Researchers have applied machine-learning techniques to achieve fast, accurate estimates of local geomagnetic fields using data taken at multiple observation points, potentially allowing detection of changes caused by earthquakes and tsunamis. A deep neural network (DNN) model was developed and trained using existing data; the result is a fast, efficient method for estimating magnetic fields for unprecedentedly early detection of natural disasters. This is vital for developing effective warning systems that might help reduce casualties and widespread damage.