Nanotechnology-Based Smart Remote Sensing Networks for Disaster Prevention

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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. 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. 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.