Multimodal Extreme Scale Data Analytics for Smart Cities Environments

< Back to search results

Multimodal Extreme Scale Data Analytics for Smart Cities Environments

Acronym

MARVEL

Project description

The “Smart City” paradigm aims to support new forms of monitoring and managing of resources as well as to provide situational awareness in decision-making fulfilling the objective of servicing the citizen, while ensuring that it meets the needs of present and future generations with respect to economic, social and environmental aspects. Considering the city as a complex and dynamic system involving different interconnected spatial, social, economic, and physical processes subject to temporal changes and continually modified by human actions. Big Data, fog, and edge computing technologies have significant potential in various scenarios considering each city individual tactical strategy. However, one critical aspect is to encapsulate the complexity of a city and support accurate, cross-scale and in-time predictions based on the ubiquitous spatio-temporal data of high-volume, high-velocity and of high-variety. To address this challenge, MARVEL delivers a disruptive Edge-to-Fog-to-Cloud ubiquitous computing framework that enables multi-modal perception and intelligence for audio-visual scene recognition, event detection in a smart city environment. MARVEL aims to collect, analyse and data mine multi-modal audio-visual data streams of a Smart City and help decision makers to improve the quality of life and services to the citizens without violating ethical and privacy limits in an AI-responsible manner. This is achieved via: (i) fusing large scale distributed multi-modal audio-visual data in real-time; (ii) achieving fast time-to-insights; (iii) supporting automated decision making at all levels of the E2F2C stack; and iv) delivering a personalized federated learning approach, where joint multi modal representations and models are co-designed and improved continuously through privacy aware sharing of personalized fog and edge models of all interested parties.
Show more

Starting year

2021

End year

2023

Granted funding

326 250 €
Participant
SPHYNX TECHNOLOGY SOLUTIONS AG (CH)
490 000 €
Participant
AARHUS UNIVERSITET (DK)
334 610 €
Participant
AUDEERING GMBH (DE)
346 925 €
Participant
INFORMATION TECHNOLOGY FOR MARKET LEADERSHIP (EL)
433 750 €
Participant
COMUNE DI TRENTO (IT)
210 000 €
Participant
INSTYTUT CHEMII BIOORGANICZNEJ POLSKIEJ AKADEMII NAUK (PL)
224 000 €
Participant
FONDAZIONE BRUNO KESSLER (IT)
377 500 €
Participant
INTRASOFT INTERNATIONAL SA (LU)
345 000 €
Participant
UNIVERZITET U NOVOM SADU FAKULTET TEHNICKIH NAUKA (RS)
301 301 €
Participant
INFINEON TECHNOLOGIES AG (DE)
407 500 €
Participant
CONSIGLIO NAZIONALE DELLE RICERCHE (IT)
412 500 €
Participant
ATOS SPAIN SA (ES)
355 000 €
Participant
IDRYMA TECHNOLOGIAS KAI EREVNAS (EL)
506 250 €
Coordinator
GREENROADS LIMITED (MT)
258 750 €
Participant
ZELUS IKE (EL)
446 250 €
Participant

Amount granted

5 998 086 €

Funder

European Union

Funding instrument

Research and Innovation action

Framework programme

Horizon 2020 Framework Programme

Call

Programme part
INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT) (H2020-EU.2.1.1.)
Topic
Big Data technologies and extreme-scale analytics (ICT-51-2020)
Call ID
H2020-ICT-2020-1

Other information

Funding decision number

957337