AI is an essential tool for predicting and providing timely aid after a natural disaster occurs.
Fremont, CA: The poor communities around the world are always more affected by natural disasters than the wealthier communities. Natural disasters often destroy infrastructure, crops, government, and people's assets, resulting in acute loss of income. People in the low-income category are the worst affected as they do not have enough resources to recover from the loss.
Natural disasters usually widen the already prevalent income equality gaps. Middle and high-income individuals are often the ones who own businesses, and so they gain profits even in emergencies. Low-income individuals are vulnerable and sometimes left to lifelong poverty due to natural disasters.
According to UN reports, poor communities experience a more significant loss of life due to natural disasters. One reason for it can be that low-income individuals live in remote regions prone to natural disasters. They also tend to live in poorly constructed and weak houses, which any disaster can easily damage. For instance, when an earthquake hit Haiti in 2010, the largest number of deaths was in one of the poorly constructed and overpopulated housing facilities.
AI for better disaster management
AI embedded systems can be used for Analyzing, tracking, and predicting weather patterns. Technologies in the past have faced challenges in predicting natural disasters like earthquakes and floods. AI and ML technologies can identify potential disasters by analyzing similar patterns from previous disasters. Geophysicist Paul Johnson's team has already used AI to predict earthquakes in the labs. Using this technology makes it easier to predict earthquakes and timely evacuate residential spaces to avoid any loss of life or fatal injuries.
AI can predict safe spaces for people during a disaster through geospatial observations. This can help the rescuing teams and officials to locate and rescue individuals easily and provide the necessary aid on time. This technology can also predict which areas will be more affected due to the earthquake and which roads and buildings are more likely to be damaged. These predictions can help officials plan out their rescue missions prior to the actual disaster so that there is no chaos.
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