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We review the history of underwater passive acoustic monitoring and predict the future trajectory. Over the past three decades, advances in digital data storage capacity and low power electronics have made it possible to collect autonomous long-term broadband passive acoustic monitoring data. Concomitant advances have taken place in data analysis and curation. Standardized spectra are an excellent first-step in analysis, calculated for all data using multiple frequency bands. These spectra allow in-situ instrument calibration based on an understanding of underwater ambient noise. Software for efficient manual scanning and signal discovery is used for verification and error estimation. Automatic detectors/classifiers are obtained from both supervised and unsupervised machine learning. Detections are aggregated into a database that allows the combination of multiple datasets and association with environmental or other data. Future work will increasing use of arrays of acoustics sensors, the integration of passive acoustics with other sensors, and machine learning that integrates these data streams to provide better understanding of anthropogenic, biological and physical processes in the ocean.
Hildebrand et al. (Fri,) studied this question.