The document outlines a problem statement for developing an Automated Image Analysis Pipeline as part of NOAA Fisheries' Optics Strategic Initiative (OSI). The OSI aims to improve the identification and classification of marine taxa through advanced technology, addressing challenges posed by traditional manual methods. Key goals include the implementation of machine learning-assisted image processing and enhancing hybrid cloud capabilities for scalable solutions across various marine surveys.
Identified issues hindering automation include insufficient expertise, lack of labeled imagery, and poor software interfaces. Desired functionalities across modalities involve end-to-end automated detection, improved user interfaces, batch processing capabilities, and the ability to derive behavioral and size estimates from imagery.
The sections address state-of-the-tech statuses in different ecological areas: fish, aerial/mammals, benthic, and plankton, emphasizing the need for tailored solutions that accommodate diverse imaging conditions and user expertise levels. The overall aim seeks to streamline image analysis processes, reduce manual labor, and enhance data accessibility, contributing to improved marine resource management and biodiversity conservation efforts. This initiative exemplifies the federal government's commitment to integrating technology into environmental monitoring and research efforts.
The National Oceanic and Atmospheric Administration (NOAA) Fisheries is issuing a Request for Information (RFI) to gather market insights for automated image analysis software as part of the Optic Strategies Initiative. This RFI is aimed at industry partners to enhance image collection, processing, and storage for aquatic surveys, including fish, plankton, and benthic studies. NOAA seeks to develop end-to-end automated optical sampling technologies that aim to replace current survey methods while improving accessibility and functionality.
Vendors are invited to propose solutions for one or more of the four focal areas and are encouraged to address machine learning and hybrid cloud processing capabilities. NOAA plans to allocate funding between $250,000 and $500,000 for projects aimed at optimizing data pipelines, with a specific interest in responses from certified small businesses.
Interested parties must submit their responses by October 29th, and individual vendor demonstrations will be scheduled based on RFI responses on November 5-6. This RFI serves as a market research tool and does not guarantee future contract awards. Proposals must include organizational details, experience, software capabilities, timelines, and a Rough Order of Magnitude for development.