming to define
standard web protocols for communication between various BMS. There has to
be some sort of agreement about the data exchange and communication
standard and protocols. This will be a win-win solution for all players involved in
the IoT arena.

building
Use appropriate data structuring and analytics to avoid issues with huge volumes, production rates
and heterogeneity of data. Correct analytics will allow creating the knowledge required to act, for
every different type of stakeholder and for every different type of building.
Need for advance technical skills: As buildings adopt the use of advance analytics for the data they
collect, they will be looking for building operators that are able to understand,make use and help in
the decision making about all building functions. Building operators need to know how the data
analytics are performed and how to interpret the outcomes of analysis and the created insights.
Note, however,that it is not all about technology. The most important is to focus on real needs of
buildings and occupants and only use current technology availability as a tool to implement the
automation of processes and create the potential value.

building
Cybersecurity and data privacy
It has already been discussed that the more the data and devices are
connected to each other, the bigger are the cybersecurity and data privacy
concerns. It is much easier for hackers to acquire access to building functions
by exploiting vulnerabilities in individual devices from variety of
manufacturers and through variety of communication protocols.

building
Steps towards security
• Choose the correct purpose-built devices and IoT solutions. Although extending the
functionality of old systems is in many cases useful, it comes with the risk of creating
security holes.
• Assign clear responsibilities for involved persons. Everybody should understand their
responsibilities and expected actions and outcomes.
• Define data management procedures. Data need to be understood and plans on how to
secure them need to be in place. Each data set may have its own security requirements. Pay
also attention to the collection and processing of personal data and relevant regulations.
• Avoid strong coupling of systems: Devices can be integrated at the communication layer and
also at application layer so as to be able to replace them when they become faulty or even
to deploy new devices and make them seamlessly talk to each other easier.

IoT capabilities across functionalities/modalities of a building
Sensor types
Smart trash-bins, pest control traps,
HVAC, thermostats, lighting, smoke/CO
sensors, structural health monitoring
systems, motion sensors, security
gateways,utility meters and smart
buildingappliances
Location – Information– Analytics

Use cases: flexibility and building intelligence
IoTs can be used in a different function than the initially prescribed one:
• Consider the case when an intelligent system decided to request the use of
the luminosity sensor from a mobile device of a person who occupies the
room, to replace temporarily a broken luminosity sensor.
• Consider the case where the system retrieves open data through the
internet from a local weather station (e.g. temperatureand humidity) and
combines this information with the window opening measurement
retrieved from the security system of the Building Management System, in
order to select the most appropriate HVAC controls.

IoTs can be used in a different function than the initially prescribed one:
• A temperatureregulation system could be reconfiguredautomatically to
utilize the output of a newly installed occupancy sensor to lower the
setpoint value of the zone temperaturewhen the zone is not occupied,
thus, saving energy.
• The security system could detect occupants' presence in a room using
information from a CO2 measurement installed for the air-quality system.

HVAC system flexibility
It is a well-known fact that buildings consume about 40% of the energy consumption in the
world. Out of this total consumption, HVAC systems represent the largest consumer class. This
comes as no surprise because HVAC systems perform one of the most essential and critical
functions; delivering comfort to building occupants.
Legacy systems have no access to assets like chillers, cooling towers and Roof Top Units (RTUs).
IoT-enabled assets and systems can capture information about supply/return temperatures,
fan speeds, vibration, flow rates, compressor run times, pressure, total asset energy
consumption, etc. Energy efficiencies will then follow naturally since inefficiencies will be
detected and corrected.

HVAC system flexibility
In addition, IoT components can monitor the condition of the HVAC assets and combine it with
fault detection and diagnosis (FDD) functionality to detect even hidden faults and make early
decisions for maintenance. For instance, it is useful to know if a cooling tower was performing
outside of the normal specifications. When failures escalate to more serious levels, the cost is
always higher and the inconvenience to building occupants is huge.
IoT devices can interface with stand-alone thermostats using standardized protocols, such as
BACnet and Modbus, and can present a cloud-interface for management and control of that
thermostat. This creates a type of virtual BAS. Such use cases provide large energy savings
opportunities in small HVAC zones, such as small retail spaces, education/training classes,
individual renting spaces, or any commercial or industrial space featuring limited smart
building functionality.

