Artificial intelligence in the fields of natural disaster prediction
Despite the differences in the importance of the presence of artificial intelligence and its differences, in our time and with the increase in climate change and natural disasters, artificial intelligence has become a savior in many cases as a powerful tool capable of making a big difference in the areas of natural disaster prediction and emergency management.
This technology depends on analyzing huge amounts of data and learning. From the previous patterns, providing accurate predictions that help in making quick and effective decisions. Although the use of artificial intelligence to predict earthquakes is still in the early stages of the development process, it achieves impressive results compared to traditional methods.
For example, remember the Dutch geologist Frank Hoogerbitz, who caused a stir with his predictions about earthquakes through... His tweets and his YouTube channel, confirming after the earthquakes occurred that he knew about them in advance.
Despite the scientific consensus that earthquakes cannot be predicted, some researchers have suggested that Hogrebitz may have used artificial intelligence to achieve this. To return to the origin of our topic, do you think that artificial intelligence actually contributed to this, and if it did, why did Frank Hogrebitz not disclose the matter in detail?
Science tricks:
The truth of the matter is that artificial intelligence does not actually perform the prediction process, but its vision differs from human eyes with its high accuracy and analytical ability to detect minute changes in the Earth’s surface through data analysis. Artificial intelligence-based models can also use features such as seismic activity, electromagnetic disturbances, groundwater changes, etc. In addition, to predict the time, location, and magnitude of an earthquake.
The matter regarding earthquakes does not depend only on data analysis, but rather the matter is in the development of artificial intelligence to a great extent, as one of the branches of artificial intelligence, which is the “machine learning” department, began to allow computers to learn from data, and from it machine learning algorithms were able to find hidden patterns between We have a lot of data for detecting earthquakes and we have a scientific application, including a team of geophysicists applying a machine learning algorithm to earthquakes in the Pacific Northwest, which gave a high success rate that exceeds laboratory rates.
Returning to the matter of prediction, we can understand that it is not a process of prediction, but rather from it we can understand the techniques that can be used from artificial intelligence, which are, respectively...
- Machine learning:
As we mentioned previously, machine learning is one of the most important artificial intelligence techniques used in predicting disasters. Machine learning relies on analyzing large amounts of historical data to identify patterns and relationships that can help predict future events, just as the geophysicists team applied.
- Neural networks:
Like the human nervous system, it is expansive and unique, but instead of nerves controlling the human brain, neural networks are used here to simulate the way the human brain works in processing data and making decisions. These networks are used to analyze complex data such as satellite images and forecast hurricanes and floods.
- Climate prediction models:
such as a unique data collector model, as these models rely on artificial intelligence to analyze climate data from various sources and provide forecasts about weather conditions and severe weather events.
Of course, the countries that are affected by these accidents and exposed to them frequently will not be late in using artificial intelligence in them, but rather have exploited it and of course it has produced significant successful results in rescue operations and disaster prediction, and among these countries...
- Earthquake prediction:
In Japan, the Japan Meteorological Agency uses artificial intelligence techniques to analyze seismic data and predict the occurrence of earthquakes. These systems depend on analyzing previous seismic patterns and using them to predict future seismic activity.
- Hurricane forecasting:
The United States is known to be exposed to many hurricanes each year, resulting in massive impacts and heavy losses, and the National Oceanic and Atmospheric Administration (NOAA) uses machine learning models to analyze satellite data and predict the path and intensity of hurricanes.
- Flood forecasting:
In Europe, the European Union's "Copernicus" program uses artificial intelligence to analyze precipitation data and weather patterns and predict floods.
We also have many countries that use artificial intelligence techniques for early avoidance of various cases, such as the Netherlands, and of course we will not forget the country, which relies heavily on various systems, especially the data analysis system, which pays great attention. We also have Canada on the list, but it does not rely only on prediction processes, but also on action, i.e. Here we mean rescue operations in places that are difficult to reach. The truth of the matter is that there are great challenges and future aspirations to develop the complete system and also complete the integration process with other technologies, as artificial intelligence can be integrated with other technologies such as the Internet of Things (IoT) and augmented reality (AR) to improve emergency response and provide... Comprehensive and integrated solutions, meaning we can be aware of the future development expected to make artificial intelligence successful by saving the greatest possible amount and enhancing the greatest amount of rescue and prediction cases.