Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/16622
Title: Applying an SOM neural network to increase the lifetime of battery-operated wireless sensor networks
Other Titles: Self-organizing maps
Authors: Cordina, Mario
Debono, Carl James
Keywords: Wireless sensor networks
Neural networks (Computer science)
Energy consumption
Wireless sensor nodes
Issue Date: 2010-04-01
Publisher: InTech
Citation: Cordina, M., & Debono, C. J. (2010). Applying an SOM neural network to increase the lifetime of battery-operated wireless sensor networks. In G. K. Matsopoulos (Eds.), Self-organizing maps (pp.411-430). Rijeka: InTech.
Abstract: Wireless sensor networks have garnered significant attention in recent years. According to (The Mobile Internet, 2004), more than half a billion nodes will be shipped for wireless sensor applications in 2010, for an end user market worth at least $7 billion. Wireless sensor networks are one of the first real-world examples of pervasive computing, the notion that small, smart, computing and cheap sensing devices will eventually permeate the environment (Bulusu & Jha, 2005). The combination of distributed sensing, low power processors and wireless communication enables such technology to be used in a wide array of applications such as habitat monitoring and environment monitoring, military solutions, such as battlefield surveillance, and commercial applications, such as monitoring material fatigue and managing inventory.
URI: https://www.um.edu.mt/library/oar//handle/123456789/16622
ISSN: 9789533070742
Appears in Collections:Scholarly Works - FacICTCCE

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