Real-estate portfolio analytics
IoT monitoring across buildings of a real-estateagent can provide added-
value higher level analytics and lower the cost of the risk in managing the
building and inside assets.
Tracking the flow of people helps understand the behaviour of people in
terms of using the space. This can result in better planning of capacity renting
and identification of peak hours, etc.

Real-estate portfolio analytics
Monitoring productivity of workers in office buildings using information from smart
electric sockets, plumbing and water usage sensors, thermal efficiency recorded by
smart thermostats, maintenance and usage information from common areas and
elevators, and measurements of human “collisions per hour per square meter.”
Potential buyers of real-estate managed buildings can benefit from real-time data
about area traffic, crime, or other real-world factors that impact property values.
This will also allow customers to better negotiate new/reviewed rents.
Buildings that lack certain IoT-enabled features will be traded at lower prices.

Aalto Space mobile application
As part of the RealGO research & development project at Aalto University,
the Aalto Space app was integrated with HVAC controls through O-MI and O-
DF standards.
The project was carried out in co-operation between Aalto Real Estate
Business Unit, Aalto HVAC Team, Aalto Computer Science, Aalto CRE (Campus
and Real Estate) and Aalto IT.
As a part of the RealGO project, integration of building control systems with
IoT sensors and room booking system was carried out.

Aalto Space mobile application
Aalto Space is a mobile app for Android and iOS devices (available in respective App stores),
which can be used to find and book study and group work facilities and meeting rooms within
the campus.
Using the map included in the app, students can also navigate to facilities not included in the
booking system. It also includes an emergency messaging feature that allows the
communications department of Aalto University to send notifications in case of emergency on
campus.
While the Aalto Space app was developed separately to the Otaniemi3D project, the
developers of the ReadyGO project saw an opportunity to integrate the app with air
conditioning and ventilation control along with the Aalto's campus booking facility, using the
open standards developed through Otaniemi3D research.

Comarch smart lighting solution
Illumination systems are an essential part of urban infrastructure. They
contribute to the sense of security in public areas and highlight the
architectural beauty of cities around the world.
Embracing a combination of modern IoT solutions and illumination systems,
one can leverage smart city technology and use it as innovative smart street
lighting system.

Comarch smart lighting solution
Comarch Smart Lighting Solution provides the ecosystem that facilitates fast
implementation of fully flexible and scalable smart IoT lighting solution for
cities, as well as municipal and enterprise buildings.
• Street lamps serving as nodes in a larger, multifunctional network of smart
cities can enable demand-driven lighting.
• Individualized lighting for every worker can be created in smart offices.

Further use-cases of IoT Lights:
• Find products in supermarkets: Customers using a supermarket’s app can
find products to an accuracy of 30 centimetres thanks to visible light
communication combined with the smart phone’s forward facing camera.
• Deliver unique promotions to shoppers: Unlike general special offers
advertised in stores, smart lights can detect where a customer is located in
a store, enabling a bespoke offer for nearby items to be sent to their smart
phone.

Further use-cases of IoT Lights: (cont.)
• Turn grudge shopping into a game: The ‘gamification' of shopping is exciting for
retailers. Customers can earn points and maintain ‘streaks’ by visiting specific
stores, and parts of the stores. IoT lights detect their location.
• Track customers in stores: Smart lights can track shoppers, such as high-net-
worth individuals in department stores, even telling what concessions and
counters they have visited.
• Make food shop faster: A supermarket app can plan your route in a
supermarket, while the smart lights – which know your location – can help
remind you of items you can pick up along an aisle.

• Find high-value equipment in hospitals: Tracing medical equipment, such
as ultrasounds and portable ECG machines can waste a lot of valuable
time. With embedded sensors in luminaires, this becomes a cinch.
• Detect the build-up of queues: Tiny sensors in luminaires can inform
hospital management of real-time queues of both people and vehicles,
such as ambulances and alert them instantly to problems.
• Help monitor the elderly: In nursing homes and care environments, lights
with sensors can tell clinical staff if an elderly patient had a fall or where
lack of movement over a period of time is a concern.

