The utilization of a stream analytical processing approach is presented in the context of real-time analysis of acoustic data streams from hydrophones for cetacean identification and classification. We discuss the development and interim results of an integrated platform for processing underwater acoustic data in real time that also utilizes supplemental data types related to the physical environment. This approach provides advanced capabilities such as real-time dynamic filtering to support the intelligent processing of multiple high volume continuous data streams in parallel. The stream processing platform is being employed for the development of a continuous broad spectrum monitoring station to establish background levels for underwater noise for environmental impact assessment and continued operational monitoring for underwater acoustic noise produced by wave and tidal ocean energy devices. The use of hydrophone and particle velocity detectors in conjunction with other real-time sensors and data sources with dynamic feedback and control mechanisms is presented. The monitoring technologies are discussed along with the establishment of a consistent measurement methodology for varied deployment regimes dependent on water depth, bottom conditions, and variable sea states. We also review the incorporation of these technologies in the Marine Institute of Ireland's multipurpose research and development SmartBay Galway system to provide a flexible and agile monitoring and management platform which is being extended to include additional environmental variables specific to the ocean energy domain. The platform is being developed for the Galway Bay Quarter Scale Wave Energy Test Site and the full-scale, grid-connected Atlantic Marine Energy Test Site now under development by the Sustainable Energy Authority of Ireland. © 2011 IEEE.