About this Research Topic
This Research Topic aims to explore the role of artificial intelligence (AI) in mitigating the risks of disasters, which can be natural or caused by human activities. In the context of climate change, data and machine learning technologies can be useful to face one of the greatest challenges facing humanity today. This Research Topic is a call for collaborative work in this domain.
The focus of this Research Topic is to examine how big data analytics and AI can play a role in preventing and reacting to these events in order to save more lives and reduce property damages. On the one hand, we invite papers that explore how artificial intelligence and data analytics can predict the occurrence of natural disasters like earthquakes, hurricanes, epidemics, flooding, and so forth. Contributions can explore the challenges related to emergency preparedness and response systems and how data and AI can contribute to predict and react in the event of a natural disaster.
Since, however, disasters can also result from human activities, such as satellite collision, glacial melting, viral consequences of changing cryosphere, nuclear plants incidents, cyberattacks of critical infrastructures among others we also invite contributions related to the challenges associated with disaster inflicted by humans. We are particularly interested here in how data analytics and AI can assist academics, industry leaders, and policymakers in improving the effectiveness of the predictions and reactions to disasters.
Possible topics include:
• Datasets quality
• Prediction quality
• Satellite Imagery and machine learning
• AI and Disaster prediction and modeling
• AI and Emergency Response Coordination
• Computer vision and disaster management
• Emergency escape route planning
• Damages mapping and modeling
• Flood simulations to predict and monitor flooding
• Prediction of Volcanic eruptions
• Neural network and Earthquake aftershock prediction
• Hurricane tracking
• Glacial melting and changing cryosphere
• AI and Dangerous anthropogenic interference with the climate system
• Emergency and Preparedness System
The focus of this Research Topic is to examine how big data analytics and AI can play a role in preventing and reacting to these events in order to save more lives and reduce property damages. On the one hand, we invite papers that explore how artificial intelligence and data analytics can predict the occurrence of natural disasters like earthquakes, hurricanes, epidemics, flooding, and so forth. Contributions can explore the challenges related to emergency preparedness and response systems and how data and AI can contribute to predict and react in the event of a natural disaster.
Since, however, disasters can also result from human activities, such as satellite collision, glacial melting, viral consequences of changing cryosphere, nuclear plants incidents, cyberattacks of critical infrastructures among others we also invite contributions related to the challenges associated with disaster inflicted by humans. We are particularly interested here in how data analytics and AI can assist academics, industry leaders, and policymakers in improving the effectiveness of the predictions and reactions to disasters.
Possible topics include:
• Datasets quality
• Prediction quality
• Satellite Imagery and machine learning
• AI and Disaster prediction and modeling
• AI and Emergency Response Coordination
• Computer vision and disaster management
• Emergency escape route planning
• Damages mapping and modeling
• Flood simulations to predict and monitor flooding
• Prediction of Volcanic eruptions
• Neural network and Earthquake aftershock prediction
• Hurricane tracking
• Glacial melting and changing cryosphere
• AI and Dangerous anthropogenic interference with the climate system
• Emergency and Preparedness System
Keywords: emergency preparedness, responses systems, artificial intelligence, big data analytics, global challenges
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