• Help wayfinding in a hospital: Wayfinding is a major problem in hospitals
– it’s estimated it costs the equivalent of two extra staff. Smart lights with
location tracking can help reduce interruptions to staff.
• Reduce theft in hospitals: Some expensive healthcare items, such as spinal
pillows, are regularly removed from hospitals. Using tags and smart labels,
IoT lights can detect when these leave designated areas.
• Tell facilities chiefs if space is well used: Smart lights can tell how well
your buildings are being used, and what areas are hot spots and what
are underused, leading to major savings.

• Prioritise cleaning: Cleaning companies can use information from smart
lights to determine the frequency of cleaning visits required for areas of
buildings based on occupancy and traffic.
• Help manage meeting rooms: Connected lights with smart sensors can tell
building operators if meeting rooms are being used after booking, and by
how many people. The information can help with space planning, as well.

• Help employees personalise their lighting: Using just a smart phone
detected by the IoT lights, employees can tune the illumination levels –
and even the colour temperature – of the lights wherever they are.
• Deliver the internet securely: Internet-connected lights with Li-Fi
functionality can deliver ultra-high internet connections to enabled
devices, avoiding the security and bandwidth issues of traditional Wi-Fi.

Further use-cases of IoT Lights - Hospitality and Leisure
• Automatically test the emergency lighting: Connected lighting can
automatically conduct the mandated regular testing of emergency lighting
systems and their batteries, and compile the necessary reports.
• Deliver information in museums and galleries: Using an app and visible
light communication, IoT lights can use proximity technology to give
museum- and gallery-goers an enhanced experience and information
about exhibits.

Further use-cases of IoT Lights - Hospitality and Leisure
• Personalise and automate guest rooms: In hotel guest rooms, smart
lighting can identify occupancy – and even the individual guest and his/her
preferences– and adjust the room’s lights, blinds, TV channels and HVAC
accordingly.
• Encourage hotel guests to buy more: Location-based restaurant
recommendations and offers, as well as checkout offers, such as a late stay
options, can be sold to hotel guests using location tracking and a smart
phone app.
• Cut costs in hotels and resorts: IoT lights with motion sensors can
intelligently turn off the air conditioning and other unnecessary utilities.

Use cases relatedto smart home services
• Measuring home conditions: Such as temperature, humidity, light and proximity. Temperature and
humidity maybe measured by one sensor, other sensors calculate the light ratio for a given area and
the distance from it to each object exposed to it. All sensors allow storing the data and visualizing it
so that the user can view it anywhere and anytime. To do so, it includes a signal processer, a
communication interface and a host on a cloud infrastructure.
• Managing home appliances: Managing home appliances on a cloud infrastructure. The managing
service allows the user, controlling the outputs of smart actuators associated with home appliances,
such as lamps and fans. Smart actuators are devices, such as valves and switches, which perform
actions, such as turning things on or off or adjusting an operational system. Actuators provide a
variety of functionalities, such as on/off valve service, positioning to percentage open, modulating to
control changes on flow conditions, emergency shutdown (ESD). To activate an actuator, a digital
write commandis issued to the actuator.

Use cases relatedto smart home services (cont.)
• Controlling home access: Home access technologies are commonly used for public access doors. A
common system uses a database with the identification attributes of authorized people. When a
person is approaching the access control system, the person’s identification attributes are collected
instantly and compared to the database. If it matches the database data, the access is allowed,
otherwise, the access is denied. For a wide distributed institute, we mayemploy cloud services for
centrally collecting persons’ data and processing it. Some use magnetic or proximity identification
cards, other use face recognition systems, finger print and RFID.
– In an example implementation, an RFID card and an RFID reader can be used. The persons scan
their cards via an RFID reader located near the door. The scanned IDs can be sent via the internet
to the cloud system. The system posts the ID to the controlling service which compares the
scanned ID againstthe authorized IDs in the database.

