DeepER tool uses deep learning to better allocate emergency services

BEGIN ARTICLE PREVIEW: BINGHAMTON, NY — Emergencies, by their very nature, are hard to predict. When and where the next crime, fire or vehicle accident will happen is often a matter of random chance. What can be measured, however, is how long it takes for emergency services personnel to consider a particular incident to be resolved — for instance, suspects apprehended, flames extinguished or damaged cars removed from the street. New York City is among the large urban areas that maintain those kinds of statistics, and a team of researchers at Binghamton University, State University of New York has used deep-learning techniques to analyze the numbers and suggest improved public safety through re-allocation of resources. Arti Ramesh and Anand Seetharam — both assistant professors in the Department of Computer Science at the Thomas J. Watson College of Engineering and Applied Science — worked with PhD students Gissella Bejarano, MS &