An IoT device that tracks coughing and crowd size in real time could become a useful tool for identifying the presence of flu-like symptoms among large groups of people, according to a team of researchers at UMass Amherst.
FluSense, as the researchers call it, is about the size of a dictionary. It contains a cheap microphone array, a thermal sensor, a Raspberry Pi and an Intel Movidius 2 neural computing engine. The idea is to use AI at the edge to classify audio samples and identify the number of people in a room at any given time.
Since the system can distinguish coughing from other types of non-speech audio, correlating coughing with the size of a given crowd could give a useful index of how many people are likely to be experiencing flu-like symptoms.
Thanks to Jon Gold (see source)