Disaster management has long been a crucial field that calls for careful preparation, prompt action, and efficient teamwork. The stakes are extremely high in the face of natural disasters like hurricanes, earthquakes, and wildfires. By facilitating quicker reaction times for governmental organizations, non-governmental organizations, and other authorities, artificial intelligence (AI) techniques such as machine learning, deep learning, and natural language processing provide answers.
72 studies on the use of AI in disaster management stages, such as modeling, detection, prediction, and post-disaster situation handling, are examined in this study. AI-based technologies facilitate the decision-making processes for the issuing of building permits and grants, enhance the delivery of early warnings, expedite risk communication, maximize relief logistics, and support evacuation plans.
Artificial Intelligence (AI) has revolutionized catastrophe safety, natural disaster response, and disaster management by reducing damage and saving lives. This article examines how artificial intelligence (AI) is transforming disaster management, emphasizing its uses, advantages, difficulties, and prospects.
Comprehending Disaster Management
A systematic strategy for preventing, preparing for, responding to, and recovering from man-made and natural disasters is known as disaster management. It includes initiatives to reduce financial loss and human suffering while guaranteeing a speedy recovery.
AI’s Applications in Disaster Management
AI’s contribution to disaster management is not only beneficial but also essential given the increasing unpredictability of our climate and the frequency of natural disasters. Significant improvements have been brought about by the use of AI in disaster response, mitigation, and forecasting. We will examine AI’s application in crisis management in more detail in the sections that follow, highlighting specific examples that highlight the technology’s promise.
1. Predicting Disasters
Seismology, which uses AI to forecast earthquakes—one of the most destructive natural disasters in human history—is one of the most interesting uses of AI in disaster management.
For instance, Stanford researchers created the Stanford Earthquake Detecting System (STEDS), an AI model for earthquake prediction that can detect small quakes that are frequently missed by traditional techniques. The achievement of STEDS highlights AI’s potential for disaster prediction and establishes a framework for its application in foretelling different types of natural disasters.
2. Preventing Disasters
AI has become a vital ally in disaster avoidance, serving as a watchful protector that constantly monitors a variety of factors, from minute changes in weather patterns to modifications in geological formations, to predict possible calamities. Google’s flood forecasting system, which is now in use in Bangladesh and India, is a noteworthy illustration of how AI is being used to avoid disasters.
3. Response to Disasters
Rapid and efficient responses are essential in the face of increasing natural calamities. In this way, AI is transforming it from a traditionally reactive process to a proactive, data-driven approach thanks to its capacity to analyze large amounts of data quickly and accurately. This is best demonstrated by IBM’s PAIRS Geoscope, a distinctive cloud-based geospatial analytics tool. It evaluates disaster damage and analyzes satellite photos using AI.
AI’s Function in the Management of Natural Disasters
Effective management of nearly all natural and man-made disasters requires common traits, regardless of the type of disaster. The following is a discussion of a few AI-based applications used to forecast and identify natural disasters:
1. Earthquake:
A number of research show notable progress in examining the use of AI and machine learning in earthquake damage assessment and prediction. AI models can be trained using the available seismic data to forecast earthquakes and aftershock patterns. AI systems can also be used to analyze building damage caused by earthquakes. This can be used to produce warning messages before an earthquake occurs, minimizing the harm from a structure collapse.
2. Landslide:
Considerable progress is being made in the more reliable and accurate forecasting of landslides through the use of machine learning algorithms. Artificial intelligence (AI) systems can forecast landslides by using geological and satellite data.
3. Volcanic Eruptions:
By utilizing geological and seismic data, AI-driven systems can forecast volcanic eruptions. AI is being used by scientists to identify and categorize the tiny ash particles from volcanoes. The type of volcano can be determined by the shape of the ash particles.
Thus, automated systems based on artificial intelligence (AI) can be used to forecast volcanic eruptions [6] and assist disaster managers in sending out relevant alerts and evacuating residents from locations that are at risk.
