VET4SBO Level 2 module 6 - unit 4 - v0.9 en

ECVET Training for Operatorsof IoT-enabledSmart Buildings (VET4SBO)
2018-1-RS01-KA202-000411
Level 2
Module 6: Enhanced automation and reduction of
human intervention
Unit 6.4: Limitations of automation solutions

Outline
1. Limitations of IoT-enabled solutions, to avoid errors on the
job
2. What not to expect from the IoT-enabled building automation
solutions

Main challenges faced by IoT
The adoption of IoT is challenged by certain technological limitations,
covering technologies needed to make IoT systems function smoothly.
These technological challenges include: Security, Integration and
Interoperability (Connectivity), Compatibility & Longevity,
Communication Standards and Technologies related to the Intelligent
Analysis & Decision Support for Actions

(Cyber)-security and data privacy
The more data and devices are connected to each other, the bigger the
cybersecurity and data privacy concerns are. 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.
There are many security measures that are taken to protect the data and
information, however, there is an ongoing battle between security levels and
hacking practices; there is always the possibility that the latter manage to
break into a system and compromise data. For example, well-known groups
of hackers, like Anonymous, hack into governmental and other sites and get
access to confidential information.

Consider then the case where all our information and building
operation details are stored on the internet, through IoT; it would
reveal a great deal of details about personal living patterns. There is
also the case of building management companies that may use the
data and information inappropriately, as it happens with other types
of data; there is a lot of value in that information.
The concerns become bigger if one considers that the IoT industry is
currently in its infancy state; during this phase, typically technology
and functionality is the focus, in the hunt for customers and
competition, while security is left behind.

With all these security and privacy concerns, there is an issue of who
will be given the trust to control the IoT; and where would the data
be stored? How is the data going to be encrypted during
communication?
How can one trust the automation systems when there is even a
small possibility for a malicious third party to compromise the data?
Imagine the case of appliances operating outside your will, products
with malicious content being delivered after ordering, etc.

Furthermore, consider the potential hacking of baby monitors,
smart fridges, thermostats, drug infusion pumps, cameras and
even the radio in your car. There will be so many “attack vectors”
offered to the hackers...
If the IoT is exposed, then the organisationsrelying their
processes on it are equally exposed to security holes.

Walled Internet: according to the World Economic Forum, the growing
number of cross border attacks will start pushing national governments
towards breaking up the internet in national, or even regional “walled
gardens”.
This will create major barriers to the flow of content and transactions.

Cloud attacks: it is likely that cloud providers will be one of the main targets
of hackers. And cybersecurity is not as advanced as the other IoT
technological and business trends. The World Economic Forum report states
that “a takedown of a single cloud provider could cause $50 billion to $120
billion of economic damage — a loss somewhere between Hurricane Sandy
and Hurricane Katrina”.

Security issues related to artificial intelligence (AI): taking a cloud provider’s
infrastructure down, affects hundreds of businesses, government entities,
critical infrastructures, and healthcare organisations. And this may become
feasible when hackers start using artificial intelligence embedded in
machines, to analyse the data and learn the internet security holes and
patterns and create malicious software automatically. It has always been the
case, for technology advances to be used in both good and bad ways.

Botnet-related issues: it is expected that small, cheap, consumer devices will
not be that protected in terms of avoiding attacks. There is a risk for this
distributed network of devices to open big security holes to whole building
networks and even utilities (through the utility measurements)and city
infrastructure.
It is thereforenecessary to secure devices with anomaly detection solutions,
to recognise the events of devices showing abnormal behaviour. It also helps
to have clear communication standards with bounds on what data devices
are allowed to send or how often they're allowed to send it.

Lack of confidence: Reports (e.g. State of IoT Security research report) state that
90% of consumers lack confidence in the security of IoT devices. As high as 96% of
businesses and 90% of consumers believe there should be IoT security regulations.
Only 14% of consumers believe that they are knowledgeable on IoT device security.
Around 60% percent of consumers are concerned about data being leaked.
Jason Hart, CTO of Data Protection at Gemalto company in The Netherlands, said:
"It's clear that both consumers and businesses have serious concerns around IoT
security and little confidence that IoT service providers and device manufacturers
will be able to protect IoT devices and more importantly the integrity of the data
created, stored and transmitted by these devices…Until there is confidence in IoT
amongst businesses and consumers, [IoT] won't see mainstream adoption…”

Integration and interoperability
Despite the 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.
Many legacy BMSs 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 constructionperiod.
Lack of scalability beyond the physical boundaries of the building
to enable remote controlling and monitoring over the internet
and cloud.

