Nowadays, only 3% of container terminals are automatized. However, the future of the port industry point towards smart ports since it is the only way to overcome the challenges and demands that arise in the sector, optimizing port operations, enhancing the supply chain of operators and carriers, and reducing the emissions and waste.
Nevertheless, the maritime port infrastructure is quite complex. On a side, a large number of agents interferes in each port operation (retailer, freight forwarder, carrier, consignee, port authority, etc.) thus stagnant silos of information are produced and the real potential of the data cannot be obtained. From this need appears the DataPorts project, a Data Platform for the Cognitive Ports of the Future.
The project is devoted to the creation of a secure data platform that allows sharing the information not only between port agents but also between other ports. Hence, this is a secure environment of data exchange in a reliable and trustworthy manner, with access permits and contracts to allow data sharing and the exploration of new Artificial Intelligence and cognitive services. DataPorts platform aims at providing to seaports a secure and private aware-environment where data coming from different sources can be shared by the stakeholders in a trusted and reliable way, in order to get real value from those data, providing a set of novel AI and cognitive tools to the port community.
- INSTITUTO TECNOLOGICO DE INFORMATICA
- TRAXENS SAS
- IBM ISRAEL
- HELLENIC TELECOMMUNICATIONS ORGANIZATION
- EVERIS SPAIN SL
- UNIVERSITAT POLITECNICA DE VALENCIA
- INSTITUTE OF COMMUNICATION AND COMPUTER SYSTEMS
- UNIVERSITAET DUISBURG-ESSEN
- ETHNIKO KENTRO EREVNAS KAI TECHNOLOGIKIS ANAPTYXIS
- FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V.
- Thessaloniki Port Authority SA
- FUNDACION DE LA COMUNIDAD VALENCIANA PARA LA INVESTIGACION, PROMOCION Y ESTUDIOS COMERCIALES DE VALENCIAPORT
Programm: Horizon 2020
Typ: Innovation Action
Fördersumme: 425.000 EUR (Gesamtfördersumme 5,7 Mio. EUR)
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 871493