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Chapter 46
Applications of Wireless
Sensor Networks
Corinna Schmitt
Technische Universität München, Germany
Georg Carle
Technische Universität München, Germany
INTRODUCTION
The goal of using a wireless sensor network is
to collect a variety of data, to store and analyze
the data and to provide the information to other
devices. Applications can be found in structural
health monitoring (e.g. the Golden Gate Bridge
Project (Kim2006)) or in habitat monitoring (e.g.
monitoring animal behavior). Other applications
for wireless sensor networks are traffic monitoring,
industrial automation, and battlefield surveillance
(Ilyas2004, Karl2005, Tavares2008).
Becauseofthecharacteristicoftheenvironment
smart technologies are very interesting. Different
typesofsensorsnodes,alsocalledmotes,havebeen
developed in order to meet the varying require-
ments. Berkeley Motes (Levis2003, Levis2004,
ABSTRACT
Today the researchers want to collect as much data as possible from different locations for monitoring
reasons. In this context large-scale wireless sensor networks are becoming an active topic of research
(Kahn1999). Because of the different locations and environments in which these sensor networks can be
used, specific requirements for the hardware apply. The hardware of the sensor nodes must be robust,
provide sufficient storage and communication capabilities, and get along with limited power resources.
Sensor nodes such as the Berkeley-Mote Family (Polastre2006, Schmitt2006) are capable of meeting
these requirements. These sensor nodes are small and light devices with radio communication and the
capability for collecting sensor data. In this chapter the authors review the key elements for sensor
networks and give an overview on possible applications in the field of monitoring.
DOI: 10.4018/978-1-61520-686-5.ch046
1077
Applications of Wireless Sensor Networks
Schmitt2006) have become highly popular be-
cause they allow quick development, are of small
size and support different sensors.
The remaining part of the chapter is structured
as follows. In section 1 a brief overview of the
history of sensor networks is given. In section
2 the theoretical background together with the
limitationofwirelesssensornetworksisdescribed
and the common Berkeley Motes are character-
ized. In the third section different approaches
corresponding to structural health and habitat
monitoring using wireless sensor networks are
presented. Finally future trends are mentioned
and a summary is given.
BACkGROUND
In this section the corresponding keywords in the
field of wireless sensor networks are mentioned
which will be characterized in more detail in
section two.
Today the industrial production is able to pro-
duce very small mobile devices (Warneke2001).
Two sorts can be distinguished: very small, spe-
cialized nodes, and larger nodes with commercial
off-the-shelf (COTS) components.
Anembeddedsystemisaspecializedcomputer
whichisusedfordevicecontrol(e.g.cars,mobiles,
hand-held-units, washing machine). Typically,
the end user has no control over it because the
device is hidden.
Embedded systems and highly embedded
systems can be differentiated. Highly embedded
systems would be particularly small, resulting in
highly limited resources. This implies the use of
sophisticated hardware, in combination with the
use of suitable, special operating systems. Data
can be collected by a variety of sensors. After
collection, this data has to be transmitted to other
nodes.Thus,wirelesssensorsystemshavetosup-
port highly developed communication.
Wireless sensor nodes have their own energy
supply provided by batteries or solar cells. Some
sensornodeshaveprocessorsthatallowtoprocess
data before passing it on. Different technolo-
gies for wireless transmission are used such as
infrared or radio frequency technology. A sensor
Figure 1. Information flow from WSN up to a user
Figure 2. Components of a sensor node
13 more pages are available in the full version of this document, which may
be purchased using the "Add to Cart" button on the product's webpage:
www.igi-global.com/chapter/applications-wireless-sensor-
networks/40840?camid=4v1
This title is available in InfoSci-Books, Business-Technology-Solution,
InfoSci-Software Technologies, Science, Engineering, and Information
Technology, InfoSci-Select, InfoSci-Computer Science and Information
Technology, InfoSci-Select, InfoSci-Select. Recommend this product to your
librarian:
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Applications Of Wireless Sensor Networks