Compatibility challenges: as devices from different manufacturers will be interconnected, the
issue of compatibility in data formatting and communicating becomes bigger. It is unlikely that
all vendors will agree to a single common standard in the foreseeable future (consider non-
unified cloud services, lack of standardized M2M protocols and diversities in firmware and
operating systems among IoT devices).
These issues may result in consumers being locked to specific devices’ vendors, thus preventing
the real wide adoption of the IoT and seriously limiting its foreseen value.
And many of the adopted technologies will eventually become obsolete in the next few years,
causing major costs to consumers that will invest on them; who would like their IoT appliances
(such as smart fridges or TVs) to require replacement in 2-5 years?

Connectivity challenges: connecting so many devices will be a challenge for current
communication models and technologies. For instance the server/client
authentication/authorisation mechanisms will suffer from the volume of devices requiring to
be securely connected. What will happen when billions and hundreds of billions of devices will
ask to join existing networks? Entire systems can go down, if the servers’ infrastructure
becomes unavailable.
It is expected that the future of IoT will be the decentralised networks. Moving much data
processing and analysis to the edge, with devices taking some mission-critical operations
locally, may help smoothing a little bit the connectivity problem.
There can also be solutions adopting peer-to-peer authentication/authorisation models,
without the need of a centralised broker; consider the possible merging of IoT technologies
with Blockchain distributed trust infrastructure.

Standards:
Technology standards which include network protocols,
communication protocols and data-aggregation formats are defining
ways to handle, process and store the data collected from the IoT
devices.
There are certain challenges related to handling unstructured data:
While structured data are stored in relational databases and queried
through (standard) SQL, unstructured data are stored in different
types of NoSQL databases, where there are no standard querying
approaches.

Scalability limitations
Even smart BMS data, still today, suffer from their inherent lack of
scalability. It was impractical in the past and it still is impractical in the
new IoT era to have buildings installing only compatible equipment
from specific vendors, using specific communication protocols and so
on.
Usually vendors are reluctant to adopt open protocols; especially the
“strong” players in the market, tend to push their own proprietary
data communication protocols, which closes the door to any third-
party integrations, thus killing scalability.

Data capturing and processing limitations
According to scientists and engineers, analysing and visualising the dense BMS data, will offer to building
operators the means to produce the ideal environment for occupants, in a more energy and cost
effective way.
However, there currently exist practical limitations with the data that can be captured by building
managementsystems, as well as limitations on the extent to which BMS data can be used to achieve the
aforementioned goal.
As of today, it is still expensive to capture and maintain data. Although the cost of sensors
has considerably dropped in recent years, the cost of a complete deployment of a BMS solution is still
high. Even the cheapest options have a cost of around €5 per square meter. And this is even for solving
individual problems, such as basic lighting controls.
[1] Evans, D. (2011) The Internet of Things: How the Next Evolution of the Internet Is Changing Everything.
http://www.cisco.com/web/about/ac79/docs/innov/IoT_IBSG_0411FINAL.pdf

Data capturing and processing limitations
In addition, there is a cost related to using the data. There is a need for expert and
dedicated building engineers to be analysing the data and adjusting set points and
configurations to derive value. This is time consuming and costly. Even in the case of
using a software to analyse and visualise the data, there are additional costsinvolved
with the product or service used for that.
Phone service suppliers such as Verizon and AT&T are no longer offering unlimited data
usage for mobile phones because it is too costly, yet by 2020 it is expected that 50
billion devices will be connected,collecting and storing data. [1]
[1] Evans, D. (2011) The Internet of Things: How the Next Evolution of the Internet Is Changing Everything.
http://www.cisco.com/web/about/ac79/docs/innov/IoT_IBSG_0411FINAL.pdf

Data value limitations
Data alone have no or little value; what carries value is the decision-making
information that hides within the datasets.
In the case of buildings, relevant decisions include equipment schedules, set points,
system configuration optimisations, etc. For instance, one can reduce the operation
costs of a building by simply turning off certain devices/functions (e.g. heating, lights),
when nobody benefits from them.