• Discoveryof water leaks and its prevention: deploying water sensors under every reasonable
potential leak source and an automated master water valve sensor for the whole house. In case the
water sensor detects a leak of water, it sends an event to the hub, which triggers the “turn valve off”
application. The home control application then sends a “turn off” command to all IoT appliances
defined as sensitive to water stopping and then sends the “turn off” commandto the main water
valve. An update message is sent via the messaging system to these appearing in the notification list.
This setup helps defending againstscenarios where the source of the water is from the house
plumbing. The underlying configuration assumes an integration via messages and commands
between the smart home and the IoT control system. It demonstrates the dependency and the
resulting benefits of combining smart home and IoT.

• Smoke detectors:Most houses already have the typical collection of smoke detectors, but there is no
bridge to send data from the sensor to a smart home hub. Connecting these sensors to a smart home
app, enables a comprehensive smoke detection system. Itis further expanded to notify the elevator
sensor to block the use of it due to fire condition, and so, it is even further expanded to any IoT
sensor, which maybe activated due to the detected smoke alert.
• Incident management to control home appliances: Consider the scenario where you leave home
while some of the appliances are still on. In case your absence is long enough, some of the
appliances may overheat and are about to blowout. To avoid such situations, you can connect all IoT
appliances’ sensors to the home application, so that when all leave home it will automatically adjust
all the appliances’ sensors accordingly, to avoid damages. Note that the indication of an empty home
is generated by the Smart Home application, while the “on” indication of the appliance, is generated
by IoT. Hence, this scenario is possible due to the integration between smart home and IoT systems.

Oracle’s building IoT innovations
Oracle’s Building is a three-story 120,000 sq. ft. structure built to house more than 550
occupants, a data center research lab, a café, a classroom space, and other necessary office
amenities. Oracle has a large team of building operators with valuable experience in managing
advanced building automation systems, integrating these systems into the enterprise IT
network and utilizing the system data to derive useful insights on building space usage and
systems’ performance.
Unlike the other building owners, Oracle did not focus on onsite energy generation, but rather
on systems efficiencies, IoT innovations, and facility performance continuous validation. Such
operational and building efficiencies qualified the building to receive LEED Gold certification
from the USGBC and Energy Star Certified.

Oracle’s building IoT innovations (cont.)
This building represents an interesting case of how systems are integrated during the design
and construction phases with the objective of integrating their data for intelligent operations
and analytics.
The building operators team drafted the specifications of the IoT project by matching desired
functionalities to available systems and products.
For example, they specified tracking space utilization and automate space conditioning and
lighting based on the occupancy level. To achieve this, they selected a smart lighting system
(Enlighted) that integrates occupancy and ambient light sensors into the LED lighting fixtures.
The data from Enlighted’s occupancy sensors have been integrated into the BMS platform
(Tridium) and used to control the variable air volume (VAV) units in the corresponding rooms.
Within the smart lighting fixtures, the LED are dimmed based on the sensed occupancy and
ambient light levels.

Another example of interesting integration was achieved between the electrochromic-glass
smart window system (supplied by View) and the mechanized shading system. The View smart
window system comes with an advanced building-roof-top sensory station that determines the
sun’s altitude, angle, and foot-candle. Data are fed internally within the View system to dim the
window glazing and are also shared within the BMS platform to open and close the shading
system by setting its set point to be 1900 foot-candle.
The building operators use data from electrical sub-meters and BTU metering for continuously
validating building performance.
IoT-based systems are connected by a dedicated network, separated from the IT network, in
order to minimise risk for cyber-threats.

In order to manage the project, Oracle set another control layer, which was facilitated
by an analytics cloud-based product, called IBIS (by Integrated Building Solutions).
IBIS proved to be much simpler than the utilized BMS platform (Tridium) in terms of
the simplicity of user interface and hiding complicated data integration functions
(which are still done by Tridium).
The IBIS solution uses data collected by the BMS platform to provide easy automation
within and between the systems.

