A Smart Assistance System for Increasing the Safety of Transportation Workers
This project aims to design and prototype a smart system for assisting transportation workers in operations. The system is architected as a cyber-physical system (CPS) to create the abilities to sense and monitor transportation workers in their workplace, assess and predict their risk exposure and awareness levels, and assist them in operations, in a near real-time manner. The project employs methods of system analytics to build the digital twin of the physical system - transportation workers operating in the workplace. The digital twin is able to process and analyze incident report data, and sensed data of workers and their workplace, to model, understand, and predict worker operations, as well as to evaluate risk exposure in the workplace. The project further uses sensing, communication, and feedback technologies to seamlessly integrate the digital twin with its physical system to allow for real-time interaction and collaboration between them. Results from the project confirms the effectiveness of the proposed approach to architecting, creating, and functioning the smart assistance system for transportation workers. The delivered prototype model has provided a foundation for improving and implementing the safety enhancement system.
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Supplemental Notes:
- This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program. Supporting datasets available at: https://doi.org/10.32873/unl.dr.20190212; https://rosap.ntl.bts.gov/view/dot/65528
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Corporate Authors:
Mid-America Transportation Center
University of Nebraska-Lincoln
2200 Vine Street, PO Box 830851
Lincoln, NE United States 68583-0851Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 Rolla, MO United States 65409-0710 -
Authors:
- Qin, Ruwen
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0000-0003-2656-8705
- Long, Suzanna
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0000-0001-6589-5528
- Godse, Pranav
- Al-Amin, Md
- Karim, Mohammad Monjurul
- Linville, Katherine
- Xue, Jian
- Publication Date: 2018-12
Language
- English
Media Info
- Media Type: Digital/other
- Edition: Final Report
- Features: Figures; Photos; References; Tables;
- Pagination: 77p
Subject/Index Terms
- TRT Terms: Detection and identification systems; Hazardous materials; Occupational safety; Personnel; Prototypes; Real time information; Risk assessment; Sensors; Systems analysis; Workplaces
- Subject Areas: Data and Information Technology; Safety and Human Factors; Transportation (General);
Filing Info
- Accession Number: 01696718
- Record Type: Publication
- Report/Paper Numbers: 25-1121-0005-130-1, MATC-MS&T: 130-1
- Contract Numbers: 69A3551747107
- Files: UTC, NTL, TRIS, ATRI, USDOT
- Created Date: Feb 28 2019 4:37PM