However, the benefit is much prominent in certain types of buildings, such as hotels or
big office complexes,which have a very dynamic profile of usage patterns. There is not
much space for optimisation, and subsequently for savings, when it comes to
residential or long-rented office buildings with consistentusage patterns.
Would it be worth the investment of data capturing and visualisations if the
optimisation space appears to be small?

Intelligent data analysis and actionable decisions
In many cases, data analysis is driven by cognitive technologies and the
accompanying models that facilitate the use of cognitive technologies. Artificial
intelligence models can be trained and improved with large data sets, which will be
available through cloud providers of services to smart buildings. New algorithms
and improvements in existing ones will become available through the increased
data availability.
However, there is always the chance of inaccurate analysis due to flaws in the data
and/or the models describing the data, thus exposing various algorithmic
limitations. This is coupled with the fact that most IoT interactions generate
unstructured data and there are no widely adopted ways of managing these data.

Intelligent data analysis and actionable decisions
Moreover, traditional analytics software are not yet ready to analyse
real-time data streams, considering the volume, velocity and variety
of information captured.
The challenges are summarised as:
• slow emergence of technologies to handle real-time data and
analyse them
• machines’ actions in unpredictable situations
• mean-reverting human behaviour

Over-reliance on technology
Imagine scenarios where
• Your fridge can identify that you have run out of milk; it contactsthe supermarket
and orders the quantity you usually need, and also informs you by sending a
message on your phone
• Your alarm rings at 6:30 am; you wake up and switch it off. As soon as you switch off
your alarm, it conveys to the geyser to heat water at a temperature you prefer and
also the coffee maker starts brewing coffee!

Over-reliance on technology
It becomes obvious that, like it did happen with the internet and the mobile devices,
our lives will be increasingly controlled by and depend on technology. We need to
make an early clear decision on how much of our daily lives we are willing to let be
controlled by technology. We need to understand that no machine system is robust and
fault-free. The more we entrust and the more dependent we are on the IoT, could lead
to a potentially catastrophic event if things collapse.
The IoT systems will be complex, thus creating more opportunities of failure. Imagine
scenarios where a bug in the software ends up automatically turning on and off the air-
conditioning system and lights every few minutes.

Potential loss of jobs
There is a big concern that reliance on the IoT and offering of
advanced automation will eventually result in the loss of jobs. The
impact is expected to be higher on the less-educated workers.
For example, people who manage inventories will lose their jobs,
because devices can not only communicate between each other, but
transmit that information to the owner. There are already jobs being
lost to automated machines, such as the checkout line in
supermarkets and even ATM’s.

Potential loss of jobs
It results to a decrease in employment of menial staff!
The unskilled workers and helpers may end up losing their jobs in
the effect of automation of daily activities. This can lead to (at
least temporary) unemployment issues in the society.
The answer is education. There will be tremendous need for
highly-educatedstaff to manage the automated systems, train
the AI algorithms and maintain them.

Business-related issues
If businesses start investing in IoT without sound plans, then the
model will fail.
It is expected that end-to-end solution providers operating in
vertical industries and delivering services using cloud analytics
will be the most successful at monetizing a large portion of the
value in IoT.

IoT can be divided into 3 categories, based on usage and clients base:
• Consumer IoT includes the connected devices such as smart cars,
phones, watches, laptops, connected appliances and entertainment
systems.
• Commercial IoT includes things like inventory controls, device
trackers and connected medical devices.
• Industrial IoT covers things such as connected electric meters,
waste water systems, flow gauges, pipeline monitors,
manufacturing robots and other types of connected industrial
devices and systems.