Second, the IBIS solution provides controlled accessibility to the building data and
automation with varying privileges given to different stakeholders. For example, the
data centre research lab was able to access the temperature, humidity, electrical
sub-metering, and BTU metering data of the research space within the IBIS
solution, with limited privileges on data accessibility and systems control.
Third, the IBIS solution provides a continuous commissioning module that
statistically analyses building data to create regression models of building
performance and energy consumption.

Lessons learnt:
• The building operators faced different scalability issues when trying to integrate
the IoT system at its full scale for the whole building.
• For example, the large number of LED smart lighting fixtures resulted in some
issues in communicating the collected data to the BMS system. These LED lights
communicate to two gateways on each floor through a wireless communication
technology (similar to ZigBee). The gateways are hardwired to a single control
unit for the whole building that is connected to the BMS. However, this single
control point created a bottleneck for communicating the lighting sensor data.
• The issue was resolved afterwards, only with the intervention of the vendor.

The Zero Net Energy Centre (ZNEC)
IBEW Local 595 and NECA’s Northern California Chapter collaborated and
established a world-class training centre, housed in a showcase smart energy-
efficient building, where electrical apprentices learn hands-on skills in
installing the latest building electrical and energy systems.
The Net-Zero Plus (NZP) Electrical Training Institute and its unique facility, are
considered the country’s largest net zero plus commercial building retrofit.

The Zero Net Energy Centre (ZNEC) (cont.)
The building was designed to be proof that an old commercial building (originally built in 1981)
can be retrofitted to achieve the zero net energy goal and to showcase the capabilities of
electrical contractors in the area of zero-net energy systems, by building a functional, cost-
effective ZNE building that also houses the apprenticeship program that trains future
electricians on the cutting-edge energy systems.
In its first year of operation, the ZNEC exceeded its net energy goal by having a surplus
(negative) energy use intensity of 5.49kBtu/ft2. The impressive performance of the building
can be attributed to the integrated design process that involved the different stakeholders and
their design ideas to end up with the final concept of the smart building integrated systems.
The lighting designer, mechanical engineer, structural engineer, renewables designer, and
general contractor were all involved from the programming phase.

The renovation was done in phases, as funding became available. First, the solar PV
rooftop panels and early generations of LED lights were installed. Other renovation
work followed over the years, including storage batteries, computerized micro-grid,
solar PV parking pavilions, newer generations of LED lights suitable for high ceiling
training spaces, roof insulation and the façade.
A single occupancy sensor system is used to control both the HVAC and lighting
systems. The roof monitors serve multiple energy efficiency aspects: natural
ventilation, natural lighting, light source for the indoor mass thermal wall and support
platform for the solar PV panels.

The building earned its NZP name due to its pioneering micro-grid
capabilities that once representedthe largest commercial grid outside of
military uses. The building uses 185,500kWh per year and generates more
than that, earning it a net-zero rating.
The facility is under continuous monitoring and validation by a system
integration firm, which was involved early in the project during the planning,
design and construction phases.

The VF Outdoor 14-acre campus in Alameda, California
VF Outdoor is a company that owns multiple fitness and outdoor fashion
product lines.
The campus comprises four office buildings and there is a plan to design and
build a fifth building. The four buildings have a total area of 160,000 square
feet with a variety of space uses, such as offices, a fitness centre, a café, and
an outdoor training area.
The entire campus was designed to achieve a zero-bet energy (ZNE) goal. But,
it is not completely a ZNE building, as it is still dependent on a gas supply to
the café and gym facilities.

The VF Outdoor 14-acre campus in Alameda, California(cont.)
The lessons learned from this project illustrate the need for more proactive monitoring and predictive
analytics to optimize the performance of the individual systems and the whole building.
The IDEC HVAC system proved to be effective, especially in the project location (San Francisco Bay Area),
where no sudden weather changes occur. However, the system showed slow reaction to sudden
extreme weather changes, which required the manual operation of the system and resulted in less
comfort for occupants some days of the year.
This issue can be solved by connecting the system to a weather station or predictive weather services,
that can adjust operational settings in anticipation of any extreme weather events. Also, some tenants
have misused the operable windows or left them open while the HVAC is operational.
Manual operable windows can be convenient for tenants to adjust their space environments, but
window sensors can be installed and integrated into the BMS to avoid running the HVAC system in the
zones that are conditioned using the operable windows.

