The number of devices connected via Internet of Things is increasing every day.
However, many obstacles will need to be overcome before we truly have a completely
smart and secure Io T system.
Over the past several years, the number of devices connected via Internet of Things (Io T) has grown
exponentially, and it is expected that number
will only continue to grow. By 2020, 50 billion
connected devices are predicted to exist,
thanks to the many new smart devices that
have become standard tools for people and
businesses to manage many of their daily
Smart connected devices boost customer’s
engagement, increase visibility, and
streamline communications, especially
with new human-machine interfaces like
Voice User Interface (VUI) the favorite
interface for new digital assistants like
HomePod, Alexa and Google Assistant for
a good reason—80 percent of our daily
communications is conducted via speech.
In the future, Io T will continue to
advance at an extraordinarily rapid pace,
with remarkable growth in many directions.
The ultimate goal is to have a smart and
completely secure Io T system, however many
obstacles will need to be overcome before that
goal can become a reality.
Io T and blockchain convergence
The current centralized architecture of Io T is
one of the main reasons for the vulnerability
of Io T networks. With billions of devices
connected and more to be added, Io T is a big
target for cyber attacks, which makes security
Blockchain offers new hope for Io T security
for several reasons. First, blockchain is public,
everyone participating in the network of
nodes of the blockchain network can see
the blocks and the transactions stored and
approves them, although users can still
have private keys to control transactions.
Second, blockchain is decentralized, so there
is no single authority that can approve the
transactions eliminating Single Point of
Failure (SPOF) weakness.
Third and most importantly,
it’s secure—the database
can only be extended
and previous records
cannot be changed.
In the coming years
recognize the benefits
of having blockchain
technology embedded in
all devices and compete
for labels like “Blockchain
Io T investments on the rise
Io T’s undisputable impact has and
will continue to lure more startup venture
capitalists towards highly innovative
projects in hardware, software and services.
Spending on Io T will hit 1.4 trillion dollars
by 2021 according to the International Data
Io T is one of the few markets that has
the interest of the emerging as well as the
traditional venture capitalists. The spread of
smart devices and the increase dependency
of customers to do many of their daily tasks
using them, will add to the excitement of
investing in Io T startups. Customers will be
waiting for the next big innovation in Io T—
such as smart mirrors that will analysis your
face and call your doctor if you look sick,
smart ATM machine that will incorporate
smart security cameras, smart forks that
will tell you how to eat and what to eat, and
smart beds that will turn off the lights when
everyone is sleeping.
Fog computing & Io T
Fog computing is a technology that
distributed the load of processing and moved
it closer to the edge of the network (sensors
in case of Io T). The benefits of using fog
computing are very attractive to Io T solution
providers. Some of these benefits allow
users minimize latency, conserve network
bandwidth, operate reliably with quick
decisions, collect and secure a wide range
of data, and move data to the best place for
processing with better analysis and insights
of local data. Microsoft just announced a $5
billion investment in Io T, including in fog/
AI & Io T will work closely
AI will help Io T data analysis in the following
areas: data preparation, data discovery,
visualization of streaming data, time series
accuracy of data, predictive and advance
analytics, and real-time geospatial and location
(logistical data). Here are a few examples.
Data preparation: Defining pools of data
and cleaning them, which will take us to
concepts like Dark Data and Data Lakes.
Data discovery: Finding useful data in
defined pools of data.
Visualization of streaming data:
On-the-fly dealing with streaming data by defining,
By Ahmed Banafa, San Jose State University
Credit: Ahmed Banafa