Nanotechnology-Based Smart Remote Sensing Networks for Disaster Prevention outlines how nanotechnology and space technology could be applied for the detection of disaster risks in early stages, using cheap sensors, cheap constellations of low Earth orbit (LEO) satellites, and smart wireless networks with artificial intelligence (AI) tools.
Nanomaterial-based sensors (nanosensors) can offer several advantages over their micro-counterparts, such as lower power or self-powered consumption, high sensitivity, lower concentration of analytes, and smaller interaction distances between the object and the sensor. Besides this, with the support of AI tools, such as fuzzy logic, genetic algorithms, neural networks, and ambient intelligence, sensor systems are becoming smarter when a large number of sensors are used.
This book is an important reference source for materials scientists, engineers, and environmental scientists who are seeking to understand how nanotechnology-based solutions can help mitigate natural disasters.
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Adil Denizli is Professor at Hacettepe University, Department of Chemistry, Ankara, Turkey. His main research fields are molecular imprinting technologies, purification of biomolecules by chromatographic methods, detection of molecules by sensors, production of polymers with different surface and bulk properties, shape and geometries, and application of these polymers in different applications.
Marcelo Alencar is Chair Professor at the Department of Electrical Engineering, Federal University of Campina Grande, Brazil. His research is in communication and information systems.
Tuan Anh Nguyen is a Senior Principal Research Scientist at the Institute for Tropical Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam. He received a BS in physics from Hanoi University in 1992, a BS in economics from Hanoi National Economics University in 1997, and a PhD in chemistry from the Paris Diderot University, France, in 2003. He was a Visiting Scientist at Seoul National University, South Korea, in 2004, and the University of Wollongong, Australia, in 2005. He then worked as a Postdoctoral Research Associate and Research Scientist at Montana State University, United States in 2006-09. In 2012 he was appointed as the Head of the Microanalysis Department at the Institute for Tropical Technology. His research areas of interest include smart sensors, smart networks, smart hospitals, smart cities, complexiverse, and digital twins. He has edited more than 74 books for Elsevier, 12 books for CRC Press, 1 book for Springer, 1 book for RSC, and 2 books for IGI Global. He is the Editor-in-Chief of Kenkyu Journal of Nanotechnology & Nanoscience.
David Motaung is Professor in the Department of Physics, University of Limpopo, Sovenga, South Africa. His current research interests include design, synthesis and characterization of semiconductor metal oxides, nanostructured materials and their application in gas sensing devices for air quality monitoring.
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Nanotechnology-Based Smart Remote Sensing Networks for Disaster Prevention outlines how nanotechnology and space technology could be applied for the detection of disaster risks in early stages, using cheap sensors, cheap constellations of low Earth orbit (LEO) satellites, and smart wireless networks with artificial intelligence (AI) tools. Nanomaterial-based sensors (nanosensors) can offer several advantages over their micro-counterparts, such as lower power or self-powered consumption, high sensitivity, lower concentration of analytes, and smaller interaction distances between the object and the sensor. Besides this, with the support of AI tools, such as fuzzy logic, genetic algorithms, neural networks, and ambient intelligence, sensor systems are becoming smarter when a large number of sensors are used. This book is an important reference source for materials scientists, engineers, and environmental scientists who are seeking to understand how nanotechnology-based solutions can help mitigate natural disasters. N° de réf. du vendeur 9780323911665
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