Several cities in the United States have installed a gunshot-detecting system that uses networked audio sensors dispersed through city blocks and machine learning to automatically identify the audio signatures of gunshots and report their location to police with high degrees of accuracy. It’s algorithms can differentiate between gunshots and other similar noises, such as a car backfiring, triangulate the origin of a gunshot, determine if multiple firearms were involved, and identify the direction a shooter was traveling in.
A machine-learning model can analyze data to recommend inspection for buildings that pose the highest fire risks. Another algorithm uses AI to monitor data about firefighters’ environments to detect signs of danger and help them recover from disorientation to exit a building safely. It can monitor sensors in firefighting gear and warn firefighters, for example, if it is becoming dangerously hot or if dangerous gases are present, map the surrounding environment, and communicate with firefighters to guide them to safety if they need to evacuate.