Assessing Damage Done By Natural Disasters Using ML

Abstract: This project uses ML to assess the damage done by natural disasters such as earthquakes, tornadoes, hurricanes, landslides, and other disasters that leave behind a trail of destruction. This model would be implemented using classification and multiclass logistic regression. The model would predict the level of damage done to a building or structure based on the proportion of key structural elements that are damaged. Based on this proportion, the building will be geotagged with a marker indicating the level of damage, helping relief workers to identify vulnerable areas and allocate resources optimally for faster response and recovery.