The Manitoba Hydro Place (MHP)
It is the first LEED Platinum Certified building in Canada and is considered the
country’s greenest and most energy-efficient building.
It is 75% more energy efficient than a typical office building in Winnipeg,
equivalent to CAD $1.5 million annual operational cost savings. The building
is owned by Manitoba Hydro, the major energy generation company.

The Manitoba Hydro Place (MHP) (cont.)
It adopted a progressive integrated project delivery (IPD) system to be able to achieve
its six core goals:
1) create a supportive workplace environment for the employees of Manitoba Hydro;
2) create an energy-efficient design to achieve a 60% reduction in energy consumption
using Canada’s Model National Energy Code of Buildings (MNECB); 3) create a design
that achieves LEED; 4) develop signature architecture integrated throughout the
building; 5) achieve a high level of urban integration to revitalize the downtown area;
and 6) employ a cost-effectivebuilding design solution that has measurable benefits to
Manitoba Hydro in terms of comfort, operations, and maintenance.

The Manitoba Hydro Place (MHP) (cont.)
The engineering team came up with a creative smart building design that features several passive
energy-saving approaches to use sunlight and wind to create a comfortable and healthy indoor
environment with minimal energy loads. These passive approaches included: 8-story high water curtain,
solar chimney for the full height of the building, indoor winter gardens, and double façade curtain walls.
It required, however, about 25,000 control and measurementpoints that are connected and controlled
by an advanced building managementsystem (BMS). Combined with the building controls, the passive
building features can become more responsive to account for the large temperature swings. The outside
operable windows are opened and closed automatically based on wind speed and temperatures inside
and outside the building. The water curtain temperature is controlled automatically to humidify the air
in winter and dehumidify it during summer months.

The Edge building
The Edge was the brainchild of developer OVG Real Estate (the property
owner) and the main building tenant, Deloitte, a global accounting and
professional services company.
It is considered the smartest and greenest building in the world, as it
achieved the most historical points (98.6/100) in the BREEAM(Building
Research Establishment Environment Assessment Methodology) green
building rating system.
The Edge also is a true showcase of how high levels of IoT connectivity is
achieved between building operations, management, and occupants comfort.

The Edge building (cont.)
Deloitte got the Edge to accommodate 2,500 employees who share 1,000 “hot” desks. Deloitte
was able to reduce the amount of space per employee from 41 square feet to 25 square feet,
while improving employee comfort and satisfaction.
The EDGE’s smart and sustainable systems achieved unprecedented levels of energy efficiency
and empowering interactions with the occupants. With the help of its large PV solar system
and geothermal aquifer, the Edge uses 70% less electricity than a typical office building and
produces more energy than it consumes.
The building features one of the early smart lighting innovations, in which Phillips custom
designed the PoE-powered LED lighting fixtures to be equipped with different sensor types
(motion, temperature, light and air). These lighting sensors are a group of a total of 28,000
sensors of every imaginable type. All have individual IP addresses and are connected and
managed by the same building operation system.

The large number of sensors allows the indoor environment control to be
significantly granular, down to only 200 square feet per a single control zone.
It allows employees to personalize both the lighting and temperature of their
workspaces with a smartphone app, while also collecting workspace
environment data to reduce energy consumption.
The facility’s operation was also optimized through the use of analytics with
the collected data.

Building operators saved time by being informed on a timely basis which coffee machines
needed to be filled and which underutilized toilet rooms can be skipped.
Mapiq was then a young company specializing in IT-driven workplace occupancy services.
Deloitte invited Mapiq to develop a customized mobile app to deliver an activity-based
management of the employee workspaces. Mapiq collaborated with Phillips and Schneider
Electric to utilize and integrate the data streams from their sensors.
This integrated vendor collaboration empowered building occupants to automate a wide range
of their daily office tasks from the Mapiq app, such as finding the location of meetings,
reserving rooms, adjusting lighting levels, changing the room temperature, finding a free
parking space, reserving lockers and even operating the coffee machines.

