Alexander Sutin and a team of acoustics experts at Stevens Institute of Technology in New Jersey are developing a system that tracks the traffic by listening to the noise it produces. On Wednesday, October 28, according to a news release issued today, they will present experimental data demonstrating the technology's ability to pick out and classify the sound of each boat in the throng at a meeting of the Acoustical Society of America (ASA) in San Antonio, TX.
As part of research conducted in the Center for Secure and Resilient Maritime Commerce (CSR), the national DHS Center of Excellence for Marine, Island and Port Security, Sutin and his team placed several underwater microphones ("hydrophones") in the Hudson River. These microphones recorded the din of engine and propeller noise produced by the ships above. They developed a computer algorithm that isolated each individual boat's sound and tracked its location based on how long the sound took to travel to each microphone.
The group was also able to classify each ship based on signature characteristics in its noise. Video cameras at the surface confirmed the accuracy of their technique.
"Classification parameters can be used like fingerprints to identify to identify what class a ship is," says Sutin.
The propellers of slow-moving boats like barges, for example, generate low-frequency modulation, while fast-moving speedboats produce high-frequency modulation. The team used special analysis techniques for extracting high-frequency modulation using low frequencies.
The team hopes to develop a database that keeps track of every individual ship's identity to assist various agencies, including the U.S. Coast Guard, with their missions.
Photo of Hudson River police patrol by Ed Yourdon. CC Attribution-Share Alike 2.0 Generic