Project Grant 2325364

Award Date 9/15/23
Completion Date 8/31/24
Dollars Obligated $275K
Federal Grant Program
47.084
Assistance Type
Project Grant
Place of Performance
Flagstaff, AZ, USA
Similar Awards
This $255,993 Project Grant from the National Science Foundation will fund Wildlife Imaging Systems LLC to develop automated video processing software and services for wildlife conservation. Through its Small Business Innovation Research program, NSF aims to foster innovation and support small businesses engaged in scientific and engineering R&D. Wildlife Imaging will use the grant to create a web-based software-as-a-service platform that can detect, track, and classify wildlife in...
The National Science Foundation (NSF) awarded a $259,330 Project Grant under its Social, Behavioral, and Economic Sciences (CFDA 47.075) program to the University of Pittsburgh. This 1-year grant, awarded on May 1, 2024, will support research on "The Datafied Animal: Biologging, Machine Learning and Wildlife Conservation." The project will analyze the ethical, social, and practical implications of using new technologies like miniaturized animal tags, GPS-telemetry, and machine learning...
Birdhabitatbot LLC received a $240,060 Project Grant award from the National Science Foundation on August 15, 2021 to complete the project by February 28, 2023. The grant is part of the NSF Technology, Innovation, and Partnerships program (CFDA 47.084) to advance science and engineering research and innovation leading to breakthrough technologies as well as solutions to national challenges. Under this award, Birdhabitatbot LLC will develop a robotic system for the removal of invasive plant...
The National Science Foundation (NSF) awarded a $274,853 Technology, Innovation, and Partnerships (CFDA 47.084) grant to Pitch Aeronautics Inc., a veteran-owned small business, to develop techniques for localizing drones near power lines and control strategies for installing, removing, and maintaining dynamic line rating (DLR) sensors on power lines. The project aims to alleviate the backlog of renewable energy projects desiring to connect to the power grid by automating the installation and...
This federal Project Grant award of $200,000 from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop innovative biomimetic swarm-based remote sensing technology for environmental monitoring in hard-to-reach areas. The project, led by the University of New Mexico, focuses on creating a swarm of lightweight sensors inspired by the natural dispersal mechanism of dandelion seeds. These sensors will utilize wind currents...
This $200,000 project grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop innovative biomimetic swarm-based remote sensing technology for environmental monitoring in inaccessible areas. The researchers are designing a system inspired by dandelion seed dispersal that uses lightweight sensors with pappus-like structures to be deployed by unmanned aerial vehicles (UAVs) and harness wind...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $199,999 to develop a novel biomimetic swarm-based remote sensing system for environmental monitoring in hard-to-reach areas. The researchers at the New Mexico Institute of Mining and Technology (New Mexico Tech) aim to create a swarm of tiny, lightweight sensors inspired by the natural design of dandelion seeds that can be deployed by...
This $550,000 Project Grant award from the National Science Foundation (NSF) Technology, Innovation, and Partnerships (TIP) program (CFDA 47.084) supports the development and demonstration of a novel system to provide secure, unmanned, aerial vehicle guidance in limited connectivity environments. The project aims to develop secure communication protocols for robust and accurate vehicle position, navigation, and timing (PNT) when GPS or GNSS signals are compromised or unavailable. The key...
Treeswift Inc. was awarded a $1 million cooperative agreement from the National Science Foundation (NSF) under the NSF Technology, Innovation, and Partnership program (CFDA 47.084) to develop robotic technologies for forest inventory and mapping. The project aims to create algorithms, software, and hardware for autonomous multi-unmanned aerial vehicle systems that can coordinate in dense forests to precisely measure vast quantities of trees. This is intended to establish more accurate,...
This $174,660 National Science Foundation project grant supports research at the Rochester Institute of Technology to develop full automation capabilities for bird-sized unmanned aerial vehicles operating in unknown, cluttered indoor environments using only an RGB-D camera for visual perception. Funded under the NSF's Computer and Information Science and Engineering program (CFDA 47.070), which supports investigator-initiated research and education across computing and information sciences, this...

The National Science Foundation (NSF) awarded a $275,000 Small Business Innovation Research (SBIR) Phase I grant to Biotronic Innovations LLC under the NSF Technology, Innovation, and Partnerships program (CFDA 47.084). The project aims to develop a high-performance, drone-based wildlife telemetry technology that is economical and easy to use. The research plan focuses on creating a co-robotic system that employs an unmanned aerial vehicle (UAV) as an assistant wildlife tracker, fusing data from the UAV with the knowledge and insights of human trackers to improve the capability of these systems. The research will develop and refine machine learning algorithms for wildlife localization, with a goal of enabling researchers to better understand the complex effects of geography, climate, interspecies competition, invasive species, and land use policy on animals and their habitats. The 12-month project is expected to be completed by August 31, 2024.

Generated 6/18/24, 5:08 AM