Devices without IoT capabilities may be more expensive in the future, since
they will lack data that can be utilised by manufacturers.
Missing regulatory standards: But, regulatory standards for all these IoT and
data markets need to be in place; need to regulate companies that sell data
collected from various sources. There is a lack of transparency about who
gets access to data and how those data are used to develop products or
services and sold to advertisers and third parties. There is a need for clear
guidelines on the retention, use and security of the data including metadata
(the data that describe other data).

Society-related issues
Understanding IoT from the customersand regulators perspective is not an easy task
for the following reasons:
• Customer demands and requirements change dynamically
• New uses for devices—as well as new devices— emerge
• Inventing and reintegrating must-have features and capabilities are expensive and
take time and resources
• The uses for IoT technology are also expanding dynamically

Society-related issues
Consumer confidence: The above may limit the will of consumers to adopt IoT and connecting
their lives to the internet. This challenge becomes bigger with the lack of understanding or
education by consumers of best practices for IoT devices security to help in improving privacy.
Beyond data privacy: consider integrating devices into our environments without us
consciously using them, e.g. tracking devices for phones and cars, as well as smart televisions
with voice recognition or vision features that can continuously listen to conversations or watch
for activity and selectively transmit that data to a cloud service for processing, which
sometimes includes a third party.
In addition, there are IoT scenarios that involve cross-national and cross-cultural deployments,
thus increasing the interoperability challenges related to societal issue. Privacy of people and
data need to consider not only technological dimensions, but also cultural and societal.

Technological limitations related to the IoT leverage
The Web of Things role in the IoT [2]
There are currently no clear boundaries to what the IoT is or is not. The Internet extends into
the physical world.
As discussed, “the Internet of Things (IoT) is a system of physical objects that can be
discovered, monitored, controlled or interacted with by electronic devices which communicate
over various networking interfaces, and eventually can be connected to the wider Internet”.
Scenarios where physical objects feel the world through sensors and then analyse, store and
exchange information are becoming reality. These objects are typically called: smart things.
Such Things go beyond the physical objects, accompanied by information stored digitally and
describing the Thing, which can be sensors, actuators, computation components,
communication interfaces.
[2] https://www.manning.com/books/building-the-web-of-things?a_bid=16f48f14&a_aid=wot

The physical world is extended in various ways, through a range of technologies that
started with the use of tags of objects (QR codes, RFID Tags), then emerged with
devices like Arduino and Raspberry Pi, continued with machines like all those smart
sensors and smart cars and is emerging with automating whole environments like
buildings and cities.

The Internet part of IoT, enables the Thing (i.e. its associated data and
services, inputs/outputs) to be accessed and processed by third-party
applications through the existing Internet infrastructure.
This means that the Thing can exist on the Internet even in the cases
where it is not physically connected to the Internet.
As of today, there are no unique and universal data formatting, data
communication and application protocols for IoT. This means that the
IoT of today is a collection of isolated Intranets of Things that are not
able to interact with each other.
Milis, George, Panayiotou, Christos, & Polycarpou, Marios. (2017). SEMIoTICS: Semantically-enhanced IoT-enabled Intelligent Control Systems. IEEE
Internet of Things Journal, (Special Issue IoT Feedback Control). http://doi.org/10.5281/zenodo.1053854

For all these Things to communicate seamlessly, a common
“language” would be necessary, for devices and applications to
understand each other, regardless of their physical technology
particularities.
Technology is already there, yet still not utilised in its full. It’s been
more than 20 years that Web technologies exist to make data and
services interoperable. Such technologies are related to the Semantic
Web, which is about Things on the internet and widely adopted Web
protocols and standards that make data and services offered by
objects more accessible to a larger pool of (Web) developers. [3]
Milis, George, Panayiotou, Christos, & Polycarpou, Marios. (2017). SEMIoTICS: Semantically-enhanced IoT-enabled Intelligent Control Systems. IEEE
Internet of Things Journal, (Special Issue IoT Feedback Control). http://doi.org/10.5281/zenodo.1053854

The limitations of the IoT become obvious when one wants to
integrate devices from various manufacturers into a single application
or system.
Building cross-functionality applications in buildings would require
smart lights from vendor A, HVAC system from vendor B, air quality
sensors from vendor C, and so on. Making these devices and systems
talk and work with each other will require lots of custom system
integration work.

