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SBIR Phase II: Building a Nature Monitoring Network for Birds

Project: Research

Abstract & Details

Description

Award ID: 2135664

The broader impact of this Small Business Innovation Research Phase II project is to further develop a product which allows consumers to listen and learn about the birds in their backyards. The product will improve the general publics scientific literacy and engagement by presenting information about birds in fun and non-threatening ways. Additionally, it will make environmental research more understandable, tangible, and valuable to more people and include women and individuals from underrepresented groups This project seeks to help casual birdwatchers know more about their own backyard ecosystems, improve their ability to identify birds by their songs, and recognize the diversity of life outside their windows. Customers will learn the importance of environmental stewardship by becoming important partners in bird-centered research and connecting with others who share their interests. Participation in bird count challenges saw large increases in 2020 and record-setting participation continued into 2021. The primary technical challenge will be to design and run birdsong detectors on low-cost edge hardware, while ignoring non-bird sounds such as dogs, insects, sirens, and machines. Edge algorithms and prototype hardware will be developed to provide the most accurate birdsong identifications at the lowest possible cost, which will result in wide commercialization. This represents a significant technical challenge because the products neural net is much larger than artificial intelligence chips can currently support. Producing a product priced for the target market will require the creation of a comprehensive labeled library of bird and environmental sounds, a well-trained neural net, optimized hardware, a comprehensive beta testing program, and an informative, easy to use website and smartphone app. 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.

NSF Program Director: Rajesh Mehta
StatusClosed
Effective start/end date03/01/2208/31/25

Funding

  • SBIR Phase II: $962,141.00

Active Fiscal Year

  • FY2024
  • FY2023
  • FY2022
  • FY2025

Start Fiscal Year

  • FY2022

TIP Programs

  • SBIR Phase II

Small Business

  • Yes

Key Technology Areas

  • Artificial Intelligence
  • (confidence score: 100%)

Technology Foci

  • Machine Learning Training Data
  • (confidence score: 97%)
  • Machine Learning (ML)
  • (confidence score: 98%)

Congressional District at Award

  • District n. 17 of Florida

Current Congressional District

  • District n. 14 of Florida

United States

  • Florida

Core Based Statistical Area (CBSA)

  • Tampa-St. Petersburg-Clearwater, FL

County

  • County: Pinellas, FL

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