Smart Tracking Data Network for Shipment by Inland Waterway

Project: Research direct

Project Details


Inland waterway transport emits three times less CO2 as compared to road transport. Inland waterway transport is predominantly used for high volume transport, where a barge can replace many trucks. Frequently, the cargo for inland waterway transport consists of diversified small volumes, which are shipped, transported and received by SMEs. However, the related transport plans may be complex and diversified.The ST4W project aims to convince cargo shippers to take steps for modal shift, i.e, from road transport to inland waterway transport. Our focus would be the transport of palletized goods.

Pallets are loaded on barges and/or consolidated together in containers and then are transported using the waterway. The logistics planning required for this consolidation demands careful synchronization between all stakeholders, e.g., shippers, logistics service providers, customs, port authorities, terminal operators and barge owners. Efficient planning requires a collaborative approach aided by organizational and behavioral changes w.r.t all stakeholders.
Effective tools for communication which are (a) simple to learn and use, (b) inexpensive and (c) exploit data exchange standards are essential for the impetus of inland waterway transport. However, no integrated solution tool for inland waterway transport exists. Comparable solutions tools for maritime transport are too expensive for SMEs and are less applicable for the inland waterway transportation sector. These concerns are even more critical in the North-West Europe (NWE) region, which accounts for 85% of inland waterway transport in Europe.
Therefore, ST4W project will offer companies a simple and inexpensive inland waterway transport management tool. The tool will allow seamless sharing of hierarchical cargo tracking data among stakeholders. The tool will exploit the services of the existing River Information System (RIS) in Europe.
The tool will be tested and deployed during the project with the help of various relevant stakeholders, facilitated by the project partners. This will enable the stakeholders to develop long-term close cooperation among themselves, subsequently leading shippers to take concrete steps towards modal shift. This will ultimately lead to a reduction in CO2 emission. The impact of the project after 10 years will allow a modal shift of 600 million, a gain of 40 000 T of CO2 in the 10th year.

ST4W project is a consortium of leading research institutes, logistics companies and IT consultancies in North Western Europe. Together we design, develop and deploy a simple yet efficient tool for hierarchical tracking of palletized goods on inland waterways. The tool will lead to better visibility of the transport chains and help reduce CO2 emissions.

Layman's description

Designing, developing and deploying a simple yet efficient tool for hierarchical tracking of palletized goods on inland waterways

Key findings

Multitel (Lead Partner), CRITT T&L, Logistics in Wallonia, TU/e, Stichting Bureau Telematica Binnenvaart, Institut du droit international des transports, Stichting Projecten Binnevaart, Port Autonome du Centre et de lÓuest, Port de Bruxelles - Haven van Brussel, Universitat Duisburg-Essen, Blue Line Logistics and Inlecom Systems.
Short titleSmart Track 4 Waterway
Effective start/end date20/09/1731/12/21


  • logistics
  • transport
  • pallets
  • NWE
  • Inter-reg


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
  • Modeling complex business environments for context aware systems

    Singh, P., Veelenturf, L. P. & van Woensel, T., 1 Jan 2020, Enterprise, Business-Process and Information Systems Modeling - 21st International Conference, BPMDS 2020, 25th International Conference, EMMSAD 2020, Held at CAiSE 2020, Proceedings. Nurcan, S., Reinhartz-Berger, I., Soffer, P. & Zdravkovic, J. (eds.). Springer, p. 242-256 15 p. (Lecture Notes in Business Information Processing; vol. 387 LNBIP).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review