Building this type of interoperability in custom hard-coding projects, will end
up having systems with zero robustness and big potential maintenance costs;
not to mention the lack of scalability and extensibility, security,
configurability.
In an ideal scenario, any device should be able to seamlessly integrate and
talk to other devices, having its data consumed by any application from any
vendor, regardless of the networking protocols used by those devices.
This is exactly where the Semantic Web would come into play.

It would be beneficial for the IoT to reuse the technology that enables Web services like
Facebook or Google to scale to millions of concurrent users, without compromising on
security or performance.
Until today, the IoT communities have been working mostly on devices and networking
issues. The Semantic Web, on the other hand, has been focusing for decades on the
application layer and the interoperability between data and services.
Properly mapping the devices into the Web layer, makes immediately all Things agnostic to
the physical and transport layer protocols used by the underline devices. What is needed is
only a set of “semantic web drivers”, which will hold a part of the information associated
with a Thing and its virtual existence on the Internet.

The Web has already become the global integration platform for distributed
applications over the Internet. Therefore,this can be extended to the
integration of the physical world applications and services, by hiding the
complexity and differences between various transport protocols used in the
IoT. Developers of IoT applications should focus on the logic of their
applications, without having to deal with the underline technicalities.
If there is no single language to be spoken by all devices, then we need a
transparent translator that will make the interactions seamless. Having such a
“semantic layer” (see Units of Level 3) would minimise the effort requiredto
maintain the system each time a device or service is added, removed, or
updated.

Such a step is realistic today, since devices can have embedded Web
servers with advanced features at low cost. Combining this with the
JavaScript advances, data processing for the language translations
maintenance can happen on the client devices or on cloud services,
thus saving computation power of servers on embedded devices.
When Things are connected on the Web, they will use the same
standards and techniques as traditional Web services. This means
that developers will be able to write IoT applications that interact
with embedded devices in exactly the same way as they write
applications to interact with any RESTful services over Web APIs.

REST is an architectural style for developing distributed applications and is
the basis upon which the modern Web is built. The essence of REST is to
focus on creating loosely coupled services that can be easily reused, which is
implemented using URIs, HTTP and standardized media types.
Abstracting the services from their application-specific semantics thanks to a
uniform interface (HTTP verbs and response codes) makes it easy to build
loosely coupled services, as it provides a simple mechanism for clients to
select the best possible representations for interactions. This makes the Web
the ideal substrate for building a “universal” architecture and Application
Programming Interface (API) to interact with Things.

• In practice, this means developers
can start interacting with Things via
Web browsers. Real-time data
collected from distributed sensors
can then be easily retrieved,
processed and displayed on the
Web, using HTML, CSS and
JavaScript technologies. This is
particularly interesting because it
enables anyone with basic Web
programming skills to build Web
sites and applications with real-time
data from the physical world.

It must be clarified that the Web technologies for the Things can
work equally well in local internets, e.g. in single buildings or
groups of buildings.
In some cases, it would make sense for Things to have a public
URL and be openly accessible over the Web. For example, traffic
or pollution sensors in a city operated by the public authorities
would be useful information in an air quality applicationof a
building in that city.

Web-connected objects can also become active and participate
to the Web as other users, by publishing their own blogs or talk
to each other using the APIs of services such as Twitter.
Leveraging the IoT into the Web represents a natural and very
promising evolution of the IoT, that would overcome a set of
today’s technologicallimitations.

Resources
• https://www.enertiv.com/resources/blog/4-limitations-bms-data
• https://sites.google.com/a/cortland.edu/the-internet-of-things/disadvantages
• https://www.linkedin.com/pulse/advantages-disadvantages-internet-things-iot-
tommy-quek/
• https://www.manning.com/books/building-the-web-of-
things?a_bid=16f48f14&a_aid=wot
• https://iot.ieee.org/newsletter/march-2017/three-major-challenges-facing-
iot.html
• https://www.cmswire.com/cms/internet-of-things/7-big-problems-with-the-
internet-of-things-024571.php
• https://dzone.com/articles/problems-with-internet-of-things-you-need-to-know

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 2 module 6 - unit 4 - v0.9 en

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