Abstract The goal of this research is to deliver a cost-effective smart system that can monitor transportation workers (e.g., drivers and operators of hazardous materials transportation), assess their risk exposure and awareness levels, and assist them in operations, in a near real-time manner and for the purpose of safety enhancement. The first-year project we propose aims to deliver the prototype model of this system. A sensor subsystem will be first developed for acquiring well-rounded real-time information of transportation workers in operations. Then, statistical-based methods will be created for processing the sensed data for estimating the risk exposure and awareness levels of workers. The improvement in estimating the metrics of interests using integrated sensor data will be tested. The prototype model provides a foundation for testing, demonstrating, and completing the smart assistance system.
Deliverables
Download the Final Report
Final Data:
https://doi.org/10.32873/unl.dr.20190212