Objective
Transportation sector undergoes a considerable transformation as it enters a new landscape where connectivity is seamless and mobility options and related business models are constantly increasing. Modern transportation systems and services have to mitigate problems emerging from complex mobility environments and intensive use of transport networks including excessive CO2 emissions, high congestion levels and reduced quality of life. Due to the saturation of most urban networks, innovative solutions to the above problems need to be underpinned by collecting, processing and broadcasting an abundance of data from various sensors, systems and service providers. Furthermore, such novel transport systems have to foresee situations in near real time and provide the means for proactive decisions, which in turn will deter problems before they even emerge. Our vision is to provide the required interoperability, adaptability and dynamicity in modern transport systems for a proactive and problem-free transportation system. OPTIMUM will establish a largely scalable, distributed architecture for the management and processing of multisource big-data, enabling continuous monitoring of transportation systems needs and proposing proactive decisions and actions in an (semi-) automatic way. OPTIMUM follows a cognitive approach based on the Observe, Orient, Decide, Act loop of the big data supply chain for continuous situational awareness. OPTIMUM's goals will be achieved by incorporating and advancing state of the art in transport and traffic modeling, travel behavior analysis, sentiment analysis, big data processing, predictive analysis and real-time event-based processing, persuasive technologies and proactive recommenders. The proposed solution will be deployed in real-life pilots in order to realise challenging use cases in the domains of proactive improvement of transport systems quality and efficiency, proactive charging for freight transport and Car2X communication integration.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- social sciencessocial geographytransportfreight transport
- natural sciencescomputer and information sciencesdata sciencebig data
- engineering and technologyenvironmental engineeringair pollution engineering
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- social sciencessocial geographytransportpublic transport
Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
1050 Bruxelles / Brussel
Belgium
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Participants (18)
106 82 ATHINA
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2829-516 Caparica
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1000 Ljubljana
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18000 Nis
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
1070 VIENNA
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
1210 Wien
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1120 Wien
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WV1 1LY Wolverhampton
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81100 Mytilini
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1050-153 Lisbon
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
55132 Kalamaria - Thessaloniki
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
2000 Szentendre
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2809 013 Lisboa
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8000 NOVO MESTO
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1000 Ljubljana
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B1 1BB Birmingham
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2670 501 LOURES LISBOA
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1253 Luxembourg
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