The chip that tells your smartphone which way is up has been
used to detect earthquake-scale forces accurately. If further
testing proves successful, smartphones could be turned into a
network of seismometers that together tell emergency services where
to respond first.
The testing was done by a pair of seismologists from the
National Institute of Geophysics and Volcanology, Antonino
D'Alessandro and Giuseppe D'Anna, who initially put forward the
proposal in April 2013 in a paper entitled "Can mobile phones be
used in strong motion seismology?" and have now published their results in the Bulletin of the
Seismological Society of America.
The chip in question is the Micro Electro-Mechanical Systems
(MEMS) accelerometer, commonly found today in smartphones and
laptops. In the former it flips the home screen the right way round
by measuring movement across three axes. For the experiments, the
LIS331DLH chip was used, found in both the iPhone 4 and iPhone 5.
Using readings from the EpiSensor FBA ES-T seismometer as a point
of reference, D'Alessandro and D'Anna set the phone sensor on a
vibrating table (typically used in seismology studies).
Although the pair found the iPhone chip had "excellent frequency
and phase response, comparable with that of some standard FBA
accelerometer used in strong motion seismology", it was not
senstitive enough to pick up earthquakes of magnitudes of 5 or
under and must be near the epicenter of the quake. Earthquakes
under 5 on the Richter scale should only cause minimal internal
damage, and not result in building collapses, therefore there is
still ample argument for using smartphone chips in organisng
emergency response networks.
"The rapid development of this technology will lead in the
coming years to the development of high sensitivity and low noise
digital MEMS sensors that may be replace the current seismic
accelerometer used in seismology," the authors predict. Since we'll
have more sensitive MEMS sensors soon, it makes sense to carry out
these studies now, considering the high penetration of these
devices in many at-risk areas including urban centre. "Actually,
the main advantage of these sensors is their common use in mobile
It was found, however, that the chip underestimates the
acceleration of the force a touch, so the authors suggest it be
calibrated before results are processed.
If used today, measurements of the worst earthquakes --
including GPS location data of where the tremors were strongest --
could be sent to a central command centre, which would then
administer instructions on where to send the most relief
"The number of victims following a strong earthquake depends
mainly on the intensity of shaking, and the speed of rescue
operations," said D'Alessandro. "A real-time urban seismic network
can drastically reduce casualties in urban areas immediately
following a strong earthquake, by quickly distributing information
about the distribution and intensity of ground shaking."
This is not the first time a smartphone's sensors have been put
forward as possible replacements for traditional seismometer
networks. A team of seismologists published an article in a University of
California, Berkeley annual report
comparing the sensors in iPhone and Android devices. In the study,
it was determined the sensors could tell the difference between
different activities including walking and running, and an
Text alert systems and apps have already been developed to aid
in emergency recovery work. In many cases, time is the most
critical factor when it comes to relief work and these technologies
help get the right people to the right places, quicker. This week
MIT's Computer Science and Artificial Intelligence Laboratory and
the Qatar Computing Research Institute announced an add-on to the App Inventor, which will allow
anyone to build an emergency response app that pulls in data from a
variety of sources in real time. All the data used in an app built
with the tools will have to be formatted according to the resource
description framework, the basis of the Semantic Web and a format
which allows for more precise searches. An app built using MIT's
tools would be able to pull in data from multiple online sources,
and organise only the relevant snippets in real time.
"As people use these apps more, they will automatically generate
structured data," said Lalana Kagal, an MIT research scientist
working on the tools. "And as there's more structured data out
there, there will be people building more apps to consume them,
which will in turn generate more structured data."
Of course all these advancements rely on widespread reliable
internet connections, not a sure thing in poorer regions.