SBIR-STTR Award

The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to decrease the number of overweight trucks on the roads by developing a financially and technically practical screening tool to detect overweight vehicles on most roads in real-time. Overweight commercial vehicles are a significant cause of the nation's crumbling roads and bridges besides being a prime threat to transportation safety. The proposed project addresses the issue of effectively detecting overweight trucks on roads using real-time video-images while neither interfering with the traffic flow nor integrity the pavement. The proprietary system, WeighCam system, includes proprietary electro-optical system, algorithms, and system design. It will be easy to operate and robust in the sense that it will reliably work in most ambient environmental conditions such as ambient luminosity changes, etc. The purpose of this research will be to validate the basics of the system and calibrate the measurements using known weights to deduce the system limitations and to establish the feature sets of the Minimum Viable Product (MVP), a necessary step to start the manufacture of a commercial prototype. The final prototype will be a practical, autonomous, quick to install, and continuously operating continuous system sending data in real time. 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 award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).This Small Business Innovation Research Phase II project focuses on the detection and deterrence of overweight vehicles on roads. This technology is developing a practical, economical, and reliable real-time screening tool that does not interfere with traffic flow. Overweight commercial vehicles are a significant contributor to the nation's crumbling roads and bridges because the damage to a road surface increases substantially with the relative load, e.g., the road damage caused by an 80,000-pound truck is thousands of times that of a car which is twenty times lighter than the truck. Any efforts to renovate or build new infrastructures will be hindered without addressing this issue broadly. Nearly 71% of U.S freight ? representing $700.3 billion in economic activity in 2017 ? moves via trucks. Also, overweight trucks are a significant safety risk. Being overweight reduces the maneuverability of the massive vehicle and causes the truck's mechanical components to be prone to failure, which in turn often causes crashes, with significant human and economic tolls, especially if the load is hazardous. The intellectual merit of this project is to effectively and reliably measure the weight of a vehicle and consistently detect overweight trucks without interfering with the traffic flow or the integrity of the pavement. The proposed fully-automated system is a disruptive technology that is non-intrusive and infers the weight of vehicles from a distance using a novel, ultra-high-spatial-resolution, electro-optical system. The product is a user-friendly mobile application that displays to subscribers (government agencies or firms in the private sector) the weight of the relevant vehicle in real time. The proposed system is an internet-of-things system, a combination of proprietary electro-optical system, algorithms, signal processing, artificial intelligence and deep learning, system design and integration.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.