The US Geological Survey is offering a funding opportunity to a CESU partner for research in the “Development of a cell phone application for use by oil spill responders for semi-quantitative analysis of hydrocarbons following spills and disasters.” Research Objectives:
The USGS is currently
conducting science to characterize and optimize the fluorescent properties of oil extracts to detect oil using image analysis.
The general approach for the project is to:
(1) optimize the fluorescent properties of simple oil/solvent systems for characterizing environmental samples, (2) characterize oil concentration based on the image analysis using laboratory derived concentration relationships, (3) develop a machine learning model and related equations to predict oil concentration using fluorescence based optical properties.
The objectives of this funding opportunity is to provide science to enhance the design of a cell phone adaptor/system 1) addresses interference of oil spill sample image collection, 2) approaches to optimize power usage, and 3) evaluate the confounding factors/conditions to optimize control/restriction of the image collection.
In this task we will seek input from the oil spill practice community for input on the design and implementation of an image collection approach.
Three key questions should be answered:
What confounding factors or conditions might affect fluorescent image analysis of oil samples? In an image collection system how can electrical energy be optimized and or managed to ensure efficient and stable image collection? What approaches can be used to address confounding factors in a fluorescent image analysis system (1) while addressing issues identified in energy optimization identified in (2)? This study will address USGS Ecosystem Mission Area goals to (1) Identify, prioritize, and detect contaminants; (2) Reduce the impact of stressors on the environment, fish, and wildlife; (3) Discover the complex interactions and combined effects of exposure to contaminants; and (4) Prepare for and respond to environmental impacts and related health threats of anthropogenic disasters.
Products of the research should include prototype systems that integrate approaches addressing the optimized fluorescent image collection and providing multiple prototype systems (up to 50) that can be provided for integration with the machine learning application for field demonstration.
Research funded under this agreement will be conducted during FY 2021, initial data summaries and deliverables will be provided to USGS by September 30, 2021 and final reports will be provided to USGS by September 30, 202 3.