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Patterns for wireless sensor networks

Sensors are shaping many activities in our society with an endless array of potential applications in military, civilian, and medical application. They support different real world applications ranging from common household appliances to complex systems. Technological advancement has enabled sensors to be used in medical applications, wherein they are deployed to monitor patients and assist disabled patients. Sensors have been invaluable in saving lives, be it a soldier's life in a remote battlefield or a civilian's life in a disaster area or natural calamities. In every application the sensors are deployed in a pre-defined manner to perform a specific function. Understanding the basic structure of a sensor node is essential as this would be helpful in using the sensors in devices and environments that have not been explored. In this research, patterns are used to present a more abstract view of the structure and architecture of sensor nodes and wireless sensor networks. This would help an application designer to choose from different types of sensor nodes and sensor network architectures for applications such as robotic landmine detection or remote patient monitoring systems. Moreover, it would also help the network designer to reuse, combine or modify the architectures to suit more complex needs. More importantly, they can be integrated with complete IT applications. One of the important applications of wireless sensor networks in the medical field is a remote patient monitoring system. In this work, patterns were developed to describe the architecture of patient monitoring system. / This pattern describes how to connect sensor nodes and other wireless devices with each other to form a network that aims to monitor the vital signs of a person and report it to a central system. This central system could be accessed by the patient's healthcare provider for treatment purposes. This system shows one of the most important applications of sensors and it application which needs to be integrated with medical records and the use of patterns makes this integration much simpler. / by Anupama Sahu. / Thesis (M.S.C.S.)--Florida Atlantic University, 2010. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2010. Mode of access: World Wide Web.

Identiferoai:union.ndltd.org:fau.edu/oai:fau.digital.flvc.org:fau_3602
ContributorsSahu, Anupama., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
PublisherFlorida Atlantic University
Source SetsFlorida Atlantic University
LanguageEnglish
Detected LanguageEnglish
TypeText, Electronic Thesis or Dissertation
Formatxi, 73 p. : ill. (some col.), electronic
Rightshttp://rightsstatements.org/vocab/InC/1.0/

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