2404015
Cooperative Agreement
Overview
Grant Description
SBIR Phase II: Prototyping Internet of Things (IoT) sensing platform for infrastructure monitoring.
The broader impact/commercial potential of this SBIR Phase II project is to deploy a novel concrete strength sensing technology to provide smart solutions to the construction industry.
This groundbreaking technology will transform the construction industry by enabling faster, data-driven decisions through real-time data of concrete strength monitoring.
Short-term, this technology will allow accelerated project timelines and eliminate costly quality control errors.
Long term, this technology will leverage the power of big data to enable data-driven decision making and optimization of concrete mix design, which will drastically reduce carbon footprint, eliminate wastes, and lead to more durable concrete infrastructures.
By leveraging AI and big data analysis of the vast amount of structural health data collected, the project paves the way for the development of AI-powered solutions for predictive maintenance and improved construction practices.
The proposed project will focus on developing the market-ready Internet-of-Things (IoT) concrete sensing system that addresses the challenge of using antiquated testing methods in the construction industry, often leading to schedule delays and cost overruns.
Built on the success of Phase I project, this program will develop a complete solution for scaling up productions.
A systematic hardware production and quality control procedure will be established, key parameters for a reproducible production line will be determined, and instrumentation errors will be minimized.
Concurrently, a scalable cloud backend will be developed, capable of serving tens of thousands of dataloggers while ensuring data security and low latency.
The machine learning algorithm will be further refined to provide fast and accurate strength inferences.
A full-scale production and stress testing of the sensor system in real-life conditions will also be conducted to evaluate the robustness and user experience.
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.
Subawards are not planned for this award.
The broader impact/commercial potential of this SBIR Phase II project is to deploy a novel concrete strength sensing technology to provide smart solutions to the construction industry.
This groundbreaking technology will transform the construction industry by enabling faster, data-driven decisions through real-time data of concrete strength monitoring.
Short-term, this technology will allow accelerated project timelines and eliminate costly quality control errors.
Long term, this technology will leverage the power of big data to enable data-driven decision making and optimization of concrete mix design, which will drastically reduce carbon footprint, eliminate wastes, and lead to more durable concrete infrastructures.
By leveraging AI and big data analysis of the vast amount of structural health data collected, the project paves the way for the development of AI-powered solutions for predictive maintenance and improved construction practices.
The proposed project will focus on developing the market-ready Internet-of-Things (IoT) concrete sensing system that addresses the challenge of using antiquated testing methods in the construction industry, often leading to schedule delays and cost overruns.
Built on the success of Phase I project, this program will develop a complete solution for scaling up productions.
A systematic hardware production and quality control procedure will be established, key parameters for a reproducible production line will be determined, and instrumentation errors will be minimized.
Concurrently, a scalable cloud backend will be developed, capable of serving tens of thousands of dataloggers while ensuring data security and low latency.
The machine learning algorithm will be further refined to provide fast and accurate strength inferences.
A full-scale production and stress testing of the sensor system in real-life conditions will also be conducted to evaluate the robustness and user experience.
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.
Subawards are not planned for this award.
Awardee
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NSF SMALL BUSINESS INNOVATION RESEARCH PHASE II (SBIR)/ SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAMS PHASE II", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF23516
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
West Lafayette,
Indiana
47906-2153
United States
Geographic Scope
Single Zip Code
Wavelogix was awarded
Cooperative Agreement 2404015
worth $999,910
from National Science Foundation in September 2024 with work to be completed primarily in West Lafayette Indiana United States.
The grant
has a duration of 2 years and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
The Cooperative Agreement was awarded through grant opportunity NSF Small Business Innovation Research / Small Business Technology Transfer Phase II Programs (SBIR/STTR Phase II).
SBIR Details
Research Type
SBIR Phase II
Title
SBIR Phase II: Prototyping Internet of Things (IoT) Sensing Platform for Infrastructure Monitoring
Abstract
The broader impact/commercial potential of this SBIR Phase II project is to deploy a novel concrete strength sensing technology to provide smart solutions to construction industry. This groundbreaking technology will transform construction industry by enabling faster, data-driven decisions through real-time data of concrete strength monitoring. Short-term, this technology will allow accelerated project timelines and eliminate costly quality control errors. Long term, this technology will leverage the power of big data to enable data-driven decision making and optimization of concrete mix design which will drastically reduce carbon footprint, eliminate wastes, and lead to more durable concrete infrastructures. By leveraging AI and big data analysis of the vast amount of structural health data collected, the project paves the way for the development of AI-powered solutions for predictive maintenance and improved construction practices.
The proposed project will focus on developing the market ready Internet-of-Things (IoT) concrete sensing system that addresses the challenge of using antiquated testing methods in construction industry, often leading to schedule delays and costs overrun. Built on the success of Phase I project, this program will develop a complete solution for scaling up productions. A systematic hardware production and quality control procedure will be established, key parameters for a reproducible production line will be determined, and instrumentation errors will be minimized. Concurrently, a scalable cloud backend will be developed, capable of serving tens of thousands of dataloggers while ensuring data security and low latency. The machine learning algorithm will be further refined to provide fast and accurate strength inferences. A full-scale production and stress testing of the sensor system in real-life conditions will also be conducted to evaluate the robustness and user experience.
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.
Topic Code
I
Solicitation Number
NSF 23-516
Status
(Ongoing)
Last Modified 9/17/24
Period of Performance
9/1/24
Start Date
8/31/26
End Date
Funding Split
$999.9K
Federal Obligation
$0.0
Non-Federal Obligation
$999.9K
Total Obligated
Activity Timeline
Additional Detail
Award ID FAIN
2404015
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
HZ17E6BSWLM3
Awardee CAGE
91YL7
Performance District
IN-04
Senators
Todd Young
Mike Braun
Mike Braun
Modified: 9/17/24