RippleGo - An AI-based Voyage Planner for US Inland Waterways

被引:0
|
作者
Sathiaraj, David [1 ]
Smith, Andrew [1 ]
Rohli, Eric [1 ]
Hsieh, Cathy [1 ]
Salindong, Arthur [1 ]
Woolsey, Nicholas [1 ]
Tec, Andres [1 ]
机构
[1] Trabus Technol, San Diego, CA 92108 USA
关键词
D O I
10.1109/CAI54212.2023.00162
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
RippleGo (https://www.ripplego.com) is an AI-based Software-as-a-Service application that makes voyages along the US Inland Waterways (IWS) safe and efficient. These voyages require enormous planning and data collection processes. Existing mariner data is available in disparate locations and lacks predictive or forecasting information. This makes a mariner's voyage planning processes manual, ad-hoc, and present-minded. RippleGo utilizes two AI-based predictive technologies. The first technology is a deep learning based algorithm to forecast river levels. Advanced knowledge of river levels help in planning cargo loads and safely navigating under bridges and through locks. The second AI technology is a machine learning based technology that predicts time taken to travel from one point to any other point along the waterways. Advanced information on travel time will enable mariners to provide accurate ETAs to customers and port terminals and improve supply chain reliability. RippleGo combines the two methodologies to provide efficient voyage plans with better situational awareness, safety alerts (through Bridge Air Gap (BAG) and Under Keel Clearances (UKC)), improved reliability of delivery, and better utilization of water transportation ports and terminals.
引用
收藏
页码:372 / 373
页数:2
相关论文
共 50 条
  • [1] US MONITORS DISCHARGES INTO INLAND WATERWAYS
    不详
    CHEMICAL & ENGINEERING NEWS, 1971, 49 (18) : 21 - &
  • [2] A Master Attack Methodology for an AI-Based Automated Attack Planner for Smart Cities
    Falco, Gregory
    Viswanathan, Arun
    Caldera, Carlos
    Shrobe, Howard
    IEEE ACCESS, 2018, 6 : 48360 - 48373
  • [3] ECONOMIC IMPACTS OF RECREATIONAL USE OF INLAND WATERWAYS IN US
    Cui, Yue
    Chang, Wen-Huei
    Mahoney, Ed
    INTERNATIONAL JOURNAL OF TRANSPORT ECONOMICS, 2015, 42 (02) : 171 - 189
  • [4] An AI-based analysis of zoning reforms in US cities
    Arianna Salazar-Miranda
    Emily Talen
    Nature Cities, 2025, 2 (4): : 304 - 315
  • [5] AI-based optimization for US-guided radiation therapy of the prostate
    Stefan Gerlach
    Theresa Hofmann
    Christoph Fürweger
    Alexander Schlaefer
    International Journal of Computer Assisted Radiology and Surgery, 2022, 17 : 2023 - 2032
  • [6] AI-based optimization for US-guided radiation therapy of the prostate
    Gerlach, Stefan
    Hofmann, Theresa
    Fuerweger, Christoph
    Schlaefer, Alexander
    INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY, 2022, 17 (11) : 2023 - 2032
  • [7] Tube Based Safe Planning on Natural Inland Waterways
    Nadales, Juan M.
    Munoz de la Pena, David
    Limon, Daniel
    Alamo, Teodoro
    2022 EUROPEAN CONTROL CONFERENCE (ECC), 2022, : 2012 - 2017
  • [8] Impact of Conventional and AI-based Image Coding on AI-based Face Recognition Performance
    Bousnina, Naima
    Ascenso, Joao
    Correia, Paulo Lobato
    Pereira, Fernando
    2022 10TH EUROPEAN WORKSHOP ON VISUAL INFORMATION PROCESSING (EUVIP), 2022,
  • [9] On IIoT and AI-based optimization
    Mikolajewski, Dariusz
    Czerniak, Jacek
    Piechowiak, Maciej
    Wȩgrzyn-Wolska, Katarzyna
    Kacprzyk, Janusz
    Bulletin of the Polish Academy of Sciences: Technical Sciences, 2023, 71 (06)
  • [10] AI-based image synthesis
    Maspero, M.
    RADIOTHERAPY AND ONCOLOGY, 2023, 182 : S426 - S426