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Predictive Analytics-Based US Inland Waterways Voyage Planning Analysis Tool (VSAT)

Award Information
Agency: Department of Energy
Branch: N/A
Contract: DE-SC0018477
Agency Tracking Number: 0000234251
Amount: $150,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: 01a
Solicitation Number: DE-FOA-0001770
Timeline
Solicitation Year: 2018
Award Year: 2018
Award Start Date (Proposal Award Date): 2018-04-09
Award End Date (Contract End Date): 2018-10-08
Small Business Information
3547 Camino Del Rio South Suite A
San Diego, CA 92108-4024
United States
DUNS: 833148427
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: Yes
Principal Investigator
 Joseph Celano
 (619) 220-8000
 joec@trabus.com
Business Contact
 Joseph Celano
Phone: (619) 220-8000
Email: joec@trabus.com
Research Institution
 Louisiana State University
 David Sathiaraj
 
202 Hime Hall
Baton Rouge, LA 70803-0001
United States

 (225) 802-4248
 Nonprofit College or University
Abstract

Trabus Technologies (TRABUS), working with Louisiana State University (LSU), will develop a predictive analytics-based US Inland Waterways Voyage Planning Analysis tool to help vessel traffic managers, tow boat pilots, and river lock operators maximize transport logistic resources. This tool will use current and forecasted hydrographic, meteorological, lock status, and Marine Safety Information to help commercial cargo operators and the Marine Industry determine optimal barge loading and tow configuration for any specified commodity/cargo movement. When planning any journey using US Inland Waterways, commercial cargo operators must manually consider a vast range of complex factors to determine optimal load for every vessel to ensure efficient and safe passage for its entire journey, which often includes rapidly-changing environmental conditions. For example, a 4-inch change in river level (from rain a week after departure) correlates to a 72-ton variance in a large barge’s capacity; operators must predict this change or risk hundreds of thousands of dollars of revenue per journey. A machine learning based predictive tool to rapidly process current and forecasted conditions would provide the Marine Industry with greater voyage planning and efficient transport management. Developed by TRABUS for the US Army Corps of Engineers (USACE), the River Information Services Enterprise (RISE) provides the technical framework enabling collection, integration, and exchange of navigation and vessel logistics information for safe, efficient, reliable, and environmentally responsible navigation between the Marine Industry and Government. Develop predictive algorithms and data-driven analytics for a commercial cloud-based Voyage/Transport Planning Service to maximize transport commodities and minimize intermodal transfers. Leverage ongoing RISE BigData efforts to analyze data from US Geological Survey (USGS), USACE Lock Performance Monitoring System, US Coast Guard’s Notice to Mariners, and Marine Industry’s barge, vessel, commodity, and supply chain data. LSU will leverage its ongoing BigData expertise with NOAA, National Weather Service, and USGS data to develop the methodology.

* Information listed above is at the time of submission. *

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