Structural Health Monitoring Using Smart Sensors - ideals ...

logic circuit. However, FPGAs are more expensive and typically have higher power
dissipation than DSPs and GPPs. ASICs can be tailored to perform specific functions
extremely well, and can be made quite power efficient. However, since ASICS are not
field-programmable, their functionality is not easily changed or updated. Also, without
mass production, the initial setup costs are prohibitively high. Smart sensor applications
require multiple tasks, such as wireless communication, data logging, data acquisition,
and diverse signal processing. Among the above-mentioned options, GPPs are best suited
for performing a broad array of tasks. When tasks on smart sensors include intensive data
processing, a DSP or an FPGA can be used in combination with a GPP to improve data
processing performance. Once smart sensor applications are well-understood, the
necessary functions may be refined and ASIC may be implemented to perform specific
tasks. Smart sensors on the market targeting a broad range of applications, in most cases,
utilize only a GPP. If deemed advantageous, smart sensor systems developed on a GPP
can then be improved by utilizing special purpose microprocessors such as DSP, FPGA,
and ASIC.
2. Sensing capability
A smart sensor is able to convert the physical state of an object or environment such
as temperature, light, sound, and/or motion into electrical or other types of signals that
may be further processed. A single smart sensor node may have several sensors measuring
different physical quantities. Micro-Electro-Mechanical System (MEMS) devices, which
are the integration of mechanical elements, sensors, actuators, and electronics on a
common silicon substrate through microfabrication technology, are often employed for
sensors because of their small size, inexpensive cost (when mass produced), and low
power consumption. Data acquisition parameters, such as sampling frequency and data
length, can be controlled by the on-board processor. The on-board microprocessor can
also access and process the acquired data. The sensing capability provides the interface
between the smart sensor's on-board microprocessor and real-world physical phenomena.
One of the promising technologies in sensors is the use of quasi-digital sensors, such
as frequency, duty-cycle, and pulse number output sensors, as proposed by Kirianaki et al.
(2000) and Yurish (2005). Low noise sensitivity, wide dynamic range, and a simple
interface which is directly connected to microprocessors are advantages of the quasidigital
sensors. The use of quasi-digital sensors is increasing. For example, the Intel Mote
developed by Intel Corporation (Kling, 2004) utilizes a duty cycle output accelerometer.
3. Wireless communication
Smart sensors communicate with each other through a wireless link. While RF
communication is most widely used, smart sensors with different transmission media,
such as acoustic, laser, and infrared transmission, have also been studied (Hollar, 2000).
Acoustic communication utilizes a sounder and a microphone. The microphone requires
little power, while the sounder power is comparable to low power RF devices; these
features are very attractive from a power saving perspective. Some disadvantages in
acoustic communication include the following: the surrounding background noise limits
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