Real-time location-based systems (RTLS)
RTLS is a form of local positioning system to track assets in real-time, usually
in indoor environments where global or cellular positioning systems cannot
operate.
By knowing where assets are located, processes can be streamlined,
generating valuable data and letting employees focus on activities that
actively bring value to the organization.

Real-time location-based systems (RTLS)
The following are some example RTLS use cases and objectives in different
industries:
• Manufacturing: track machines and goods through the assembly line and
identify any bottlenecks of inefficiencies.
• Healthcare: track the location of medical devices to help reduce wasted
staff time.
• Offices: track employees to monitor desk utilization in flexible work
environments.
• Hotels: guest tags can help in-room automations and employee tags can
impact security and safety.

EDGE AND FOG COMPUTING
“One of the beautiful outputs of connecting ‘things’ is unlocking access to
real-time data. Next is turning that data into information and, more
importantly, actions that drive business value. In trying to do so, companies
are finding themselves deluged with data. So much so that demand for vast
compute and storage needs have arisen, very nicely handled by public cloud
providers. But the cost of transport and speed of processing has also
increased, which is challenging for many uses cases such as mission-critical
services.”
Macario Namie, Cisco’s Head of IoT Strategy, 2017

Future smart buildings will contain hundreds and thousands of sensors
measuring various building operating parameters, such as temperature,
humidity, occupancy, energy usage, key card readers, parking space
occupancy, fire, smoke, flood, security, elevators, and air quality.
Collectively, these sensors capture massive amounts of data that must be
transmitted to the cloud, stored, analysed and acted upon using actuators,
often in real-time, to provide a truly smart building experience.

Some of this processing and actuating is extremely time-sensitive, and
requires a real-time response from the field devices. Examples would include
turning on fire suppression systems in response to detecting a fire event and
guiding occupants to the nearest exit, or locking down an area if an
unauthorized person tries to gain entry.
This pure cloud-based IoT vision of smart buildings can face scalability and
reliability issues with the further deployment of IoT devices and the growth
of their data communication needs. The industry needs a different vision,
cheaper and smarter than the traditional cloud-based one that typically
involves gathering the data, sending them through the network to the cloud,
and processing and leveraging them.

Depending on the context and scope of the project, you want the data you
need fast. Better yet, you need the aggregated and analysed data fast, in the
shape of actionable intelligence, enabling you to take actions and decisions,
whether these decisions are human or not.
So, you do not need all that data to store it and analyse it in the cloud. You
only want that bit of key data traveling across your networks.
Some building systems are life or mission critical and require higher
availability than cloud-based solutions can achieve. Some smart building IoT
systems generate significant data volumes that would swamp the building’s
network bandwidth.

IoT, smart home and cloud computing are not just a merge of technologies. But rather, a
balance between local and central computing along with optimization of resources
consumption. A computing task can be either executed on the IoT and smart home devices or
outsourced to the cloud.
Where to compute depends on the overhead trade-offs, data availability, data dependency,
amount of data transportation, communications dependency and security considerations.
On the one hand, the triple computing model involving the cloud, IoT and smart home, should
minimize the entire system cost, usually with more focus on reducing resource consumptions
at home. On the other hand, an IoT and smart home computing service model, should improve
IoT users to fulfil their demand when using cloud applications and address complex problems
arising from the new IoT, smart home and cloud service model.

The IoT industry started the old approach of performing some basic computing in
the devices themselves or somewhere in the local network close to them, instead
of transmitting huge amounts of raw data for cloud computing.
This old approach had the name “edge computing”, often mixed with another term
called “fog computing”. Both approaches (edge and fog computing) entail moving
intelligence and processing capabilities down closer to where the data originates.
They differ in where that computing occurs in the spectrum between the cloud and
the devices. Fog computing pushes intelligence down to the local area network
level of network architecture, processing data in a fog node or IoT gateway. Edge
computing pushes some or most of the intelligence, processing power and
communication directly into the field devices like programmable automation
controllers (PACs).

