Certain trends, such as ‘wearables’, get a lot of media
attention because of their obvious visibility and relevance to the man in the
street. Because of a small electronic bracelet on his wrist, a person can now
measure the number of steps he takes in a day, his sleep patterns, his heart
rate and a host of other data that always existed but simply didn’t resonate.
A person might decide to change his lifestyle as a result –
perhaps walk more to achieve a target, or go to bed at a certain time to
maximize his sleep. He can measure his progress every day by looking at his
wearable device, in the pursuit of better health.
You may think the transformative element is the wearable
device, some sleek bracelet he wears on his wrist, but it’s not. The device is merely a means, the transformative
element is data.
Armed with data, a person can make decisions he could not
make before. He can measure how far he
is progressing against his goals, and set new goals as he achieves the old
ones, because now, he receives a constant stream of data from the device on his
wrist.
Just as data can transform a person’s life by providing
information, on a large scale, the same means can change an organization and the
way it works.
All organisations need data – on how well they’re doing,
which products are selling better in which markets, on their profit margins, on
their resellers, their suppliers and so on.
Most of the time, an organization has to wait for a period for the data
– whether that’s the end of the day when the sales are tallied, or the end of the week for a
weekly report, or the end of the year for the accounts to be drawn.
Based on that, an organization may decide to take certain
actions – to change its product mix, to change its selling price, to make
changes to its products and services, in order to do better.
What if the organization now received data far more quickly
– say, immediately – of exactly what was happening at this very instant?
Just like the wearable measuring the number of steps taken
by a person, or his sleep patterns, what if a product could ‘talk’ and send
back data about its condition – where it was, where it was heading, what its
storage conditions were like, and how long it’s been sitting on the shelf?
Self-reporting products and services aren’t a pipe dream,
but reality, for just like that wearable device, they are part of that large
group of technologies loosely called the Internet of Things, more conveniently
abbreviated to “IoT”.
The IoT can be a completely transformative technology
because it can allow an organization to ‘see’ and understand things that were
invisible before.
Simply put, the IoT is the connectedness of things. Things – whether a retail product, a piece of
machinery, or a condition, such as person’s health – can be measured and
reported in real time. Tiny measuring
devices – and there are well over half-a-dozen in your smartphone, and dozens
in your car, by the way – can sense various conditions, and connectedness
allows them to transmit this data.
Data by itself makes no sense - a temperature is only a
number, the number of steps walked is just a number – but in context, data
becomes very meaningful – a machine part is overheating, the number of steps
walked is below the desired threshold.
Data doesn’t have to have a human at the other end – there
must be few less boring jobs than staring at a constant stream of data – but
what if that data could, by itself, make sense? If the temperature reading went
above a certain value, the computer would beep loudly, prod its human operator,
or provide feedback to the machine to slow down and cool itself off.
This is already happening. In the manufacturing industry,
downtime of a production line, for example, can be very costly in terms of lost
sales or in meeting a deadline. Sensors
constantly monitor machine vibration and temperature, informing their human
operators that maintenance is due before a breakdown occurs. This can be
automated, so that instead of informing a human, the data triggers a mechanized
control system which takes corrective action – shifting the workload to an
alternate line, for example while producing an alert to a technician to
investigate the machine before it actually fails.
In agriculture, soil sensors monitor local soil humidity –
the data is fed into a precise drip irrigation system which irrigates according
to the soil moisture in each particular location, as compared to traditional
flood irrigation which uses far more water, by irrigating field
indiscriminately.
Lots and lots of data could also have hidden patterns within
–Do sales peak at certain times of the day? Does factory production vary
depending on the day of the week? Does a
staff supervisor calling in sick for the day have an effect on overall
productivity? Which colour product sells better on cloudy days compared to
sunny days?
Data is often most useful when it is combined with other
data to provide fresh and meaningful insights.
Location data of vehicles can be combined with a map to provide precise
location services which could be used in mapping traffic flows in a city, or
identifying hotspots of clumped or stalled traffic. Further combined with weather data, the
emerging picture could be even more useful – if heavy rains are expected, car
drivers can be alerted early to avoid certain roads which are known to flood in
heavy rain.
Similarly, embedded road sensors can inform of the traffic
volume on a stretch of road and average travel times. Combined with other data,
such as CCTV data, the cause of slow moving traffic can be identified – perhaps
a car pulled over, or an accident, or other obstruction.
The IoT is a technology that provides near or real time
data, the transformation occurs in how that data is used. Driving patterns of drivers can be monitored
in real time – after all, why should a driver who only uses her car a few times
a week to drive to the local supermarket pay the same insurance premium a young
man who drives often and recklessly?
Aged patients no longer need to travel to the hospital to
have their vital signs read. Remote sensors can monitor their blood sugar
level, pulse rate, temperature, blood pressure, even their movement, or lack of
movement – in the comfort of their homes.
This can dramatically reduce healthcare and manpower costs, freeing
nurses to spend more time with other patients, while reducing travel times and
inconvenience for patients.
Users who know their exact electricity consumption at any
point in time have been shown to adopt more prudent habits than users who only
knows the electricity consumption at the end of the month. Smart electric meters, being rolled out in
many parts of the world, allow this on-the-spot view.
The IoT is becoming more pervasive, thanks to a number of
factors, such as the miniaturization of technology, always-on connectivity, the
continuing decline in the cost of technology and the business need to become
more efficient and competitive. Reducing
cost is just one aspect; the real magic happens when the technology of
real-time data from hundreds, thousands, millions of connected objects, changes
the way organisations work.
In Malaysia, MIMOS, the Malaysian R&D organization
estimates that the economic impact of the technology to be 9.5 Billion Ringgit
to the Gross National Income (GNI) by 2020, increasing to RM42.5B by 2025. Underlining its importance, in 2015, the
Ministry of Science, Technology and Innovation (MOSTI) unveiled the National
Strategic Roadmap for the Internet of Things.
The IoT is also specifically mentioned in the 11th Malaysia
Plan (2016-2020).
Savvy Malaysian CIOs in manufacturing companies have begun
to implement systems that make their organisations stronger and leaner. A Government agency has issued a bid for an
early flood-warning system based on a system of sensors, and even CIOs in large
banks have begun to explore how this technology can give them a competitive
edge.
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