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SBIR Phase I: Tool to estimate object visibility to fish in complex aquatic environments.

Award Information
Agency: National Science Foundation
Branch: N/A
Contract: 1913419
Agency Tracking Number: 1913419
Amount: $224,977.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: MI
Solicitation Number: N/A
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-08-01
Award End Date (Contract End Date): 2020-04-30
Small Business Information
2112 Burlison Dr.
Urbana, IL 61801
United States
DUNS: 079834957
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Michael Mrozik
 (815) 570-9597
Business Contact
 Michael Mrozik
Phone: (815) 570-9597
Research Institution

The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to develop tools that will create vast amounts of water quality data for the nation's inland, fresh waters. The data allow for direct environmental monitoring and for validation of other remote sensing GIS techniques to measure inland water quality. Algorithms will also be developed to use the data to allow anglers to customize their selection of lures based on the time and location where they are fishing. The difficulty for the angler is anticipating which lures are most visible to the fish, because fish see differently than humans. This project develops software tools and water quality sensors that allow anglers to customize their fishing strategies for any type of water. The product will ultimately recommend lures that work well for a given location based on the properties of the water, the properties of the lures, and the visual capabilities of fish in that environment. The proposed project will measure the optical properties of (a) lakes and rivers. First-generation photometers would be constructed to estimate the sub-surface transmission and light-levels at three wavelengths and capture relevant water quality data. The project also proposes new methods to accommodate the selection of fluorescent pigments on lures. Algorithms will use the data to estimate the visual contrasts as perceived by certain species of fish and determine which lures have the highest probability of success for that species - bass in the first instance. The novelty of this approach is that it relies on estimating critical lighting parameters at three wavelength bands. Traditional methods rely on spectrometers that estimate spectra with thousands of data points and are not feasible for anglers. This project directly tests whether 3 well-spaced data points can accurately estimate lighting environments, visual signals, and their transmission in diverse water bodies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

* Information listed above is at the time of submission. *

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