TECHNOLOGY AT WORK

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Citi GPS: Global Perspectives & Solutions February 2015
monitoring of equipment and infrastructure, and with algorithms able to identify
anomalous conditions, installation, maintenance and repair jobs are becoming
increasingly automatable.
Sensors have improved the monitoring of
people in health and workplace scenarios
Advances in machine learning technologies
have directly contributed to the growth of
wearables
Perhaps more profound are the implications of using the IoT to improve the
monitoring of people. Particularly relevant are recent innovations in wearable
devices such as the Apple Watch and FitBit Surge, which are equipped with
increasingly sophisticated sensors capable of measuring heart rate and activity
levels. Healthcare occupations will be affected by such sophisticated sensors and
algorithms, including the clinical staff responsible for monitoring the state of patients
in intensive care. Remote health monitoring may decrease the need for hospitals
and attendant workers, with technology allowing some patients to stay at home, with
their anomalous health conditions identified by machine learning algorithms. The
comprehensive monitoring of consumers with wearables may allow stores to further
automate retail. For example, a business may use heart rate measurements to
assess a customer's emotional reaction to the product they have just picked up (as
detected by the sensor on the product) and, depending on the assessment, then
use the wearable device to make product recommendations. Employees equipped
with wearable devices would also be much more thoroughly monitored than is
currently possible, enabling employee compensatory schemes that are much more
difficult to 'game'. Similar devices, again reliant on machine learning techniques to
identify anomalies, might allow also for further automation of fraud detection and tax
evasion.
Advances in machine learning technologies have directly contributed to the growth
in wearables by permitting improved user interfaces. In particular, intelligent user
interfaces that can understand a wider range of user intentions are enabling smaller
and more intuitive devices. For example, the predictive text capabilities of
companies such as SwiftKey can correct for user's typing mistakes by learning their
distinctive patterns of writing. Apple's Siri and Google Now use intelligent software
to recognise spoken words, interpret their meanings, and act on them accordingly,
even in the presence of ambient noise. These technologies allow a more efficient
means of obtaining rich data from a human user, enabling automation by better
access to human tacit knowledge. Moreover, these technologies may directly
substitute for occupations requiring human interaction. For example, a company
called SmartAction now provides call computerisation solutions that use advanced
speech recognition software that have realised cost savings of 60% to 80% over an
outsourced call centre consisting of human labour. 60
The IoT finds significance in that the volume of rich, heterogeneous data it delivers
will better allow algorithms to understand and influence the physical world. This is in
contrast to most current sources of big data (e.g. e-commerce), which are relevant
only to our digital behaviours. Increasingly intelligent algorithms can hence be
brought to bear on the automation of the many jobs that involve interacting with our
physical environment.
Sensors are Driving Automation
Jim Suva, CFA
US IT Hardware & Supply Chain Analyst
Arthur Lai
Asian Display and Touch Panel Analyst
Manufacturing has continued to adapt — first shifting to low-cost labour, then to tax
holiday havens, and now to lowest landed total costs (a mixture of shipping, labour,
taxes, real estate, etc.) — all the while embracing technology innovation of which
sensors and connectors have become increasingly important.
60 Canadian Automobile Association (2012).
© 2015 Citigroup