AI models can enhance natural disaster management by increasing visibility into various disaster types and providing recommendations for improving modeling quality.

Can we detect trends in natural disaster management with artificial intelligence? A review of modeling practices

AI can enhance natural disaster management by utilizing diverse data types, improving forecasting, detection, and humanitarian assistance.

Artificial Intelligence for Natural Disaster Management

AI techniques can enhance disaster management, particularly in response, but more research is needed to address challenges in mitigation, preparedness, response, and recovery.

Applications of artificial intelligence for disaster management

AI applications in disaster management enhance planning, analysis, situational awareness, and recovery operations, leading to faster, more concise, and equipped responses.

Toward an Integrated Disaster Management Approach: How Artificial Intelligence Can Boost Disaster Management

AI, machine learning, and deep learning techniques effectively analyze and predict disasters using social media, satellite, sensor data, and historical data for classification and prediction.

The Use of Artificial Intelligence in Disaster Management - A Systematic Literature Review

This paper reviews current emergency management prediction methods, highlighting challenges and future directions for improved disaster management.

A systematic review of prediction methods for emergency management

AI integration in disaster management and predictive modeling enhances disaster response by analyzing large data sets, aiding in disaster prevention and enhancing decision-making.

The Use of AI In Disaster Management and Predictive Modeling

Artificial intelligence in disaster management enhances speed, precision, and readiness, improving planning, analysis, and recovery efforts.

Present and Future of Artificial Intelligence in Disaster Management

AI techniques can enhance disaster management strategies, particularly in preparedness and response, with a focus on mitigation and recovery.

An Artificial Intelligence (AI) Approach to Controlling Disaster Scenarios

Machine learning techniques can enhance disaster management by monitoring, analyzing, and forecasting hydro-meteorological variables.

Intelligent Data Analytics for Decision-Support Systems in Hazard Mitigation

AI applications, such as geographical analysis and risk mapping, can enhance disaster management by providing faster solutions and enabling quick and effective decisions in emergency situations.

Role of Artificial Intelligence (AI) in Combined Disaster Management

The proposed intelligent disaster management system (IDSS) uses big data and AI algorithms to improve decision-making in smart city disaster management, focusing on wildfires and cold/heat waves.

Conceptual Framework of an Intelligent Decision Support System for Smart City Disaster Management

The Convolutional Neural Network (CNN) performs best in flood forecasting and the Adaptive Neuro-Fuzzy Inference System (WANFIS) for meteorological drought forecasting, regardless of the climate of the region studied.

Evaluation of artificial intelligence models for flood and drought forecasting in arid and tropical regions

Artificial intelligence in disaster risk management faces challenges such as data quality, compatibility, ethical implications, and data privacy and security, requiring ongoing research and development for fair and equitable use.

CHALLENGES OF ARTIFICIAL INTELLIGENCE APPLICATION FOR DISASTER RISK MANAGEMENT

Big data, machine learning, and deep learning can effectively reduce the risks of natural disasters by visualizing, analyzing, and predicting events.

Natural Disaster Application on Big Data and Machine Learning: A Review

Random forest regression model accurately predicts natural disasters, aiding early warning and saving lives.

Cloud Based Application for Prediction of Natural Disasters

AI tools in geospatial analysis can enhance disaster management by identifying risk areas and future needs, improving decision-making and response times.

ARTIFICIAL INTELLIGENCE AND GEOSPATIAL ANALYSIS IN DISASTER
MANAGEMENT

Artificial Intelligence techniques can effectively combine textual and imagery content from social media during disaster events, improving situational awareness and aiding humanitarian organizations in relief efforts.

Descriptive and visual summaries of disaster events using artificial intelligence techniques: case studies of Hurricanes Harvey, Irma, and Maria

AI, specifically Random Forest technique, can improve flood resilience and preparedness by accurately classifying different flood types, leading to better decision-making for prevention and preparedness measures.

Use of Artificial Intelligence to Improve Resilience and Preparedness Against Adverse Flood Events

Artificial intelligence can effectively classify social media messages into three categories for natural disaster management, with the best accuracy in earthquakes, forest fires, and floods.

Using Social Media Data to Monitor Natural Disaster: A Multi Dimension Convolutional Neural Network Approach with Word Embedding

The role of artificial intelligence in predicting and managing natural disasters.

These studies suggest that artificial intelligence enhances natural disaster management by improving prediction, planning, response, and recovery through the analysis of diverse data types and large datasets.