The Autonomous Internet of Things: How The IoT Will Become Context-aware And Self-sufficient
The need for contextual intelligence
will become fundamental for a harmonious and self-sustaining IoT in the next
few years
Posted by Chloe
Green www.information-age.com/
on 7 January 2016
The IoT needs a common language
for devices and applications to talk to each other without human intervention
With the recent explosion of news
and updates concerning the Internet of Things (IoT) and its
yet-to-be-fully-determined potential to drastically change the way the world
operates, people could be led to believe this technology has barely arrived on
the technology landscape.
However, sensors and monitors have
been available for decades and have been widely deployed to achieve more
efficient systems in industrial supply chains. It is only now from the scale
and connectedness of devices that it’s actually being referred to as the
'Internet of Things'.
So with this shift comes a need for
streamlined standards and the ability for machines to be able to derive context
from a continuous stream of data. As we now architect many of our technology
platforms to embrace the IoT we stand on a tipping point.
Enormous data
According to
International Data Corporation (IDC), worldwide spending on the IoT will reach
nearly $1.3 billion in 2019, from $698.6 billion in 2015, as reported on Datamation. This growth is
happening because the thresholds have been lowered as devices become cheaper,
more practical and more powerful.
Things have
become smarter in the age of artificial intelligence, algorithmically-driven
software power and big
data. With all these factors combined, an enormous amount
of data is being generated, yet businesses are being held back by their
inability to generate useful insight from that data.
But the IoT is proving its power in
some areas. Among the earliest areas to flourish were sensors for determining
weather patterns and traffic sensors to monitor speed and traffic density and
help people plan journeys.
Additionally, the agriculture and
food production industries make much use of radio-frequency identification
(RFID) tags for livestock. Although many of these initiatives are limited in
geographic scope, they have seen a fair level of standardisation - and this has
been a key facilitator towards progress.
Communities of Things
The next step is to band these
isolated schemes into communities of things. However, for that to become a
reality, more work needs to be done in terms of how communities and the devices
within them interact and how information is shared.
As new broader more standardised
platforms now emerge we will quickly get to a point where actionable insights
can be derived from information streams the IoT feeds to us. This requires
context to be derived from data and interactions.
An example of why context is so
important can be seen with smart labelling for clothes. With smart labels, an
item of clothing could pass data from its label to a washing machine so that
the washing machine could select the correct setting according to what it is
made of. This underpins the need for devices and things to be able to pass
information - or context - between each other.
Machine learning
In order for the IoT to become
widespread, machines and devices must be capable of making decisions
autonomously. This depends on their ability to derive context through machine
learning. When this is achieved, it will allow humans to be taken out of the
equation, driving value and cost efficiencies.
For instance, in agriculture,
sensors can already derive context from RFID tags fitted to animals to alert
owners when an animal has strayed from pasture, cutting down on the time spent
monitoring herds.
If this can be further matured in
the manufacturing, energy, and oil and gas industries, sensors and other
devices that collect data will be able to correlate information to better
manage inventories and allow for the preventive maintenance of expensive
equipment without onsite workers.
Further, cities would become smarter,
replacing the current isolated systems that cannot efficiently talk to each
other and block services from being managed in an integrated manner.
All of this relies on context -
allowing machines and devices to infer meaning from streams of data from disparate
systems. When a common language is developed for devices and applications to
talk to each other without human intervention, we will multiply the
opportunities of the IoT. When this happens, society will be able to move
beyond the concept of smart consumer devices to the smart community.
Sourced from Giri Fox, director
of Customer Technology Services, Rackspace
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