Wireless Sensor Networks

Only available on StudyMode
  • Topic: Wireless sensor network, Sensor, Sensor node
  • Pages : 30 (8501 words )
  • Download(s) : 190
  • Published : April 23, 2013
Open Document
Text Preview
1. Introduction
The increasing interest in wireless sensor networks
can be promptly understood simply by thinking
about what they essentially are: a large number of
small sensing self-powered nodes which gather information
or detect special events and communicate in a wireless
fashion, with the end goal of handing their processed
data to a base station. Sensing, processing and communication are three key elements whose combination in one
tiny device gives rise to a vast number of applications
[A1], [A2]. Sensor networks provide endless opportunities,
but at the same time pose formidable challenges,
such as the fact that energy is a scarce and usually
non-renewable resource. However, recent advances in
low power VLSI, embedded computing, communication
hardware, and in general, the convergence of computing
and communications, are making this emerging technology
a reality [A3]. Likewise, advances in nanotechnology
and Micro Electro-Mechanical Systems (MEMS) are
pushing toward networks of tiny distributed sensors and
actuators.
2. Applications of Sensor Networks
Possible applications of sensor networks are of interest to
the most diverse fields. Environmental monitoring, warfare,
child education, surveillance, micro-surgery, and
agriculture are only a few examples [A4]. Through joint
efforts of the University of California at Berkeley and the
College of the Atlantic, environmental monitoring is carried out off the coast of Maine on Great Duck Island by
means of a network of Berkeley motes equipped with various
sensors [B6]. The nodes send their data to a base
station which makes them available on the Internet. Since
habitat monitoring is rather sensitive to human presence,
the deployment of a sensor network provides a noninvasive
approach and a remarkable degree of granularity
in data acquisition [B7]. The same idea lies behind the
Pods project at the University of Hawaii at Manoa [B8],
where environmental data (air temperature, light, wind,
relative humidity and rainfall) are gathered by a network
of weather sensors embedded in the communication
units deployed in the South-West Rift Zone in Volcanoes
National Park on the Big Island of Hawaii. A major concern
of the researchers was in this case camouflaging the sensors to make them invisible to curious tourists. In Princeton’s Zebranet Project [B9], a dynamic sensor network
has been created by attaching special collars equipped
with a low-power GPS system to the necks of zebras to
monitor their moves and their behavior. Since the network
is designed to operate in an infrastructure-free environment, peer-to-peer swaps of information are used to
produce redundant databases so that researchers only
have to encounter a few zebras in order to collect the
data. Sensor networks can also be used to monitor and
study natural phenomena which intrinsically discourage
human presence, such as hurricanes and forest fires.
Joint efforts between Harvard University, the University
of New Hampshire, and the University of North Carolina
have recently led to the deployment of a wireless sensor
network to monitor eruptions at Volcán Tungurahua, an
active volcano in central Ecuador. A network of Berkeley
motes monitored infrasonic signals during eruptions, and
data were transmitted over a 9 km wireless link to a base
station at the volcano observatory [B10].
Intel’s Wireless Vineyard [B11] is an example of using
ubiquitous computing for agricultural monitoring. In this
application, the network is expected not only to collect
and interpret data, but also to use such data to make decisions aimed at detecting the presence of parasites and
enabling the use of the appropriate kind of insecticide.
Data collection relies on data mules, small devices carried
by people (or dogs) that communicate with the nodes
and collect data. In this project, the attention is shifted
from reliable information collection to active decisionmaking based on...
tracking img