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mechanical process automation, repetitive tasks are completed by machines rather than humans [1].
Rule-based automation typically refers to using a humanprovided set of rules to collect, sort, and store data. In the
context of I&M, this typically comes into play with how the
measurement data is processed. For example, in manufacturing applications, it can be used to perform data fusion on
non-identical sensors and to help improve diagnosing faults
in machinery [2]-[4]. In autonomous vehicle applications, it
can be used to help connected vehicles merge onto highways
or to improve fuel efficiency [5], [6]. As an aside, connectivity
is an important aspect of making autonomous vehicles feasible
on a wide scale, but it is also important in many other application realms and is growing in importance with the advent of
IoT. Thus, connectivity will later be discussed as its own Trend
of Choice. Rule-based automation can also be used in nondestructive evaluation (NDE) to help automate the process of
detecting and analyzing damage in parts or structures from
measurement data [7], [8].
Automation also has the potential to improve safety. An
example of this is using robots to perform NDE on civil and
aerospace structures, removing the human inspector from potentially dangerous situations [9], [10]. Another example is
helping vehicles perform tasks like sense objects in their blind
spots or parallel park, in turn helping the human driver. These
are cases in which there is a human involved in the decisionmaking process.
The challenge of scalability is seen in all of these application realms and with all different types of automation. It is seen
in attempting to make an entire manufacturing process automated, in utilizing autonomous vehicles when not all vehicles
are connected and communicating to each other, and in trying
to perform NDE on a large number of parts or on large structures. Across these application realms, another challenge is
the choice of whether or not to remove humans from the decision-making process. Due to liability concerns, we may not see
humans removed from the process in the next five years, but
as automation becomes more widespread and our automation
processes improve, the role of humans is expected to continually decrease [11]. Thus, enhanced efficiency, productivity, and
safety and the convenience provided to humans will continue
to propel automation as a trend in the I&M community.
Another Trend of Choice is miniaturization. With the advent of
new nanofabrication techniques, such as extreme ultraviolet lithography, circuits can be made smaller and smaller, allowing
for smaller instruments [12]. As the utility of these new nanofabrication techniques become more prevalent, quicker and
less expensive manufacturing process is will result. Differentiated silicon and system level integration capabilities have also
been at the forefront of CMOS R&D, with the goal of achieving smaller and smaller device form factors [13]. In addition
to CMOS-type nanofabrication, MEMs and nanomaterials are
other types of nanotechnology that have also contributed to
miniaturization of instrumentation.
In the area of nanotechnology, I&M has played a critical role. This role centers around the need to accurately and
4	

repeatedly measure characteristics, such as feature size and
capacitance, on the nanoscale. As smaller features are manufactured (e.g., going to 5 nm or less nanofabrication limits)
and new nanomaterials are developed, measurement systems
must also advance in order to keep up [14].
Miniaturization has also been facilitated by the use of fiber optics. Fiber optics have the advantage of being compact,
lightweight, sensitive, rugged, and capable of performing distributed sensing [15]-[17]. These advantages have resulted in
the creation of new fiber-based instruments, such as Lidars
and anemometers [18]-[21].
Some application areas in which miniaturization has seen
major growth and advancement are in the healthcare and environmental sensing. In the area of healthcare, for example,
technologies enabled by miniaturization include compact
instrumentation for blood impedance and respiratory rate
measurements, and implantable biodegradable sensors
[22]-[25].
As sensors and instruments become smaller and more
affordable and automation becomes more prevalent, the possibility of having connectivity between these devices grows.
Connectivity allows systems and programs to exchange information and communicate with each other. Increasingly, it also
enables us to communicate in more extreme environments. In
the context of I&M, monitoring conditions in extreme environments with a variety of instruments becomes increasingly
possible. This is seen in applications like underwater acoustic
monitoring and remote sensing [26]-[28].
Through the IoT, connectivity has also started to touch every aspect of our daily lives, bringing us closer to the internet
of everything (IoE). From smart household appliances to structural health monitoring (SHM) to power grids to the vision of
smart cities, IoT allows connectivity to be achieved on the individual, household, city, and industrial levels. Thus, devices
capable of communicating to each other and providing critical information required to make decisions are becoming more
prevalent, and connectivity has become a Trend of Choice.
This growing level of connectivity has the potential to introduce many benefits, but it is not without challenges and risks.
In the case of IoT-enabled SHM, smart sensors can be used to
measure physical quantities, send the information to either
other sensor nodes or a processing station, and use the collected information to make decisions and assess the health of
the structure being monitored. This results in improved safety
and the ability to perform maintenance more effectively. In traditional SHM systems, invasive and bulky wired solutions,
such as coaxial line sensors, have been used. By integrating IoT
with SHM, the sensors used can send information wirelessly,
allowing for less accessible areas to be monitored and for the
invasiveness of the SHM system to be reduced by not requiring communication cables connecting the sensors. This results
in more efficient and potentially continuous monitoring of
structures, which increases the possibility of detecting damage
before it becomes critical [29], [30].
In the case of power grids, reliable and accurate measurement data is required to properly monitor and control power

IEEE Instrumentation & Measurement Magazine	

May 2020



Instrumentation & Measurement Magazine 23-3

Table of Contents for the Digital Edition of Instrumentation & Measurement Magazine 23-3

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