Guest Editors' Introduction: Hostile Environments
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Citation
Lukowicz, Paul, Mary G. Baker, and Joseph Paradiso. “Guest
Editors’ Introduction: Hostile Environments.” IEEE Pervasive
Computing 9.4 (2010): 13–15. Web. © 2012 IEEE.
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http://dx.doi.org/10.1109/MPRV.2010.80
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IEEE Computer Society
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GUEST EDITORS’ INTRODUCTION
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ostile environments are a particularly relevant application
of pervasive computing. The
technology can save lives by
both eliminating the need for
humans to work in these environments and
supporting them when they do. Examples of
application areas include fi rePaul Lukowicz
fighting,1 search and rescue, 2
University of Passau, Germany
the military, 3 and environmental monitoring.4,5 PotenMary G. Baker
tially hostile environments for
HP Labs Palo Alto
humans include outer space,
caves, the arctic, deserts, junJoseph Paradiso
gles, underwater, and certain
MIT Media Lab
industrial or research settings,
such as nuclear power stations, accelerator beamlines,
biohazard zones, and chemical plants. Significant challenges for pervasive systems are often
also found in sports (for example, swimming6
Published by the IEEE CS ■1536-1268/10/$26.00©2010IEEE
or skiing7 ), which can at times involve user
risk.
In general, environments that are hazardous
to humans are hard on technology as well. Of
course, nonhazardous situations can also strain
the technology—for example, monitoring machinery that creates intensive, high-frequency
vibrations can be hard on the electronics without being dangerous to humans.
Applications in Hostile Environments
We can distinguish three broad categories of
applications in hostile environments, which
are exemplified by the articles in this special
issue.
Environmental monitoring is the traditional domain of sensor networks and has a
large pool of research and applications.8 Devices record and forward simple parameters,
often over large areas and extended time periods. Such applications facilitate the study of
PER VA SI V E computing 13
GUEST EDITORS’ INTRODUCTION
the AUTHORS
Paul Lukowicz is a professor of computer science at the University of Passau,
Germany. His research interests include pervasive and ubiquitous computing,
particularly activity and context recognition and wearable systems. Lukowicz
has a PhD in computer science from the University of Karlsruhe, Germany. Contact him at paul.lukowicz@uni-passau.de.
Mary G. Baker is a senior research scientist at HP Labs Palo Alto. Her research
interests include distributed systems, networks, mobile systems, and digital
preservation. Baker has a PhD in computer science from the University of California, Berkeley. She’s a member of Usenix, the ACM, and IEEE. Contact her at
mary.baker@hp.com.
Joseph Paradiso is an associate professor of Media Arts and Sciences at MIT
Media Lab, where he directs the Responsive Environments Group, which explores how sensor networks augment and mediate human experience, interaction, and perception. Paradiso has a PhD in physics from MIT’s Lab for Nuclear
Science. He’s a senior member of IEEE and the American Institute of Aeronautics and Astronautics, and a member of the American Physical Society, the
ACM, and Sigma Xi. Contact him at joep@media.mit.edu.
environments that are hostile or not
easily accessible without endangering
humans. In this issue, Marcus Chang
and Philippe Bonnet’s article on arctic
monitoring represents this category.
Going beyond monitoring of simple parameters, pervasive computing also offers situational awareness
and tactical support, assisting teams
engaged in activities in hazardous environments with complex, integrated
information and extended communication and collaboration capabilities.1
The article on wildfire monitoring by
Cristina Barrado and her colleagues
exemplifies this domain.
Pervasive systems can also focus on
the individual, enhancing his or her
ability to deal with a hazardous situation. Functionality can range from
guidance support and advanced communication capabilities to hazard
warnings.9 In most cases, appropriate user interfaces are a key issue, and
wearable computing solutions play
an important role. In this issue, the
LifeBelt article by Alois Ferscha and
14 PER VA SI V E computing
Kashif Zia is an example of such an
application type.
Technology challenges come mainly
from four sources:
• the harshness of the environment, in
which factors such as temperature,
vibration, or radiation have significant impact on hardware reliability
and stability and require special
precautions;
• the environment’s impact on the system’s ability to function correctly,
in particular with respect to sensordata collection and communication;
• the need for safety-critical systems
with high data reliability and accuracy; and
• the need for interaction concepts
that provide full access to the required functionality without distracting the user from the physical
world.
