Elsevier Nanotechnology-Based Smart Remote Sensing Networks for Disaster Prevention (Micro and Nano Technologies)

Nanotechnology-Based Smart Remote Sensing Networks for Disaster Prevention outlines how a bottom-up/top-down hybrid approach could be feasible for the detection of disaster risks at early stages using cheap sensors, cheap constellations of LEO satellites, and smart wireless networks using 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 object and sensor. In this book, users will find comprehensive discussions on how nanotechnology and space technology can be used in smart-remote sensing networks to prevent disaster risks. This will be an important reference source for materials scientists, engineers and environmental scientists who are looking to understand how nanotechnology-based solutions can help mitigate natural disasters. Review A detailed examination of how nanotechnology can be combined with space technology to provide more efficient disaster prevention and mitigation solutions From the Back Cover <p>Most current technologies applied to disaster monitoring, analysis, and management are based on a top-down approach, using satellites, drones, unmanned aerial vehicles, etc. However, this approach is usually too reactive for any effective response when disasters happen. Emerging solutions relating to the application of land-based sensors and their wireless networks for disaster prevention, especially in combination with traditional top-down approach. This book outlines how a bottom-up/top-down hybrid approach could be feasible for the detection of disaster risks at the early stages, using cheap sensors, cheap constellations of LEO satellites, and smart wireless networks using artificial intelligence (AI) tools. </p> <p>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, smaller interaction distances between object and sensor. Besides this, with the support of AI tools, such as fuzzy logic, genetic algorithms, neural networks, ambient intelligence, etc., sensor systems are becoming smarter when a large number of sensors is used. </p> <p>This book explores how nanotechnology and space technology can be used in smart-remote sensing networks to prevent disaster risks. It is an important reference source for materials scientists, engineers and environmental scientists who are looking to understand how nanotechnology-based solutions can help mitigate natural disasters. </p> About the Author 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 Principal Research Scientist at the Institute for Tropical Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam. His research focuses on advanced nanomaterials and applied nanotechnology. His research activities include smart coatings, conducting polymers, corrosion and protection of metals/concrete, antibacterial materials, and smart sensors/devices. He is Editor-In-Chief of Kenkyu Journal of Nanotechnology & Nanoscience and Founding Co-Editor-In-Chief of Current Nanotoxicity & Prevention. David Motaung is Professor in the Department of Physics, University of Limpopo, Sovenga, South Africa. His curr