Nanotechnology-Based Smart Remote Sensing Networks for Disaster Prevention

Front Cover
Nanotechnology-Based Smart Remote Sensing Networks for Disaster Prevention
Copyright
Dedication
Contents
Contributors
Preface
Section 1: Nanotechnology for disaster prevention
	Chapter 1: Application of nanotechnology in disaster prevention: An introduction
		1.1. Introduction
		1.2. Nanotechnology in sustainable agriculture and hunger prevention
		1.3. Role of nanotechnology in environmental pollution prevention
		1.4. Nanotechnology in harvesting renewable energy
		1.5. Nanotechnology in health sector
		1.6. Nanotechnology in protection of infrastructures
		1.7. Conclusion
		References
	Chapter 2: Nanomaterials for construction building products designed to withstand natural disasters
		2.1. Introduction
		2.2. Nanomaterials used in the construction
		2.3. Traditional materials for construction against disaster
		2.4. Sustainable usages of nano-based materials
			2.4.1. Nanoceramic coating
			2.4.2. Nano fibers
			2.4.3. Nanocomposites
			2.4.4. Nanoclays
			2.4.5. Titanium dioxide
			2.4.6. Carbon nanotubes
			2.4.7. Elctrochromic windows
			2.4.8. MMFX2 steel
			2.4.9. Nanowire
			2.4.10. Nanosilica
		2.5. Nanomaterials in advanced architecture
		2.6. Health aspects of nanomaterials when used in the construction building materials
		2.7. Environmental advantages and disadvantages and life-cycle assessment
		2.8. Risk assessment and analysis for nanomaterials used in the construction
		2.9. Regulations data in various countries
			2.9.1. United States
			2.9.2. Australia
			2.9.3. Europe
			2.9.4. China
		2.10. Conclusion
		2.11. Future scope
		References
	Chapter 3: Nano-sensors and nano-devices for biological disaster monitoring (virus/disease epidemics/animal plagu
		3.1. Introduction
		3.2. Nano-sensors and nano-devices
		3.3. The biological disaster monitoring applications
			3.3.1. Viruses
				3.3.1.1. Human immunodeficiency virus
				3.3.1.2. Human papilloma virus
				3.3.1.3. SARS virus
				3.3.1.4. Ebola virus
				3.3.1.5. Zika virus
				3.3.1.6. Hepatitis
				3.3.1.7. Influenza virus
		3.4. Conclusions
		References
	Chapter 4: Internet of Things-based disaster management system
		4.1. Introduction to disaster
		4.2. Classification
		4.3. Wireless sensor network and internet of things
			4.3.1. IoT
			4.3.2. Sensors used for disaster management
		4.4. Design challenges of using WSN/IoT in disaster management and possible solutions
			4.4.1. Deployment strategy
			4.4.2. IoT system
				4.4.2.1. Hardware
					Edge
					Network
					Core
					Date integration
					Data management
					Business innovation
				4.4.2.2. IoT-supported protocols for disaster management
		4.5. Results and discussion
			4.5.1. Landslide
			4.5.2. Earthquake disaster management
			4.5.3. Fire detection alarm using IoT
			4.5.4. Industrial disaster management
			4.5.5. Urban disaster management
		4.6. Scope for research in disaster management
			4.6.1. Cost
			4.6.2. Energy
			4.6.3. Interoperability
			4.6.4. Maintenance
			4.6.5. Robust and fault tolerance
			4.6.6. Minimize computation
			4.6.7. Artificial intelligence
			4.6.8. Data
		4.7. Conclusion
		References
	Chapter 5: Nanosensors for smartphone-enabled sensing devices
		5.1. Introduction
		5.2. Nanosensors
			5.2.1. Smart sensing system
		5.3. Nanosensors on smart platforms
			5.3.1. Optical nanosensors on smartphone sensing
			5.3.2. Mass-based nanosensors on smartphone sensing
			5.3.3. Electrochemical nanosensors on smartphone sensing
		5.4. Conclusion and future perspectives
		References
	Chapter 6: Smart and autonomous (self-powered) nanosensor networks
		6.1. Introduction
		6.2. Technology for self-powered nanosensors
		6.3. Applications of self-powered sensors for natural disasters
		6.4. Conclusion and remarks
		References
	Chapter 7: Nanosensors for smartphone sensing method
		7.1. Introduction
		7.2. Applications of nanosensors in smartphones
			7.2.1. Energy autonomy
			7.2.2. Physical durability
		7.3. Conclusion and remarks
		References
Section 2: Space technology for disaster prevention
	Chapter 8: Nanotechnology in the space industry
		8.1. Introduction of nanotechnology in space technology
		8.2. Nanomaterials in space industries
			8.2.1. Carbon nanotubes
			8.2.2. Nano Ti alloys
			8.2.3. Nano composites
		8.3. Nanostructures in aero-parts
			8.3.1. Nanosensors
			8.3.2. Thin solar sails
			8.3.3. Nanofuel in propulsion systems
			8.3.4. CNT-wheels
			8.3.5. Aero-vehicle frames
		8.4. Summary
		References
	Chapter 9: Unmanned aerial vehicles (UAVs) for disaster management
		9.1. Introduction
		9.2. UAV advancement for disaster management
			9.2.1. UAV services
		9.3. UAV-assisted communication network for disaster management
