Spectrometers measure the light
spectrum to gauge the amount and
type of chemicals present in a given
sample of material. But even today’s
powerful smartphone cameras were
never intended for this kind of intensive optical analysis.
“The camera was never designed for
sampling,” says Li. “It was designed for
taking pictures at a distance.” To compensate for the limitations of tiny lenses, Li and his team fashioned a special
prism array capable of dividing incoming light into waves for processing.
Most of the technical challenges came
in trying to fabricate the prism array itself; the software application was comparatively easy to develop using standard image processing routines.
In the past, large hospitals would
have expected to pay up to $500,000
for a top-of-the-line spectrometer; a
more basic model might run as little
as $10,000. While Li’s device won’t fully supplant those kinds of machines,
it could make spectrometer-based
analysis available to smaller hospitals
and clinics in rural areas or developing
countries, thus bringing the technique
within reach of patients who might
otherwise never have access to this
kind of diagnostic capability.
At the University of Washington, a
team of doctors and engineers partnered
to create a smartphone-based device
called BiliCam that allows doctors and
new parents to identify signs of jaundice,
a common affliction of newborn babies.
The system consists of an app that
invokes a standard smartphone camera and flash, along with a printed card
used to calibrate color with a range of
different lighting conditions and skin
tones. By taking a photo of the baby’s
skin in proximity to the card, a parent
or healthcare provider can then use
the app to submit the photo to a cloud-based system that analyzes the data using machine-learning algorithms, then
generates a report on the baby’s bilirubin levels that it can send back almost
instantly to a parent’s smartphone.
Beyond image-processing applications, the sheer computing power
of smartphones—the Samsung S7
handset now boasts far more processing power than a supercomputer
from the mid-1990s—opens the door
to a wide range of other pocket-sized
scientific instruments.
In the U.K., a company called Oxford Nanopore Technologies builds
compact devices known as nanopore
sequencers for genetic analysis; they
utilize a highly cost-effective approach
that allows a single molecule of DNA or
RNA to be analyzed via electrical conductivity (as opposed to more resource-intensive solid-state methods). The
method makes genetic sequencing
more readily available to researchers
for a wide range of purposes: identifying pathogens in food or water, monitoring environmental conditions for
climate science, or even sequencing
the human genome. Nanopore sequencing also holds promise for a wide
range of other scientific applications
including plant research, population
genomics, and microbiology.
In 2014, the company released MinION, a nanopore sequencer that weighs
under 100 grams and plugs into a PC
or laptop via a USB cable. With prices
starting at $1,000, the device is making
genetic sequencing widely available to
a range of researchers who might not
otherwise have access to sequencing
technology. It has already been used for
surveillance of Zika in Brazil and Ebola
in Guinea, and has even found its way
onto the International Space Station.
Oxford Nanopore is now taking this
work a step further with its as-yet-unre-leased SmidgION, a sequencer attachment that snaps onto a smartphone
running specialized software.
The proliferation of mobile processing power will not only make
high-powered scientific instruments
more readily available to researchers,
At the University
of Washington, a
smartphone-based
device allows doctors
and new parents
to identify signs
of jaundice,
an affliction common
to newborn babies.
Milestones
Labarta
Recognized
with ACM-IEEE
Kennedy Award
ACM and IEEE recently named
Jesús Labarta of the Barcelona
Supercomputing Center and
Universitat Politècnica de
Catalunya as the recipient of
the 2017 ACM-IEEE CS Ken
Kennedy Award.
Labarta was recognized
for his seminal contributions
to programming models and
performance analysis tools for
high performance computing.
Throughout his career,
Labarta has developed tools for
scientists and engineers working
in parallel programming. In
the programming models
area, he made fundamental
contributions to the concept
of asynchronous task-based
models and intelligent runtime
systems. In the performance
tools area, Labarta’s team
develops and distributes
Open Source Barcelona
Supercomputer Center
tools designed to analyze an
application’s behavior and
identify issues that may impact
performance.
Labarta is director of
the Computer Science
Department at the Barcelona
Supercomputing Center and
a professor of Computer
Architecture at the Universitat
Politècnica de Catalunya.
From 1996 to 2004 he served
as director of the European
Center of Parallelism of
Barcelona. He has been
involved in research and
cooperation with many leading
companies on HPC-related
topics. Currently, he is the
leader of the Performance
Optimization and Productivity
EU Center of Excellence, where
more than 100 users (both
academic and SMEs) from a
very wide range of application
sectors receive performance
assessments and suggestions
for code refactoring efforts.
ACM and IEEE co-sponsor
the Kennedy Award, which was
established in 2009 to recognize
substantial contributions
to programmability and
productivity in computing
and significant community
service or mentoring
contributions. The Award
carries a $5,000 honorarium
endowed by the SC Conference
Steering Committee.