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Titlebook: Autonomous Sensor Networks; Collective Sensing S Daniel Filippini Book 2013 Springer-Verlag Berlin Heidelberg 2013 Ambient assisted living.

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,Durch alle Städte: Hamiltonsche Graphen, electronics, digital components as well as computing can be embedded. These fabrics are identified as E-textiles (e.g., electronic textiles or smart textiles). Starting from the established concept, which asserts that future systems need to be more suitably interfaced with the humans with minimal d
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Graphen und algorithmische Graphenprobleme,ter, we describe the main frameworks for developing auto-LOC devices including the plug-in framework and the monolithic framework. The plug-in model aims at miniaturizing stand-alone plug-and-play components, which can then be assembled together with the microfabricated chip to develop an integrated
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https://doi.org/10.1007/978-3-663-10193-2cell phones, wrist watches) as well as high-performance components of consumer products (e.g., micromachined accelerometers, radiofrequency identification tags) present a prominent set of attractive capabilities for advanced sensors. For detection of chemical species in liquids and gases, we take ad
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https://doi.org/10.1007/978-3-7091-9144-6mation acquisition for applications ranging from environmental monitoring to in-vivo sensing. This chapter presents a range of on-going projects with an emphasis on environmental sensing; relevant literature pertaining to sensor networks is reviewed, validated sensing applications are described and
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Graphen- und Netzwerkoptimierungllimeter-scale miniature devices with sensing, processing, and wireless communication capabilities will change the way we live. These systems will provide the technology behind numerous collective sensing applications expected in the near future. Collective sensing is the collaboration between multi
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Daniel FilippiniWritten by international experts from multiple disciplines.Richly illustrated.A valuable source of information for researchers in both academic and industrial settings and advanced students.Includes s
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https://doi.org/10.1007/978-3-642-34648-4Ambient assisted living; Body area networks; Energy harvesting; Environmental sensors; Implanted sensors
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