Artificial Intelligence in Human-Made Disaster Management
The following is a discussion of some AI-based strategies to prevent or lessen the negative effects of man-made disasters:
1. Crowd Disaster:
By evaluating crowd dynamics in real-time, anticipating possible hazards, and assisting emergency management through crowd monitoring, behavior analysis, and simulation models, artificial intelligence (AI) can greatly improve crowd disaster prevention and response. This will increase safety and lessen the effects of disasters.
The growing frequency of crowd tragedies has made crowd safety and management an essential responsibility for disaster managers. It takes an automated crowd catastrophe avoidance system to analyze the intricate nature of crowd motion.
2. CBRN:
A catastrophic incident involving chemical, biological, radiological, and nuclear materials is referred to as a CBRN disaster. Through the use of decision support systems, pattern recognition, and predictive analytics, AI has the potential to enhance CBRN defense measures.
3. Industrial Risk:
Using AI to manage industrial dangers is a revolutionary way to improve operational effectiveness, environmental preservation, and workplace safety.
Chemical spills, equipment failures, explosive dangers, and occupational health concerns are examples of industrial hazards that provide serious problems for industries like manufacturing, energy, and chemicals. By utilizing real-time monitoring, predictive analytics, and sophisticated decision-support systems, artificial intelligence (AI) greatly improves the identification, control, and mitigation of industrial hazards.
AI’s Benefits for Disaster Management
AI has many benefits for disaster management, starting with improving early warning systems to aid in recovery after a disaster. Let’s examine some of the advantages of AI in disaster management in more detail:
1. AI for Precise Weather Prediction
Traditional weather forecasting models, which rely on intricate mathematical formulas to replicate atmospheric phenomena, can be improved by artificial intelligence. It accomplishes this through the use of machine learning techniques and the addition of additional data sources. These methods can spot trends that human forecasters would overlook.
2. AI in Response and Recovery Activities for Disasters
The newest technology in disaster management, AI-powered drones and robots, can be used to evaluate damage, look for survivors, and transport aid to impacted areas after a natural catastrophe. By evaluating information on the extent of the damage, the requirements of impacted communities, and the available resources, artificial intelligence (AI) can also help in disaster response efforts by optimizing resource allocation.
3. AI in Reconstruction and Recovery After Disasters
By examining data on the effects of previous disasters, AI algorithms can determine the best plans for repairing infrastructure, reestablishing ecosystems, and aiding impacted communities. This reduces the long-term effects of natural disasters by guaranteeing that recovery efforts are focused and effective.
AI’s Role in Disaster Management in the Future
AI’s role in responding to natural disasters has a promising future thanks to several upcoming developments:
Smart Cities with AI Integration: Cities that have AI and IoT sensors installed will be better able to recognize and react to emergencies.
Better AI Algorithms: Developments in AI will improve the precision of resource allocation models and disaster forecasts.
Global Cooperation: Stronger disaster management systems will result from international collaboration in AI research and data exchange.
FAQ’S
1. Can AI enhance efforts to respond to disasters?
Artificial intelligence enhances disaster response activities by enabling real-time data analysis, resource allocation, and communication. AI-powered tools prioritize rescue activities by employing drones and satellite imagery to analyze impacted areas, guaranteeing quicker and more efficient responses.
2. What role does AI play in lowering the danger of disaster?
Artificial intelligence lowers the chance of disasters by forecasting high-risk areas, simulating disaster scenarios, and offering practical advice for preventive actions. To reduce possible effects, AI-powered technologies assist with community awareness campaigns, emergency exercises, and urban planning.
3. How might artificial intelligence help forecast disasters?
By examining vast datasets from sensors, satellite pictures, and historical patterns, artificial intelligence (AI) helps anticipate future calamities. Early warnings for earthquakes, hurricanes, and floods are made possible by machine learning algorithms that identify abnormalities in weather data, seismic activity, and environmental changes.
