SBIR/STTR Research Award

SBIR Phase I:Remote IoT Monitoring Network for Early Warning and Measurement of Structural Movements

Award identifier c736e5e34cea7c316f1e1d8d5f9f724319eee4d846569b20f0e3df7765ec589cAwarding agency National Science Foundation

Award amount

$256,000

Program and phase

SBIR · Phase I

Award year

2022

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
2KR SYSTEMS, LLC
Proposal award date
2022-03-01
Contract end date
2023-02-28
UEI
Q7U5MNY7P8M5
Solicitation number
NSF 21-562
Topic code
I

Research abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to reduce injury, property damage, operating costs, and liability in the built and natural environments.Excessive snow, rain, wind and seismic activity create high structural loads that can lead to the collapse of buildings, bridges, and other infrastructure.These loads can also destabilize geographical features such as water impoundments and hillsides.Increasingly extreme climate impacts and aging infrastructure make these situations more common and unpredictable.Weather events affect 5.9 million commercial buildings and 137,000 schools in the US.Of the 600,000 highway bridges in the US, 45,000 are structurally deficient. Landslides result in $3.5 billion in repair costs due to physical damage and result in 25 to 50 deaths annually.Since small structural movements often precede damage and even catastrophic failure, the ability to detect and monitor these motions at key locations and deliver warnings to any user with a cell phone or computer is of great societal benefit.This project will lead to the development of a low cost, rapidly installed, and intuitive wireless system to measure and record movements within broad categories of infrastructure and geographic features.Early warning of structural movements helps mitigate risk, prevent unnecessary damage, initiate evacuations, and keep occupants safe.This Small Business Innovation Research (SBIR) Phase I team will construct a series of sensors that measure commercial rooftop movement like that seen from high snow and wind loading.Existing disaster forecasting systems are expensive, operationally complex, and/or provide limited data.The sensors in this project will use precision radio receivers to create 3 axis centimeter-accurate movement data.Sensors report movements to an application server where an algorithm will be created to analyze and display geo-located data.When necessary, alerts are sent to users via Short Message System (SMS, i.e., text) and email, indicating the location and severity of the problem.A key metric to success will be the ability for the sensors to operate accurately on structures such as metal-decked rooftops which can create challenges for radio frequency devices.A compact design is necessary for commercial viability and to create a stable enclosure with low aerodynamic drag. Therefore, a novel hybrid energy supply will perform additional system functions and will be evaluated for output efficiency.To reduce battery demands, algorithms will be developed instructing units to remain in “power saving mode” during periods of low activity then switch into “high fidelity mode” when motion is detected or expected, such as during storms or geological events.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.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

2 SBIR/STTR records share this UEI (2022–2024). Reported award amounts total $1,256,000. Reported amounts are not federal obligations.

Phases: Phase II, Phase I

Agencies: National Science Foundation

Agency intelligence

National Science Foundation

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