			9.3.1. UAV-assisted network architecture for disaster management
			9.3.2. UAV-assisted network design considerations
		9.4. Disaster types and phases
			9.4.1. Type A disasters: Massive terrestrial infrastructure damage
			9.4.2. Type B disasters: Moderate terrestrial infrastructure damage
			9.4.3. Type C disaster: Low terrestrial infrastructure damage
		9.5. Case studies
			9.5.1. Case study 1: UAV-assisted earthquake response and recovery
			9.5.2. Case study 2: Wildfire detection and monitoring
			9.5.3. Case study 3: UAV-assisted biological diseases management
		9.6. Conclusions
		References
	Chapter 10: The role of satellite remote sensing in natural disaster management
		10.1. Introduction
			10.1.1. Hydrological and geological hazards
			10.1.2. Geophysical hazards
			10.1.3. Meteorological hazards
			10.1.4. Climatological hazards
		10.2. Remote sensing data and techniques to access natural disasters
			10.2.1. Hydrological and geological hazards
				10.2.1.1. Floods
				10.2.1.2. Landslides
				10.2.1.3. Sea-level rise
			10.2.2. Geophysical hazards
				10.2.2.1. Earthquakes
				10.2.2.2. Volcanoes
				10.2.2.3. Tsunamis
			10.2.3. Meteorological hazards
				10.2.3.1. Storms
				10.2.3.2. Tropical cyclones
			10.2.4. Climatological hazards
				10.2.4.1. Droughts
				10.2.4.2. Fires
				10.2.4.3. Desertification
				10.2.4.4. Coastal erosion
		10.3. Conclusions
		References
	Chapter 11: The synergy of remote sensing and geographical information systems in the management of natural disasters
		11.1. Introduction
		11.2. The synergy of remote sensing and GIS in the management of natural disasters
			11.2.1. Hydrological and geological hazards
			11.2.2. Geophysical hazards
			11.2.3. Meteorological hazards
			11.2.4. Climatological hazards
		11.3. Conclusions
		References
	Chapter 12: Small satellites for disaster monitoring
		12.1. Introduction
		12.2. Remote sensing platforms
			12.2.1. Mission related aspects
				12.2.1.1. Orbits and temporal resolution
				12.2.1.2. Spatial resolution
				12.2.1.3. Necessary infrastructure
		12.3. A taxonomy of disasters
		12.4. Enabling technologies
			12.4.1. Instruments
			12.4.2. Constellations
			12.4.3. Ground segment
			12.4.4. Data collection systems
		12.5. Conclusions
		References
	Chapter 13: A comparative study of deep learning-based time-series forecasting techniques for fine-scale&spi
		13.1. Introduction
		13.2. Data
			13.2.1. IoT air temperature from GeoTab
			13.2.2. Air temperature measurements from weather underground
			13.2.3. High-resolution rapid refresh (HRRR)
		13.3. Methods
			13.3.1. Stacked LSTM
			13.3.2. ConvGRU
			13.3.3. Transformer
		13.4. Training and evaluation
			13.4.1. Training and testing data split
			13.4.2. Evaluation
			13.4.3. Baseline models
		13.5. Experiment result
			13.5.1. Overall performance comparison
			13.5.2. Sensitivity of GeoTab missing data ratio
			13.5.3. Impact of adding historical WU in training
			13.5.4. Performance on cases with rapid air temperature change
			13.5.5. Comparison with HRRR
		13.6. Conclusions
		References
	Chapter 14: Satellite and aerial remote sensing in disaster management: An introduction
		14.1. Introduction
		14.2. Data and methods
			14.2.1. Data
			14.2.2. Methods
				14.2.2.1. Preparation of spatial-factor layers
				14.2.2.2. Architecture of agent-based disaster risk dynamics model (AB-DRDM)
		14.3. Results
		14.4. Conclusions
		References
	Chapter 15: Emerging role of unmanned aerial vehicles (UAVs) for disaster management applications
		15.1. Introduction
		15.2. Disaster management cycle
		15.3. Unmanned aerial vehicles (UAVs)
		15.4. Overview of UAV sensors
		15.5. UAV regulations
		15.6. UAV hardware considerations
		15.7. Applications of UAVs in disaster management
			15.7.1. Land use classification
			15.7.2. Early warning systems
			15.7.3. Emergency communication networks
			15.7.4. Logistics
			15.7.5. Baseline data collection
			15.7.6. Disaster surveying
			15.7.7. Search and rescue
			15.7.8. Structural health monitoring
			15.7.9. Reconstruction monitoring
		15.8. Future applications and challenges
		References
	Chapter 16: Smart remote sensing network for early warning of disaster risks
		16.1. Introduction
		16.2. Remote sensing network architecture
			16.2.1. Wireless sensor networks
			16.2.2. Cloud integration
		16.3. Utilizing machine learning for smart sensing
			16.3.1. Smart sensing for agriculture applications
			16.3.2. Smart sensing for industry 4.0 applications
		16.4. UAV potential in early warning systems
			16.4.1. UAV for early nature disaster detection
			16.4.2. Wildfire detection
			16.4.3. Mountain hazards detection
			16.4.4. Flood detection
			16.4.5. General natural disaster
			16.4.6. Cooperative UAVs
		16.5. Conclusion
		References
Index
Back Cover