Big Data will have a profound economic and societal impact on the mobility and logistics sector, which is one of the most-used industries in the world contributing to approximately 15% of GDP.
Big Data is expected to lead to $500 billion in value worldwide due to time and fuel savings, as well as a significant environmental impact by saving an estimated 380 megatons of CO2 just in the mobility and logistics sector. With freight transport activities projected to increase by 40% in 2030, transforming the current mobility and logistics processes to become significantly more efficient will have a profound impact. A 10% efficiency improvement may lead to cost savings of €100 billion in the EU. Despite these promises, merely 19% of EU mobility and logistics companies employ Big Data solutions as part of value creation and business processes.Big Data Decision Support
The Transforming Transport (TT) project will demonstrate the transformative effects that Big Data will have on the mobility and logistics market. To this end, TT validates the technical and economic viability of Big Data to reshape transport processes and services to significantly increase operational efficiency, deliver improved customer experience, and foster new business models.
TT will address seven pilot domains of major importance for the mobility and logistics sector in Europe:
IT Innovation's work in TT focuses on the Proactive Rail Infrastructures pilot, using our expertise in Big Data analytics, machine learning, data mining and knowledge modelling for investigating the rail network's mechanical and electrical assets in order to provide health assessment and making prognosis of implications for the assets' maintenance regimes. This work builds on projects such as TRIDEC and ZONeSEC.
The Transforming Transport project is a 29 month project funded by the EC H2020 ICT framework programme.
Coordinator: Indra Sistemas SA, Spain
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 731932.