NoiseSpotter: Real-time underwater acoustic characterization in support of marine renewable energy projects

Frank Spada, Kaus Raghukumar, Grace Chang and Craig Alexander Jones, Integral Consulting Inc., Santa Cruz, CA, United States
NoiseSpotter is a real-time, autonomous underwater environmental monitoring system that characterizes, classifies, and provides accurate location information for anthropogenic and natural sounds. It has been developed with the primary goal of supporting the evaluation of potential environmental effects of offshore energy projects. NoiseSpotter consists of a compact array of three acoustic vector sensors that measure acoustic pressure and 3D particle velocities associated with the propagation of an acoustic wave. Acoustic vector sensor data are stored onboard a custom low-noise, low-power data logger and also transmitted in near real-time, via Ethernet cable, to a surface buoy for creation of data digests and communication of digests to a dedicated cloud server. Data digests may include acoustic metrics for noises of interest such as peak sound levels, cumulative exposure levels, ambient noise intensities, and source location information. Determination of source location is enabled by the array of 3D vector sensors, which inherently provides information necessary to triangulate individual bearings. Using plane wave beam-forming, the acoustic signature of specific acoustic sources located in different regions of the ocean can be characterized. NoiseSpotter in-water field tests in Sequim Bay, Washington have resulted in successful near real-time transmissions of data digests at 1-min intervals with less than 5% data drop out. Location estimation errors of less than 5% of actual were accomplished with the NoiseSpotter separated from controlled, acoustic source transmissions at varying distances, demonstrating its potential for accurate acoustic characterization of offshore energy devices.