  • 1. 1076 Copyright © 2010, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 46 Applications of Wireless Sensor Networks Corinna Schmitt Technische Universität München, Germany Georg Carle Technische Universität München, Germany INTRODUCTION The goal of using a wireless sensor network is to collect a variety of data, to store and analyze the data and to provide the information to other devices. Applications can be found in structural health monitoring (e.g. the Golden Gate Bridge Project (Kim2006)) or in habitat monitoring (e.g. monitoring animal behavior). Other applications for wireless sensor networks are traffic monitoring, industrial automation, and battlefield surveillance (Ilyas2004, Karl2005, Tavares2008). Becauseofthecharacteristicoftheenvironment smart technologies are very interesting. Different typesofsensorsnodes,alsocalledmotes,havebeen developed in order to meet the varying require- ments. Berkeley Motes (Levis2003, Levis2004, ABSTRACT Today the researchers want to collect as much data as possible from different locations for monitoring reasons. In this context large-scale wireless sensor networks are becoming an active topic of research (Kahn1999). Because of the different locations and environments in which these sensor networks can be used, specific requirements for the hardware apply. The hardware of the sensor nodes must be robust, provide sufficient storage and communication capabilities, and get along with limited power resources. Sensor nodes such as the Berkeley-Mote Family (Polastre2006, Schmitt2006) are capable of meeting these requirements. These sensor nodes are small and light devices with radio communication and the capability for collecting sensor data. In this chapter the authors review the key elements for sensor networks and give an overview on possible applications in the field of monitoring. DOI: 10.4018/978-1-61520-686-5.ch046
  • 2. 1077 Applications of Wireless Sensor Networks Schmitt2006) have become highly popular be- cause they allow quick development, are of small size and support different sensors. The remaining part of the chapter is structured as follows. In section 1 a brief overview of the history of sensor networks is given. In section 2 the theoretical background together with the limitationofwirelesssensornetworksisdescribed and the common Berkeley Motes are character- ized. In the third section different approaches corresponding to structural health and habitat monitoring using wireless sensor networks are presented. Finally future trends are mentioned and a summary is given. BACkGROUND In this section the corresponding keywords in the field of wireless sensor networks are mentioned which will be characterized in more detail in section two. Today the industrial production is able to pro- duce very small mobile devices (Warneke2001). Two sorts can be distinguished: very small, spe- cialized nodes, and larger nodes with commercial off-the-shelf (COTS) components. Anembeddedsystemisaspecializedcomputer whichisusedfordevicecontrol(e.g.cars,mobiles, hand-held-units, washing machine). Typically, the end user has no control over it because the device is hidden. Embedded systems and highly embedded systems can be differentiated. Highly embedded systems would be particularly small, resulting in highly limited resources. This implies the use of sophisticated hardware, in combination with the use of suitable, special operating systems. Data can be collected by a variety of sensors. After collection, this data has to be transmitted to other nodes.Thus,wirelesssensorsystemshavetosup- port highly developed communication. Wireless sensor nodes have their own energy supply provided by batteries or solar cells. Some sensornodeshaveprocessorsthatallowtoprocess data before passing it on. Different technolo- gies for wireless transmission are used such as infrared or radio frequency technology. A sensor Figure 1. Information flow from WSN up to a user Figure 2. Components of a sensor node
  • 3. 13 more pages are available in the full version of this document, which may be purchased using the "Add to Cart" button on the product's webpage: www.igi-global.com/chapter/applications-wireless-sensor- networks/40840?camid=4v1 This title is available in InfoSci-Books, Business-Technology-Solution, InfoSci-Software Technologies, Science, Engineering, and Information Technology, InfoSci-Select, InfoSci-Computer Science and Information Technology, InfoSci-Select, InfoSci-Select. Recommend this product to your librarian: www.igi-global.com/e-resources/library-recommendation/?id=1 Related Content Adjusting Thread Parallelism Dynamically to Accelerate Dynamic Programming with Irregular Workload Distribution on GPGPUs Chao-Chin Wu, Jenn-Yang Ke, Heshan Lin and Syun-Sheng Jhan (2014). International Journal of Grid and High Performance Computing (pp. 1-20). www.igi-global.com/article/adjusting-thread-parallelism-dynamically-to-accelerate-dynamic- programming-with-irregular-workload-distribution-on-gpgpus/114710?camid=4v1a A Highly Efficient Big Data Mining Algorithm Based on Stock Market Jinfei Yang, Jiajia Li and Qingzhen Xu (2018). International Journal of Grid and High Performance Computing (pp. 14-33). www.igi-global.com/article/a-highly-efficient-big-data-mining-algorithm-based-on-stock- market/202409?camid=4v1a The Development of a Parallel Ray Launching Algorithm for Wireless Network Planning Zhihua Lai, Nik Bessis, Guillaume De La Roche, Pierre Kuonen, Jie Zhang and Gordon J. Clapworthy (2011). International Journal of Distributed Systems and Technologies (pp. 1-19). www.igi-global.com/article/development-parallel-ray-launching-algorithm/53849?camid=4v1a QoS Oriented Enhancement based on the Analysis of Dynamic Job Scheduling in HPC Reshmi Raveendran and D. Shanthi Saravanan (2014). International Journal of Grid and High Performance Computing (pp. 28-45). www.igi-global.com/article/qos-oriented-enhancement-based-on-the-analysis-of-dynamic-job- scheduling-in-hpc/127373?camid=4v1a