2232899
Project Grant
Overview
Grant Description
Sttr Phase I: Internet of Things (IoT) safety device and system for micro-mobility products - The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is the development of new technologies to enhance the safety of micro-mobility vehicles and fleets (bicycles, electronic bikes, and electric scooters).
Micro-mobility has a high potential to reduce congestion, emissions, and noise pollution in urban settings. These vehicles can address many first- and last-mile transportation challenges. The technology developed in this project will integrate low-cost sensors, advanced machine learning and model-based algorithms with Internet of Things (IoT)-based technologies for micro-mobility safety devices.
Furthermore, IoT-based early detection and warning systems can address safety concerns in the use of micro-mobility, resulting in the development of strong ecosystems. This Small Business Technology Transfer (STTR) Phase I project will develop and evaluate a cost-effective, innovative IoT technology and turn it into a product and service that are essential to the safety and reliability of the micro-mobility vehicles and fleets.
The technology involves predicting likely future failures in vehicle braking components and systems in advance of their occurrence as well as early detection of hazardous driving conditions (due to misbehavior of riders, road conditions, or weather conditions). The solution will issue warnings to the rider and proactive alerts with actionable recommendations (e.g., for proactive maintenance).
The project will develop and evaluate model-based and machine-learning-assisted algorithms for the detection, isolation, and prediction of failures and hazardous driving conditions as well as the associated level of confidence in the accuracy of the decisions. The performance of the safety device and operation under experimental conditions and constraints will be evaluated using end-to-end simulation and a testbed.
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.
Micro-mobility has a high potential to reduce congestion, emissions, and noise pollution in urban settings. These vehicles can address many first- and last-mile transportation challenges. The technology developed in this project will integrate low-cost sensors, advanced machine learning and model-based algorithms with Internet of Things (IoT)-based technologies for micro-mobility safety devices.
Furthermore, IoT-based early detection and warning systems can address safety concerns in the use of micro-mobility, resulting in the development of strong ecosystems. This Small Business Technology Transfer (STTR) Phase I project will develop and evaluate a cost-effective, innovative IoT technology and turn it into a product and service that are essential to the safety and reliability of the micro-mobility vehicles and fleets.
The technology involves predicting likely future failures in vehicle braking components and systems in advance of their occurrence as well as early detection of hazardous driving conditions (due to misbehavior of riders, road conditions, or weather conditions). The solution will issue warnings to the rider and proactive alerts with actionable recommendations (e.g., for proactive maintenance).
The project will develop and evaluate model-based and machine-learning-assisted algorithms for the detection, isolation, and prediction of failures and hazardous driving conditions as well as the associated level of confidence in the accuracy of the decisions. The performance of the safety device and operation under experimental conditions and constraints will be evaluated using end-to-end simulation and a testbed.
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.
Awardee
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Rochester,
Michigan
48306-3658
United States
Geographic Scope
Single Zip Code
Related Opportunity
None
Analysis Notes
Amendment Since initial award the total obligations have decreased 50% from $550,000 to $275,000.
Systems Research & Consulting was awarded
Project Grant 2232899
worth $275,000
from National Science Foundation in April 2023 with work to be completed primarily in Rochester Michigan United States.
The grant
has a duration of 1 year and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
SBIR Details
Research Type
STTR Phase I
Title
STTR Phase I: Internet of Things (IOT) Safety Device and System for Micro-Mobility Products
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is the development of new technologies to enhance the safety of micro-mobility vehicles and fleets (bicycles, electronic bikes, and electric scooters). Micro-mobility has a high potential to reduce congestion, emissions, and noise pollution in urban settings.These vehicles can address many first- and last-mile transportation challenges. The technology developed in this project will integrate low-cost sensors, advanced machine learning and model-based algorithms with Internet of Things (IOT)-based technologies for micro-mobility safety devices. Furthermore, IOT-based early detection and warning systems can address safety concerns in the use of micro-mobility, resulting in the development of strong ecosystems._x000D_ _x000D_ This Small Business Technology Transfer (STTR) Phase I project will develop and evaluate a cost-effective. innovative, IOT technology and turn it into a product and service that are essential to the safety and reliability of the micro-mobility vehicles and fleets. The technology involves predicting likely future failures in vehicle braking components and systems in advance of their occurrence as well as early detection of hazardous driving conditions (due to misbehavior of riders, road conditions, or weather conditions).The solution will issue warnings to the rider and proactive alerts with actionable recommendations (e.g., for proactive maintenance). The project will develop and evaluate model-based and machine-learning-assisted algorithms for the detection, isolation, and prediction of failures and hazardous driving conditions as well as the associated level of confidence in the accuracy of the decisions. The performance of the safety device and operation under experimental conditions and constraints will be evaluated using end-to-end simulation and a testbed._x000D_ _x000D_ 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 22-551
Status
(Complete)
Last Modified 4/5/23
Period of Performance
4/1/23
Start Date
3/31/24
End Date
Funding Split
$275.0K
Federal Obligation
$0.0
Non-Federal Obligation
$275.0K
Total Obligated
Activity Timeline
Additional Detail
Award ID FAIN
2232899
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
L74XLMVCBNJ7
Awardee CAGE
8AD98
Performance District
Not Applicable
Budget Funding
| Federal Account | Budget Subfunction | Object Class | Total | Percentage |
|---|---|---|---|---|
| Research and Related Activities, National Science Foundation (049-0100) | General science and basic research | Grants, subsidies, and contributions (41.0) | $275,000 | 100% |
Modified: 4/5/23