SBIR/STTR Research Award

STTR Phase I: Internet of Things (IOT) Safety Device and System for Micro-Mobility Products

Award identifier efe66efcda187a4a2548ad0b4a50913adba5e5fe4393b8cca49225440393bcecAwarding agency National Science Foundation

Award amount

$275,000

Program and phase

STTR · Phase I

Award year

2023

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
Systems Research & Consulting LLC
Proposal award date
2023-04-01
Contract end date
2024-03-31
UEI
L74XLMVCBNJ7
Solicitation number
NSF 22-551
Topic code
I

Research 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.

Technology keywords

Not reported

Agency intelligence

National Science Foundation

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