Five projects awarded within compartment 2 of the ‘Big Data: real time ICT for logistics’ research

25 July 2017

In the beginning of July the Science domain and Social Sciences and Humanities domain of NWO have granted five applications within compartment 2 of the ‘Big Data: real time ICT for logistics’ research programme. The budget for compartment 2 is 2,8 million euro (M€ 2,8) and was made available by NWO and the Ministry of Economic Affairs.

Big Data: Real Time ICT for Logistics focusses on scientific research which enables innovative big data applications in the logistics sector. The call for proposals has been divided into two compartments of which compartment 2 focusses on three main subjects:

  1. Internet of Things in logistics;
  2. Data fusion across infrastructure, vehicles and cargo;
  3. Data security in logistics.

Big Data: Real Time ICT for Logistics is part of the Commit2Data initiative. Commit2Data is a national public-private research- and innovation program which focuses on data science, stewardship, and technology relevant for the Dutch top sectors and will last several years. The goal of Commit2Data is too keep and strengthen de Dutch top 5 position in Big Data.

The following research projects have been granted:

Real-Time Data for Products to Move  Data-Driven Real-Time Decision Making in Supply Chains and Logistics
Main applicant: Prof. dr. T. van Woensel, Technische Universiteit Eindhoven

The purpose of this project is to develop and demonstrate real-time data-driven logistics methods and techniques, with a specific focus on inventory transhipment and transport. Stock decisions (e.g., transhipment, Omni-channels, Chain positioning) lead to transport decisions (e.g. vehicle routes, capacity, fleet). With the Internet-of-Things as one of the most important drivers, data-driven decision making in logistics is now more and more achievable, but successful implementations depend critically on the question "how?". For this, innovative research in combination with practical implementation is necessary.

ToGRIP: GRIP on freight TRIPS
Main applicant: Dr. M. Snelder, Technische Universiteit Delft, TNO

For shippers, carriers and terminal operations it is important to have reliable and predictable travel and handling times. In this project, a data-driven integrated traffic and logistics model will be developed that will be used to design interventions to combat travel time unreliability and to improve logistic operations.

Real-time data-driven maintenance logistics
Main applicant: Prof. dr. ir. G.J.J.A.N. van Houtum, Technische Universiteit Eindhoven

Because of Internet-of-Things, companies have a lot of real-time data about assets and spare parts. This real-time data gives companies the opportunity to organize the maintenance of assets more efficiently. Companies should therefore transition from static, time-driven towards dynamic, data-driven maintenance processes. This project develops techniques to support this transition

DataRel - Big Data for Resilient Logistics
Main applicant: Prof. dr. ing. P.J.M. Havinga, Universiteit Twente

The logistics sector is undergoing major changes and is facing many challenges. The use of innovative IoT technology and big data is a possible solution to this. DATAREL aims at advancing the logistic knowledge for detecting emergence to improve the quality control and multimodal planning in terms of resilience, real time, efficiency, and dynamics.

Secure scalable policy-enforced distributed data processing
Main applicant: Dr. ir. M.M.J. Stevens, Centrum Wiskunde & Informatica

This project combines Big Data, High Performance Computing and Cryptology in multidisciplinary fundamental and applied research. This research aims to develop integrated secure, end-to-end trusted, scalable and future-proof solutions for the problem of policy-enforced distributed data sharing and processing across multiple logistic domains.

More information on Big Data: real time ICT for logistics - compartiment 2




Source: NWO