Summary
EMERALDS’s vision is to design, develop and create an urban data-oriented Mobility Analytics as a Service (MAaaS) toolset, consisting of the so-called ‘emeralds’ services, compiled in a proof-of-concept prototype, capable of exploiting the untapped potential of extreme urban mobility data. The toolset will enable the stakeholders of the urban mobility ecosystem to collect and manage ubiquitous spatio-temporal data of high-volume, high-velocity and of high-variety, analyse them both in online and offline settings, import them to real-time responsive AI/ML algorithms and visualize results in interactive dashboards, whilst implementing privacy preservation techniques at all data modalities and at all levels of its architecture. The toolset will offer advanced capabilities in data mining (searching and processing) of large amounts and varieties of urban mobility data and its efficiency will be assessed, validated and demonstrated in three TRL5 pilot use cases (by following a co-development approach with mobility and city stakeholders to improve decision making in urban smart city environments), and deployed/showcased in two early adopters’ data-driven TRL6 applications (by integrating the new services to existing systems to improve commercial offerings).
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More information & hyperlinks
Web resources: | https://cordis.europa.eu/project/id/101093051 |
Start date: | 01-01-2023 |
End date: | 31-12-2025 |
Total budget - Public funding: | 4 998 938,00 Euro - 4 998 438,00 Euro |
Cordis data
Original description
EMERALDS’s vision is to design, develop and create an urban data-oriented Mobility Analytics as a Service (MAaaS) toolset, consisting of the so-called ‘emeralds’ services, compiled in a proof-of-concept prototype, capable of exploiting the untapped potential of extreme urban mobility data. The toolset will enable the stakeholders of the urban mobility ecosystem to collect and manage ubiquitous spatio-temporal data of high-volume, high-velocity and of high-variety, analyse them both in online and offline settings, import them to real-time responsive AI/ML algorithms and visualize results in interactive dashboards, whilst implementing privacy preservation techniques at all data modalities and at all levels of its architecture. The toolset will offer advanced capabilities in data mining (searching and processing) of large amounts and varieties of urban mobility data and its efficiency will be assessed, validated and demonstrated in three TRL5 pilot use cases (by following a co-development approach with mobility and city stakeholders to improve decision making in urban smart city environments), and deployed/showcased in two early adopters’ data-driven TRL6 applications (by integrating the new services to existing systems to improve commercial offerings).Status
SIGNEDCall topic
HORIZON-CL4-2022-DATA-01-05Update Date
09-02-2023
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