Edge, fog, and cloud computing will complement each other, rather than
competing against each other. It is not yet clear how these computational
approaches will be deployed in smart buildings, as different architectures are
presentedby the leading industry organizations, such as the OpenFog
Consortium smart building use case (Open Fog 2018), the definition of fog
computing by the National Institute of Standards and Technology (NIST 2018),
and Edge X Foundry (EdgeX 2018).

Edge Node: The edge node can representa sensor/device with onboard
microcontrollers, such as VAV, IP Camera, smoke detectors, etc. Small
programs called Device Services are installed in the embedded
microcontrollers to provide real-time logic and control actions. Also, the edge
node and its device services screen data locally, reducing the volume of data
traffic sent further into the fog and cloud path.

Room Fog Node: Room fog nodes can govern a conference room, an
office, an apartment or any similarly- structured closed space. The room
node will have enough intelligence to discern which data require
storage, based on which actions require real-time processing, which can
be passed to a floor fog node, or which can be shared with another
room node. It will have enough AI power to perform localised actions,
such as conserving energy load within an unoccupied room, to learn
and maintain an occupant’s preferred temperature, recognize intruders,
and even recognize occupants’ gestures or voice commands to provide
specific comfort services.

Floor Fog Node: Floor fog nodes connect to many of the same sensors and
actuators as room fog nodes (those that are in open areas) and to room
nodes themselves. Floor fog nodes coordinate all room nodes for a given
floor, exchange information with other floor nodes, and share with the
building fog node any information required for optimizing the entire building,
or for storage in the cloud. These enhanced capabilities require more
advanced analytics and larger storage space than room fog nodes and
maintain similar latency. The floor node’s AI power enables constant solving
of complex optimization problems, such as balancing the energy loads
between different rooms.

Building Fog Node: Well-architected building fog nodes communicate with
fog nodes below them in the hierarchy and other building fog nodes. They
ingest data from room and floor fog nodes and take slower, more deliberate
actions, such as setting equipment schedules, optimizing overall load on the
building’s systems, and communicating with the cloud.

Public/Private Fog Node: Intermediate fog computing nodes can exist
between buildings and the cloud, which can be owned by public or private
entities. Public nodes can be owned by local jurisdictions to make smart cities
and smart grids a reality by coordinating the services and utilities between
different buildings. Private fog nodes can be owned by mobile network
providers and operators and integrated into their future 5G towers. Private
enterprises can then rent these fog nodes for AI analytics, instead of having a
dedicated building fog node.

Cloud Node: Cloud fog nodes provide the analytics power to train predictive
models with huge, stored datasets, compare a Smart Building's performance
to that of like Smart Buildings, and generate the wisdom learned from
Petabytes of data collected from tens to hundreds of buildings. Also, cloud
nodes will provide the ability for a Smart Building to connect to other fog
nodes in the area without opening itself up to malicious hacks.

Open discussion…ideas?
• Let’s share ideas on ways to use IoT capabilities in
combinations of functions to automate building and
occupants’processes…

Resources
• http://dupress.com/articles/iot-primer-iot-technologies-
applications/
• https://www.sciencedirect.com/science/article/pii/S09265805
17305964
• https://www.intechopen.com/online-first/smart-home-
systems-based-on-internet-of-things
• https://poweringchicago.com/wp-
content/uploads/2019/03/Smart-Building-IOT-FINAL.pdf

Disclaimer
For further information, relatedto the VET4SBO project, please visit the project’swebsite at https://smart-building-
operator.euor visit us at https://www.facebook.com/Vet4sbo.
Downloadour mobile app at https://play.google.com/store/apps/details?id=com.vet4sbo.mobile.
This project (2018-1-RS01-KA202-000411) has been funded with support from the European Commission (Erasmus+
Programme). Thispublicationreflects the views only of the author, and the Commission cannot be held responsible
for any use which may be made of the informationcontainedtherein.

VET4SBO Level 1 module 4 - unit 3 - v0.9 en

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