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Smart headphones to save pedestrians from getting run over by vehicles

A group of scientists are developing special earphones that alert their users of approaching vehicles.

Walking the streets while wearing headphones can put people at a massive risk of getting run over by vehicles. In an effort to avert any such freak accidents in the future, a group of scientists is developing special earphones that alert their users of approaching vehicles that can potentially prove to be a threat. The number of pedestrian deaths caused due to careless headphone use has dramatically skyrocketed in America, with the highest recorded fatalities occurring in 2018. The group of researchers from the Data Science Institute at Columbia University who are behind this pioneering piece of equipment are currently carrying out prototype testing on the busy streets of New York. According to an article on the Columbia University website, "The headphones have miniature microphones and intelligent signal processing that detects sounds of approaching vehicles. If a hazard appears near, the system sends an audio alert to the pedestrian's headphones." The headphones are fitted with small microphones that use intelligent signal processing to detect the sounds of vehicles that are dangerously close. The headphones then put out a sound alert to caution its user. Fred Jiang, an associate professor of mechanical engineering at Columbia University said, "We are exploring a new area in developing an inexpensive and low-power technology that creates an audio-alert mechanism for pedestrians." The project has till now received 1.2 million dollars in funding and its creators have published three research papers in the IEEE Internet of Things Journal. The team has also won many awards and accolades for their first of a kind invention. The researchers have used the latest data science techniques for developing advanced signal processing mechanisms, and additionally, these headphones would utilize machine learning models installed on the user's smartphones to identify hundreds of acoustic cues of nearby vehicles.

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