Although such interaction requirements in this last challenge are common of many pervasive systems,
they’re particularly critical and
difficult in hostile environments,
where undue distractions can be life
threatening.
In This Issue
This issue contains three articles and
a Spotlight column, all of which illustrate many of the issues discussed
here.
Chang and Bonnet’s article, “Monitoring in a High Arctic Environment:
Some Lessons from MANA,” is an
experience report illustrating the
challenges involved in water-quality
monitoring in a remote arctic region.
The system consists of sensing buoys
deployed on a lake and a base station
that receives, processes, and forwards
the data. Discussion includes handling temperatures as low as -40º C
combined with humidity and winds;
power supply considerations; communications system design; and deployment problems.
The Spotlight column, “The IceCube Detector: A Large Sensor Network at the South Pole,” by Martin
Merck, takes place at the opposite end
of the Earth, and describes challenges
involved in deploying the IceCube
neutrino observatory—essentially a
large sensor network comprised of
many phototubes deployed deep in
the Antarctic ice to detect neutrinos
for cosmic ray physics research. Sensor networks are a core technology of
ubiquitous computing, and this article
indeed describes an extreme implementation of one.
“Wildfire Monitoring Using a
Mixed Air-Ground Mobile Network” by Barrado and her colleagues
describes a mobile ad hoc network
solution for forest-fire-hot-spot localization that consists of unmanned
aerial devices equipped with infrared
sensors, a set of relay balloons that
improve communication quality,
and ground vehicles. The article focuses on communication design and
quality.
Ferscha and Zia’s “LifeBelt: Crowd
www.computer.org/pervasive
Evacuation Based on Vibro-Tactile
Guidance” describes a vibro-tactile
belt designed to help people find their
way out of a building in an emergency. The article briefly sketches
the devices, then models their influence on large-scale evacuations. This
article exemplifies an emerging trend
in pervasive computing research—
examining the impact of technology
on collective behavior.
Pervasive Computing, vol. 4, no. 1, 2005,
pp. 72–79.
and Monitoring Professional Skiers,”
IEEE Pervasive Computing, vol. 4, no. 3,
pp. 40–46.
3. S. Julier et al., “BARS: Battlefield Augmented Reality System,” Proc. NATO
Symp. Information Processing Techniques for Military Systems, 2000; http://
handle.dtic.mil/100.2/ADP010892.
8. I.F. Akyildiz et al., “Wireless Sensor Networks: A Survey,” Computer Networks,
vol. 38, no. 4, 2002, pp. 393–422.
9. P. Lukowicz et al., “WearIT@Work:
Toward Real-World Industrial Wearable
Computing,” IEEE Pervasive Computing, vol. 6, no. 4, 2007, pp. 8–13.
4. R. Szewczyk et al., “An Analysis of a
Large Scale Habitat Monitoring Application,” Proc. 2nd Int’l Conf. Embedded
Networked Sensor Systems, ACM Press,
2004, pp. 214–226.
5. J. Partan, J. Kurose, and B.N. Levine,
“A Survey of Practical Issues in Underwater Networks,” ACM SIGMOBILE
Mobile Computing and Communications
Review, vol. 11, no. 4, 2007, pp. 23–33.
REFERENCES
1. X. Jiang et al., “Ubiquitous Computing
for Firefighters: Field Studies and Prototypes of Large Displays for Incident Command,” Proc. SIGCHI Conf. Human Factors in Computing Systems, ACM Press,
2004, pp. 679–686.
6. M. Bächlin, K. Förster, and G. Tröster,
“SwimMaster: A Wearable Assistant for
Swimmer,” Proc. 11th Int’l Conf. Ubiquitous Computing (Ubicomp 09), ACM
Press, 2009, pp. 215–224.
2. I. Nourbakhsh et al., “Human-Robot
Teaming for Search and Rescue,” IEEE
Selected CS articles and columns are also available for free at http://ComputingNow.computer.org.
7. F. Michahelles and B. Schiele, “Sensing
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