SBIR Phase I: A Workplace Wearable Device For Social Distancing and Contact Tracing in Essential Businesses During COVID-19
- Funded by National Science Foundation (NSF)
- Total publications:0 publications
Grant number: 2030327
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Key facts
Disease
COVID-19Start & end year
20202021Known Financial Commitments (USD)
$255,993Funder
National Science Foundation (NSF)Principal Investigator
Haytham ElhawaryResearch Location
United States of AmericaLead Research Institution
One Million Metrics CorpResearch Priority Alignment
N/A
Research Category
Epidemiological studies
Research Subcategory
Disease transmission dynamics
Special Interest Tags
Innovation
Study Type
Not applicable
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Not Applicable
Vulnerable Population
Not applicable
Occupations of Interest
Not applicable
Abstract
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to protect the public during the COVID-19 pandemic through contact tracing. This project will develop wearable technology to provide proximity alerts when workers are in close contact, creating awareness around social distancing. It will also record every contact between workers to provide contact tracing should a worker test positive for COVID-19. These tools protect front-line workers from the spread of the virus, along with their families and communities. The technology will extend existing wearable technology to reduce overexertion injuries in the workplace.
This Small Business Innovation Research (SBIR) Phase I project will estimate distance between workers through a machine learning algorithm combining signal strength from Bluetooth technology with motion sensor data from accelerometers and gyroscopes to measure worker activity prior and at the end of each contact event. The project will develop distance detection algorithms and a set of performance requirements to optimize design of a rapid, accurate solution.
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.
This Small Business Innovation Research (SBIR) Phase I project will estimate distance between workers through a machine learning algorithm combining signal strength from Bluetooth technology with motion sensor data from accelerometers and gyroscopes to measure worker activity prior and at the end of each contact event. The project will develop distance detection algorithms and a set of performance requirements to optimize design of a rapid, accurate solution.
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.