Artificial intelligence (AI) has sped up the process of detecting flooded buildings immediately after a large-scale flood, allowing emergency personnel to direct their efforts efficiently. Now, a research group from Tohoku University has created a machine learning (ML) model that uses news media photos to identify flooded buildings accurately within 24 hours of the disaster. Their research was published in the journal Remote Sensing on April 5, 2021. "Our model demonstrates how the rapid reporting of news media can speed up and increase the accuracy of damage mapping activities, accelerating disaster relief and response decisions, said Shunichi Koshimura of Tohoku University's International Research Institute of Disaster Science and co-author of the study. ML and deep learning algorithms are tailored to classify objects through image analysis.